Evidence Report/Technology Assessment 

Number 162 

Therapeutic Management, Delivery, and Postpartum 

Risk Assessment and Screening in Gestational 

Diabetes 

Prepared for: 

Agency for Healthcare Research and Quality 

U.S. Department of Health and Human Services 

540 Gaither Road 

Rockville, MD 20850 

www.ahrq.gov 

Contract No. 290-02-0018 

Prepared by: 

The Johns Hopkins University Evidence-based Practice Center, Baltimore, MD 

Investigators 

Wanda K. Nicholson, M.D., M.P.H., M.B.A. 

Lisa M. Wilson, Sc.M. 

Catherine Takacs Witkop, M.D., M.P.H. 

Kesha Baptiste-Roberts, Ph.D., M.P.H. 

Wendy L. Bennett, M.D., M.P.H. 

Shari Bolen, M.D., M.P.H. 

Bethany B. Barone, Sc.M. 

Sherita Hill Golden, M.D., M.H.S. 

Tiffany L. Gary, Ph.D. 

Donna M. Neale, M.D. 

Eric B. Bass, M.D., M.P.H. 

AHRQ Publication No. 08-E004 

March 2008 
This report is based on research conducted by the Johns Hopkins University Evidence-based 

Practice Center (EPC) under contract to the Agency for Healthcare Research and Quality 

(AHRQ), Rockville, MD (Contract No. 290-02-0018). The findings and conclusions in this 

document are those of the author(s), who are responsible for its content, and do not 

necessarily represent the views of AHRQ. No statement in this report should be construed as 

an official position of AHRQ or of the U.S. Department of Health and Human Services. 

The information in this report is intended to help clinicians, employers, policymakers, and 

others make informed decisions about the provision of health care services. This report is

intended as a reference and not as a substitute for clinical judgment. 

This report may be used, in whole or in part, as the basis for the development of clinical 

practice guidelines and other quality enhancement tools, or as a basis for reimbursement and 

coverage policies. AHRQ or U.S. Department of Health and Human Services endorsement of 

such derivative products may not be stated or implied. 

 
ii 

This document is in the public domain and may be used and reprinted without permission except 

those copyrighted materials noted for which further reproduction is prohibited without the 

specific permission of copyright holders. 

Suggested Citation: 

Nicholson WK, Wilson LM, Witkop CT, Baptiste-Roberts K, Bennett WL, Bolen S, Barone BB, 

Golden SH, Gary TL, Neale DM, Bass EB. Therapeutic Management, Delivery, and Postpartum 

Risk Assessment and Screening in Gestational Diabetes. Evidence Report/Technology 

Assessment No. 162 (Prepared by the Johns Hopkins University Evidence-based Practice Center 

under Contract No. 290-02-0018.) AHRQ Publication No. 08-E004. Rockville, MD: Agency for 

Healthcare Research and Quality. March 2008.

No investigators have any affiliations or financial involvement (e.g., employment, 

consultancies, honoraria, stock options, expert testimony, grants or patents received or 

pending, or royalties) that conflict with material presented in this report. 
iii 

Preface 

 The Agency for Healthcare Research and Quality (AHRQ), through its Evidence-Based 

Practice Centers (EPCs), sponsors the development of evidence reports and technology 

assessments to assist public- and private-sector organizations in their efforts to improve the 

quality of health care in the United States. The reports and assessments provide organizations 

with comprehensive, science-based information on common, costly medical conditions and new 

health care technologies. The EPCs systematically review the relevant scientific literature on 

topics assigned to them by AHRQ and conduct additional analyses when appropriate prior to 

developing their reports and assessments. 

 To bring the broadest range of experts into the development of evidence reports and health 

technology assessments, AHRQ encourages the EPCs to form partnerships and enter into 

collaborations with other medical and research organizations. The EPCs work with these partner 

organizations to ensure that the evidence reports and technology assessments they produce will 

become building blocks for health care quality improvement projects throughout the Nation. The 

reports undergo peer review prior to their release. 

 AHRQ expects that the EPC evidence reports and technology assessments will inform 

individual health plans, providers, and purchasers as well as the health care system as a whole by 

providing important information to help improve health care quality. 

 We welcome comments on this evidence report. They may be sent by mail to the Task Order 

Officer named below at: Agency for Healthcare Research and Quality, 540 Gaither Road, 

Rockville, MD 20850, or by e-mail to epc@ahrq.gov. 

Carolyn M. Clancy, M.D. 

Director 

Agency for Healthcare Research and Quality 

Jean Slutsky, P.A., M.S.P.H. 

Director, Center for Outcomes and Evidence 

Agency for Healthcare Research and Quality 

Beth A. Collins Sharp, R.N., Ph.D. 

Director, EPC Program 

Agency for Healthcare Research and Quality 

Shilpa H. Amin, M.D., M.Bsc. 

EPC Program Task Order Officer 

Agency for Healthcare Research and Quality 
iv 

Acknowledgments 

The Evidence-based Practice Center thanks Gabriel Lai and Haeseong Park for their assistance 

with article reviewing and data entry; Karen Robinson for her guidance on the search strategy; 

Allison Jonas for her assistance with final preparations of the report; Deborah McClellan for 

copy editing; and Renee Wilson and Michael Oladubu for their assistance with the study. We 

would also like to acknowledge our technical expert panel: 

E. Albert Reece, M.D., Ph.D., M.B.A. 

Dean & Vice President for Medical Affairs 

University of Maryland School of Medicine 

Baltimore, MD 

Richard Hellman, M.D. 

Clinical Professor of Medicine 

University of Missouri – Kansas City School 

of Medicine 

Kansas City, MO 

Troy Flint Porter, M.D. 

University of Utah School of Medicine and 

Intermountain Health Care 

Salt Lake City, UT 

Jean M. Lawrence, Sc.D., M.P.H. 

Research Scientist II/Epidemiologist 

Research and Evaluation 

Kaiser Permanente Southern California 

Pasadena, CA 
v 

Structured Abstract 

Objectives: We focused on four questions: (1) What are the risks and benefits of an oral diabetes 

agent (i.e., glyburide), as compared to all types of insulin, for gestational diabetes? (2) What is 

the evidence that elective labor induction, cesarean delivery, or timing of induction is associated 

with benefits or harm to the mother and neonate? (3) What risk factors are associated with the 

development of type 2 diabetes after gestational diabetes? (4) What are the performance 

characteristics of diagnostic tests for type 2 diabetes in women with gestational diabetes? 

Data Sources: We searched electronic databases for studies published through January 2007. 

Additional articles were identified by searching the table of contents of 13 journals for relevant 

citations from August 2006 to January 2007 and reviewing the references in eligible articles and 

selected review articles. 

Review Methods: Paired investigators reviewed abstracts and full articles. We included studies 

that were written in English, reported on human subjects, contained original data, and evaluated 

women with appropriately diagnosed gestational diabetes. Paired reviewers performed serial 

abstraction of data from each eligible study. Study quality was assessed independently by each 

reviewer. 

Main Results: The search identified 45 relevant articles. The evidence indicated that (1) 

maternal glucose levels do not differ substantially in those treated with insulin versus insulin 

analogues or oral agents; (2) average infant birth weight may be lower in mothers treated with 

insulin than with glyburide; (3) induction at 38 weeks may reduce the macrosomia rate, with no 

increase in cesarean delivery rates; (4) anthropometric measures, fasting blood glucose (FBG), 

and 2-hour glucose value are the strongest risk factors associated with development of type 2 

diabetes; (5) FBG had high specificity, but variable sensitivity, when compared to the 75-gm oral 

glucose tolerance test (OGTT) in the diagnosis of type 2 diabetes after delivery. 

Conclusions: The evidence suggests that benefits and a low likelihood of harm are associated 

with the treatment of gestational diabetes with an oral diabetes agent or insulin. The effect of 

induction or elective cesarean on outcomes is unclear. The evidence is consistent that 

anthropometry identifies women at risk of developing subsequent type 2 diabetes; however, no 

evidence suggested the FBG out-performs the 75-gm OGTT in diagnosing type 2 diabetes after 

delivery. 
vii 

Contents 

Executive Summary.........................................................................................................................1 

Evidence Report...........................................................................................................................13 

Chapter 1. Introduction ..................................................................................................................15 

Conceptual Framework and Key Questions ............................................................................17 

Chapter 2. Methods........................................................................................................................23 

Topic Development..................................................................................................................23 

Search Strategy ........................................................................................................................23 

Study Selection ........................................................................................................................24 

Data Abstraction ......................................................................................................................26 

Study Quality Assessment .......................................................................................................26 

Data Synthesis..........................................................................................................................27 

Data Entry and Quality Control ...............................................................................................27

Rating the Body of Evidence ...................................................................................................28 

Peer Review .............................................................................................................................28 

 

Chapter 3. Results ..........................................................................................................................29 

Search Results..........................................................................................................................29 

Key Question 1 ........................................................................................................................29 

Background and Conceptual Framework...........................................................................29 

Results................................................................................................................................32 

Conclusions........................................................................................................................45 

Key Question 2 ........................................................................................................................45 

Background and Conceptual Framework...........................................................................46 

Results................................................................................................................................47 

Conclusions........................................................................................................................56 

Key Question 3 ........................................................................................................................57 

Background and Conceptual Framework...........................................................................57 

Results................................................................................................................................57 

Key Question 4 ........................................................................................................................73 

Background and Conceptual Framework...........................................................................73 

Results................................................................................................................................74 

Chapter 4. Discussion ....................................................................................................................81 

Summary of the Key Findings .................................................................................................81 

Key Question 1 ..................................................................................................................81 

Key Question 2 ..................................................................................................................83 

Key Question 3 ..................................................................................................................83 

Key Question 4 ..................................................................................................................84 

Conclusions..............................................................................................................................85 

Future Research .......................................................................................................................86 

Implications..............................................................................................................................88 
viii 

References......................................................................................................................................89 

List of Abbreviations .....................................................................................................................95 

Figures 

Figure 1. Conceptual framework for labor and postpartum management of women with 

gestational diabetes mellitus...........................................................................................18 

Figure 2. Summary of literature search and review process (number of articles) .........................30 

Figure 3. Conceptual framework of treatment effects on maternal and neonatal outcomes..........31 

Figure 4. Meta-analysis of three RCTs on the effect of insulin and glyburide on mean 

difference in infant birth weight .....................................................................................35 

Figure 5. Conceptual framework of the effects of gestational age, fetal weight, and labor 

management on maternal and neonatal outcomes .........................................................47 

Figure 6. Conceptual framework for Key Question 3 on risk factors for developing type 2 

diabetes following a pregnancy with gestational diabetes mellitus...............................58 

Figure 7. Summary of reported measures of association between anthropometric 

measures and the risk of developing type 2 diabetes following a pregnancy 

with gestational diabetes mellitus..................................................................................65 

Figure 8. Summary of selected reported measures of association between measures of 

metabolic risk factors and the risk of developing type 2 diabetes following a 

pregnancy with gestational diabetes mellitus ................................................................67 

Figure 9. Conceptual framework of performance characteristics of tests for diagnosing 

type 2 diabetes mellitus when conducted after pregnancy in patients with a 

history of gestational diabetes mellitus..........................................................................74 

Figure 10. Specificity of an FBG > 7.0 mmol/L (126 mg/dL) as compared to an FBG 

>7.8 mmol/L (140 mg/dL) threshold as part of the 2-hr 75-gm OGTT .......................79 

Figure 11. Sensitivity for studies of FBG level > 7.0 mmol/L (126 mg/dL) [comparison 

test] (ADA 1997) compared to the 75-gm OGTT [reference test] (WHO 

1999) ............................................................................................................................79 

Figure 12. Sensitivity and specificity of studies of FBG > 7.0 mmol/L (126 mg/dL) 

[comparison test] (ADA 1997) compared to the 75-gm OGTT [reference test] 

(WHO 1985) ................................................................................................................79 

Tables 

Table 1. List of outcomes reviewed...............................................................................................25 

Table 2. List of maternal and neonatal outcomes in which data was abstracted from RCTs 

of medications for gestational diabetes ...........................................................................33 

Table 3. Meta-analysis of three RCTs on the effect of insulin and glyburide on infant 

birth weight: random effects model.................................................................................35 

Table 4. Adverse events reported in RCTs of medications for gestational diabetes. 

Numbers are n (%)...........................................................................................................40 

Table 5. Summary table of eight studies examining the effect of delivery management on 

maternal and neonatal outcomes......................................................................................49 

Table 6. Threshold values for tests to diagnose type 2 diabetes mellitus postpartum...................74 
ix 

Table 7. Example of the calculation of sensitivity, specificity, and standard errors for 

tests diagnosing type 2 diabetes when conducted in postpartum gestational 

diabetes patients after pregnancy.....................................................................................75 

Appendixes 

Appendix A: Technical Experts and Peer Reviewers 

Appendix B: Hand Searched Journals 

Appendix C: Detailed Electronic Database Search Strategies 

Appendix D: List of Excluded Studies 

Appendix E: Data Abstraction Forms 

Appendix F: Evidence Tables 

Appendixes and Evidence Tables for this report are provided electronically at 

http://www.ahrq.gov/clinic/tp/gdmparttp.htm.
1 

Executive Summary 

Introduction 

Gestational diabetes mellitus (gestational diabetes), one of the most common medical 

complications of pregnancy, is defined as carbohydrate intolerance of variable degree, with an 

onset or first recognition occurring during pregnancy. Of the estimated 4 million births annually 

in the United States, gestational diabetes affects approximately 200,000 (7 percent), depending 

on the criteria (diagnostic test and threshold values) chosen for diagnosis. Initial diagnostic 

criteria for gestational diabetes were based on the ability to identify women at risk of developing 

type 2 diabetes, since 15 to 60 percent of women with gestational diabetes develop type 2 

diabetes mellitus within 5 to 15 years of delivery. Therefore, the diagnosis and subsequent 

management of gestational diabetes after delivery has important implications for the prevention 

of type 2 diabetes. Questions remain, however, about the optimal ways to assess the postpartum 

risk of diabetes and to screen women for diabetes after a diagnosis of gestational diabetes has 

been made. 

Equally important, gestational diabetes is associated with both maternal and infant 

complications, including maternal and neonatal hypoglycemia and complications of macrosomia, 

such as birth trauma and cesarean delivery. Treatment recommendations for gestational diabetes 

are based primarily on evidence from early trials suggesting that insulin treatment can reduce the 

incidence of macrosomia. To date, relatively little work has been done to synthesize more recent 

evidence regarding the management of maternal glucose or physicians’ decisions to recommend 

elective labor induction or cesarean delivery in women with gestational diabetes. 

Furthermore, while there is substantial literature regarding risk factors for type 2 diabetes, 

there has been no comprehensive review of these risk factors or the relative magnitude of their 

associations with type 2 diabetes. Finally, little work has been done to investigate the 

performance of postpartum glucose testing in women with gestational diabetes or to analyze the 

effect of performing the tests at different time intervals following delivery on the relative 

performance of current screening modalities. 

Because of the broad clinical and public health policy implications of the management of 

women with gestational diabetes, the American College of Obstetricians and Gynecologists 

(ACOG) requested an evidence report from the Agency for Healthcare Research and Quality 

(AHRQ) through the Evidence-based Practice Center program (EPC) to systematically and 

critically examine the literature on specific aspects of the management of gestational diabetes. 

We were guided in our key questions and outcomes of interest by the ACOG, the AHRQ, and 

our panel of technical experts. 

Our key questions were: 

1. What is the evidence for the risks and benefits of oral diabetes agents (e.g., secondgeneration sulfonylureas and metformin), as compared to all types of insulin, for both the 

mother and neonate in the treatment of women with gestational diabetes? 

a. How does maternal outcome vary based on the level of glucose at the initiation of a 

medication? 
2 

b. How does neonatal outcome vary based on the level of glucose at the initiation of a 

medication? 

Maternal outcomes 

• cesarean delivery 

• glycemic control (fasting 

blood glucose [FBG], 1-hour [hr] 

and 2-hr postprandial glucose 

[PPG]) 

• hemorrhage 

• hypoglycemia 

• operative vaginal delivery 

• perineal tears 

• pre-eclampsia 

• weight 

Neonatal outcomes 

• anoxia 

• birth trauma 

• birth weight 

• congenital malformations 

• hyperbilirubinemia 

• hypoglycemia 

• large for gestational age (LGA) 

• macrosomia 

• mortality 

• neonatal intensive care admissions 

• respiratory distress syndrome 

• shoulder dystocia 

• small for gestational age (SGA) 

2. What is the evidence that elective cesarean delivery or the choice of timing of induction 

in women with gestational diabetes results in beneficial or harmful maternal and neonatal 

outcomes? 

a. What is the evidence for elective cesarean delivery at term, as compared to an attempt 

at vaginal delivery (spontaneous or induced) at term, with regard to beneficial or 

harmful maternal and neonatal outcomes in gestational diabetes? 

i. cesarean versus spontaneous labor and vaginal delivery 

ii. cesarean versus induced labor and vaginal delivery 

iii. cesarean versus any attempt at vaginal delivery at term 

b. What is the evidence for labor induction at 40 weeks, as compared to labor induction 

at an earlier gestational age (less than 40 weeks) or spontaneous labor, with regard to 

beneficial or harmful maternal and neonatal outcomes in gestational diabetes? 

i. labor induction at less than 40 weeks versus labor induction at 40 weeks 

ii. labor induction at 40 weeks versus spontaneous labor 

iii. labor induction at less than 40 weeks versus spontaneous labor 

c. How is the estimated fetal weight (EFW) related to outcomes of management of 

gestational diabetes with elective cesarean delivery or the timing (i.e., gestational age 

range) of labor induction? 

d. How is gestational age related to outcomes of management of gestational diabetes 

with elective cesarean delivery or the choice of timing (i.e., gestational age range) of 

labor induction? 

Maternal outcomes 

• cesarean delivery 

• hemorrhage 

• infection 

• operative vaginal delivery 

• perineal tears 

Neonatal outcomes 

• same as Key Question 1 
3 

3. What risk factors, including but not limited to family history, physical activity, prepregnancy weight, and gestational weight gain, are associated with short-term and longterm development of type 2 diabetes following a pregnancy with gestational diabetes? 

4. What are the performance characteristics (sensitivity, specificity, and reproducibility) of 

tests for diagnosing type 2 diabetes after pregnancy in patients with a history of 

gestational diabetes? Are there differences in the performance characteristics of the test 

results based on subgroup analysis? 

Methods 

Approach to Evaluating the Literature 

We identified the primary literature on labor and postpartum management of gestational 

diabetes and the association with maternal and neonatal outcomes through a comprehensive 

search plan that included electronic and hand searching. We ran searches of the following 

databases for the specified periods of time: MEDLINE® (1950 through January 2007), 

EMBASE® (1974 through January 2007), The Cochrane Central Register of Controlled Trials 

(CENTRAL; Issue 1, 2007), and the Cumulative Index to Nursing & Allied Health Literature 

(CINAHL®; 1982 through January 2007). Hand searching for relevant citations took several 

forms. From our electronic search, we identified the 13 journals (see Appendix Ba) that were 

most likely to publish articles on this topic. We scanned the table of contents of each issue of 

these journals for relevant articles from August 2006 through January 2007. For the second form 

of hand searching, reviewers received eligible articles and flagged references of interest for the 

team to compare to the existing database. 

Two independent reviewers conducted title scans in a parallel fashion. If either reviewer 

thought that a title was potentially eligible, its abstract was reviewed. If the abstract was deemed 

to meet the inclusion criteria by two reviewers, the abstract was included in our article review. 

Any differences of opinion were resolved by the two primary reviewers or by a third independent 

reviewer. 

 Each eligible article underwent double review by study investigators. A primary reviewer 

completed all data abstraction forms, and a second reviewer confirmed the first reviewer’s data 

abstraction forms for completeness and accuracy. The reviewers assessed study quality 

independently. Reviewer pairs were formed to include personnel with both clinical and 

methodological expertise. A third reviewer re-reviewed a random sample of articles by the first 

two reviewers to ensure consistency in the abstraction of the articles. 

Quality Assessment 

We used several study quality assessment tools, based on the study design of the articles 

included in the review. Our dual, independent review of article quality judged articles on several 

aspects of each study type’s internal validity. Quality assessment of trials for Key Questions 1 

and 2 was based on the Jadad criteria and included: (1) whether the study was randomized, (2) 

the appropriateness of the randomization scheme, (3) whether the study was blinded, (4) the 

appropriateness of the blinding, and (5) the description of withdrawals and drop-outs. For each 
4 

trial, we created a score between 5 (high quality) and 0 (low quality). Quality assessment of 

observational studies for Key Questions 1, 2, and 3 was designed by selecting key elements from 

the Standards for Reporting of Observational Studies (STROBE) checklist for reporting 

observational studies. The STROBE checklist is based on the consensus of 27 participants of the 

Meta-analysis of Observational Studies in Epidemiology (MOOSE) group and includes 

recommendations for standards for individual studies with regard to the presentation of the study 

hypotheses, eligibility criteria, study population, power and sample size calculations, definitions 

of outcomes, and description of loss to followup and missing data. Quality assessment of the 

diagnostic test studies for Key Question 4 was designed by selecting key elements from the 

Standards for Reporting of Diagnostic Accuracy (STARD) Initiative and included items about 

reporting the sampling design, describing the lost-to-followup, reporting diagnostic accuracy, 

verifying positive and negative tests equally, interpreting the tests independently, reporting 

reproducibility, and reporting subgroup analyses. 

 Based on the quantity, quality, and consistency of the studies, we graded the overall body of 

evidence for each of the key questions using the evidence-grading scheme recommended by the 

GRADE Working Group. 

Analysis 

 We conducted meta-analyses when there were sufficient data (three or more studies) and the 

studies were homogeneous with respect to key variables (population characteristics, study 

duration, intervention/exposure/comparison tests, and length of followup). When the data were 

not sufficient to allow us combine the studies in a meta-analysis, we prepared a qualitative 

summary of the results. 

Results 

Search Results 

We retrieved 11,400 unique citations from our original search. After reviewing the titles and 

abstracts, 552 were deemed eligible for further review, and the full articles were retrieved. A 

total of 45 articles were ultimately included in this review. 
5 

Key Question 1 

What is the evidence for the risks and benefits of oral diabetes agents (e.g., second-generation 

sulfonylureas and metformin), as compared to all types of insulin, for both the mother and 

neonate in the treatment of women with gestational diabetes? 

a. How does maternal outcome vary based on the level of glucose at the initiation of a 

medication? 

b. How does neonatal outcome vary based on the level of glucose at the initiation of a 

medication? 

• We identified eight randomized controlled trials (RCTs) with a total of 845 participants 

that met our inclusion criteria for review: Three trials compared insulin to glyburide; two 

trials compared insulin to insulin lispro; one trial compared long-acting to short-acting 

insulin; one trial compared four-times-daily insulin to two-times daily insulin; and one 

trial compared diet to insulin. 

• Two small trials and one large trial (404 women) reported no significant difference in 

maternal glucose control or rates of cesarean delivery between the insulin and glyburide 

groups. 

• A meta-analysis of the three RCTs comparing insulin and glyburide showed that 

treatment with insulin was associated with a lower mean infant birth weight when 

compared to glyburide (weighted mean difference: -93 grams [gm]) (95 percent 

confidence interval [CI]: -191 to 5 gm), but the difference was small and not statistically 

significant. 

• The largest trial reported no difference in the proportion of infants with hypoglycemia (9 

percent with glyburide as compared to 6 percent with insulin therapy [p = 0.25]). A 

smaller trial reported a significantly higher percentage of infants with hypoglycemia in 

the glyburide group than in the insulin or acarbose groups (33 percent compared to 4 

percent and 5 percent, respectively; p = 0.006). 

• Four observational studies (N = 911 women) compared the effects of insulin and 

glyburide on maternal and neonatal outcomes. 

• Due to potential selection bias, loss to followup, and the lack of any power analysis to 

estimate detectable effect sizes, none of the observational studies was deemed strong 

enough to justify a modification of the conclusions drawn from the RCTs. 

• We graded the overall evidence comparing insulin and glyburide as very low. 

• We identified two RCTs that compared insulin lispro to insulin. It appeared that insulin 

lispro might be associated with tighter maternal glucose control than regular insulin, but 

there were only limited data to support this conclusion. 

• Both RCTs reported similar rates of cesarean delivery among women in the insulin lispro 

group, as compared to the insulin group. 

• No evidence existed to suggest that neonatal outcomes differ between women treated 

with insulin lispro and those treated with regular insulin. 

• We graded the strength of the evidence comparing insulin to insulin lispro as very low.

• One RCT (N = 23 women) reported that long-acting insulin was associated with a higher 

proportion of infants with macrosomia when compared to short-acting insulin. No 
6 

difference in birth trauma or metabolic abnormalities was found, but this study was not 

adequately powered to detect differences in these outcomes. 

• There was insufficient evidence to allow us to draw any conclusions regarding maternal 

outcomes. 

• One RCT (N = 274 women) reported that twice-daily insulin was associated with a higher 

proportion of hypoglycemia (6 percent versus 1 percent; p = 0.002) and 

hyperbilirubinemia (21 percent versus 11 percent; p = 0.002) when compared to fourtimes-daily insulin. No evidence existed to suggest a difference in maternal glucose 

levels or cesarean delivery between twice-daily and four-times-daily use of insulin. 

• We identified only one RCT (N = 95 women) that reported lower rates of macrosomia 

(5.9 percent versus 26.5 percent, respectively; p = 0.005) and lower infant birth weights 

(p = 0.002) for those using insulin plus dietary management versus those treated with diet 

alone.

• We graded the overall evidence regarding comparisons of diet plus insulin to diet alone 

as very low, given that only one small RCT met our inclusion criteria.

• We found no evidence to indicate whether the relative effect of different treatment 

approaches on maternal and infant outcomes varied with the level of glucose at the 

initiation of medical therapy. 

• We expect that the ongoing Hyperglycemia and Adverse Pregnancy Outcomes (HAPO) 

Study, an observational study of 23,325 pregnant women, should provide data on 

maternal and neonatal outcomes at various maternal glucose levels and potentially 

indicate thresholds at which medical therapy should be initiated. 

• We found no RCTs or observational studies comparing metformin to insulin in 

gestational diabetics that met our criteria for review. The Metformin in Gestational 

Diabetes (MiG) Trial is an ongoing randomized trial of over 500 women that should 

provide future insight into the benefits and risks of metformin use throughout pregnancy. 

• There were insufficient data regarding the teratogenic effects of intrauterine exposure to 

metformin or its potential effect on infant growth and motor development. 

Key Question 2 

What is the evidence that elective cesarean delivery or the choice of timing of induction in 

women with gestational diabetes results in beneficial or harmful maternal and neonatal 

outcomes? 

• One RCT and seven observational studies evaluated two of our five maternal outcomes of 

interest and 11 of the 12 neonatal outcomes of interest. 

• One RCT of 200 women reported that elective induction at 38 weeks of gestation, as 

compared to expectant management (induction at 42 weeks’ gestation or if the EFW was 

4,200 gm or greater), reduced infant birth weight and the rate of macrosomia but did not 

alter other maternal or neonatal outcomes, including the rate of cesarean delivery. 

• Two observational studies of low quality also reported a reduction in infant birth weight 

or rates of macrosomia in women induced at 38 weeks of gestation, as compared to 

historical controls. 
7 

• Five additional observational studies examined the effects of various delivery 

management protocols, but each had serious limitations, including reliance on historical 

controls, no adjustment for potential confounders, or no adjustment or stratified analysis 

based on severity of gestational diabetes (class A1 [diet-controlled] versus class A2 

[insulin-controlled]). In addition, the studies covered a wide time period (4-19 years), 

with no adjustment for changes in clinical practice. 

• We were unable to draw firm conclusions from the limited data available. 

• We graded the overall strength of the evidence as very low, given the limited number of 

RCTs and the serious design limitations in the conduct of the observational studies. 

Key Question 3 

What risk factors, including but not limited to family history, physical activity, pre-pregnancy 

weight, and gestational weight gain, are associated with short-term and long-term development 

of type 2 diabetes following a pregnancy with gestational diabetes? 

• We developed an a priori list of risk factors for type 2 diabetes, based on guidance from 

the AHRQ, the ACOG, and members of our technical panel, and then grouped these risk 

factors into nine categories: 

1. Family history of type 2 diabetes 

2. Sociodemographics 

3. Lifestyle factors 

4. Parity 

5. Pregnancy-related factors 

6. Postpartum factors 

7. Measures of anthropometry 

8. Oral contraceptives 

9. Physiological measures 

• Sixteen studies evaluated at least one risk factor and reported adjusted measures of 

association. 

• We identified 11 cohort studies that evaluated the relationship between 11 different 

anthropometric measures and the development of type 2 diabetes; 8 studies reported 

adjusted measures of association from multivariate models. 

• Seven of the eight studies that evaluated anthropometric measures (pre-pregnancy body 

mass index [BMI], pregnancy BMI, weight, waist-to-hip ratio) using multivariate 

analysis reported that these measures were positively associated with the risk of 

developing type 2 diabetes. 

• We graded the evidence on anthropometric measures and the risk of developing type 2 

diabetes as moderate because of the inconsistency in the anthropometric measures used 

across the studies. 

• We identified five studies that included family history of type 2 diabetes in the 

multivariate analysis, but only one study reported the actual magnitude of the association 

of family history with the risk of type 2 diabetes, and this association was not statistically 

significant (relative risk [RR] = 1.7; 95 percent CI: 0.6 to 4.6). 
8 

• We graded the evidence on family history as very low because only one study reported 

the actual measure of association. 

• Five studies assessed age as a risk factor for developing type 2 diabetes among 

gestational diabetics, but only one study reported the actual measure of association; 

women who were 30 years of age and older at diagnosis of gestational diabetes had a 

higher likelihood of developing type 2 diabetes, but the relative risk was not statistically 

significant. 

• We did not identify any studies of lifestyle behaviors that met our criteria for inclusion in 

this review. 

• Gestational age at diagnosis of gestational diabetes was inversely associated with a higher 

likelihood of the development of type 2 diabetes, but the modeling of gestational age 

varied across studies and therefore limited our ability to synthesize the data. 

• Two studies evaluated the association between the use of progesterone-only 

contraception or combination oral contraception (estrogen and progesterone) and the risk 

of developing type 2 diabetes in women with gestational diabetes. One study reported a 

two-fold increase in the risk of developing diabetes with the use of progestin-only oral 

contraceptives as compared to combination oral contraception; one study reported no 

increased risk in women using depo-medroxyprogesterone acetate as compared to 

combined oral contraceptives. 

• FBG, 2-hour glucose value, and the area under the curve from the diagnostic antepartum 

oral glucose tolerance test (OGTT) were associated with a significantly higher risk of 

developing type 2 diabetes in women with gestational diabetes. 

Key Question 4 

What are the performance characteristics (sensitivity, specificity, and reproducibility) of tests for 

diagnosing type 2 diabetes after pregnancy in patients with a history of gestational diabetes? Are 

there differences in the performance characteristics of the test results based on subgroup 

analysis?

• We identified eight studies that reported 10 evaluations of the performance of a reference 

test versus a comparison (screening) test for the diagnosis of type 2 diabetes in the 

postpartum period. 

• Our review yielded three general comparisons: (1) two different diagnostic threshold 

values applied to the 75-gm OGTT (the World Health Organization [WHO] 1985 

criterion compared with the WHO 1999 criterion), (2) FBG level greater than 7.0 mmol/L 

(126 mg/dL) (the American Diabetes Association [ADA] 1997) compared to the 75-gm 

OGTT (WHO 1999), and (3) FBG greater than 7.0 mmol/L (126 mg/dL) (ADA 1997) 

compared to the 75-gm OGTT (WHO 1985). 

• The sensitivity for the FBG greater than 7.0 mmol/L (126 mg/dL) alone as compared 

with a complete OGTT using the same FBG threshold (FBG greater than 7.0 mmol/L 

(126 mg/dL) or a 2-hr plasma glucose level after 75-g OGTT greater than 11.1 mmol/L 

(200 mg/dL) varied across the three studies, ranging from 46 to 89 percent. 

• With a threshold greater than 7.0 mmol/L, the FBG had high specificity when compared 

to the 75-gm OGTT but had highly variable sensitivity. 
9 

• No studies included in this review reported measures of reproducibility. 

• We graded the strength of the evidence regarding postpartum screening for type 2 

diabetes as very low because of the limited number of studies within each category of 

comparisons and the heterogeneity in the study populations. 

Discussion 

Conclusions 

Although the overall quality of the evidence was very low, we were able to draw some 

conclusions regarding treatment options for maternal glucose control, the timing and method of 

delivery, the risk factors for the development of type 2 diabetes, and the performance 

characteristics of screening tests conducted in the postpartum period to identify those who have 

developed type 2 diabetes. 

When patients ask about the effect of the use of insulin analogues or glyburide as compared 

to insulin, clinicians should be aware that little clinical difference has been demonstrated in the 

infant birth weights associated with the use of these three regimens. Clinicians should also be 

aware that while the use of an alternative to regular insulin is unlikely to result in any adverse 

maternal or infant outcomes, there were insufficient data to allow us to determine whether 

insulin analogues or glyburide are more efficacious than regular insulin in achieving maternal 

glucose targets. Also, there was no evidence supporting a difference in terms of the prevention of 

episodes of maternal or neonatal hypoglycemia. To date, only insulin has been approved by the 

Food and Drug Administration for use in gestational diabetes. Because of the limited data 

available, it was unclear what glucose thresholds should be used to initiate treatment with 

insulin, insulin analogues, or glyburide in patients who are being treated with diet alone. 

Furthermore, there were insufficient data regarding the potential benefits or risk of metformin 

use. 

There was also insufficient evidence to permit us to develop guidelines for elective labor 

induction or cesarean delivery in women with gestational diabetes. Well-designed clinical trials 

are needed to provide a stronger base of evidence for the management of gestational diabetes. 

Based on multivariate models, measures of obesity appeared to be the strongest risk factor 

for type 2 diabetes in women with gestational diabetes. We have concluded that there are 

insufficient data to justify recommending alternative tests to the 75-gm OGTT for the detection 

of type 2 diabetes in women with gestational diabetes. Further studies conducted in diverse 

populations and high-risk subgroups and incorporating measures of reproducibility will help to 

move this area of investigation toward the development of clinically acceptable testing 

guidelines. 

Limitations 

This review has several important limitations. First, the heterogeneous nature of the studies 

prevented a quantitative summary of much of the data. For Key Question 1, we were able to 

provide a summary measure of the weighted mean difference in infant birth weight in the three 

RCTs comparing insulin and glyburide. However, the pooled estimate provided data on only one 

of several important maternal and neonatal outcomes related to medical treatment in gestational 
10 

diabetics. We were unable to conduct additional analysis because the number of trials comparing 

similar treatments was very limited. Also, maternal and neonatal outcomes were not consistent 

across studies. Few of the same outcome measures were included in two or more studies, and the 

definitions of outcomes varied across studies. Our review of five observational studies 

comparing of glyburide and insulin did not alter our limited conclusions from the RCTs. We 

were further limited by a lack of data on the potential risk of glyburide use. We were unable to 

provide evidence on the potential risks and benefits of metformin because of a lack of published 

studies that met our inclusion criteria. 

We were also unable to draw substantial conclusions from our review of seven observational 

studies and a single RCT on elective induction and cesarean delivery. The observational studies 

had serious limitations, with no adjustment for potential confounders, severity of gestational 

diabetes, or variation in the definitions of major outcomes. There was substantial heterogeneity 

in the study populations and the time periods of these observational studies. 

The lack of multivariate analysis in some studies, as well as inconsistencies in the covariates 

included in the multivariate models of other studies, made it difficult to compare results across 

the 16 studies on risk factors for type 2 diabetes. We found limited evidence for the magnitude of 

association of traditional risk factors (sociodemographics, parity, family history) with the 

development of type 2 diabetes in women with gestational diabetes. We were also limited by the 

lack of availability of any studies on the possible relationship of lifestyle behaviors to the risk of 

type 2 diabetes. 

Finally, heterogeneity in the study populations and the time intervals of postpartum testing 

made it difficult to draw firm conclusions regarding the effectiveness of postpartum glucose 

screening in women with a history of gestational diabetes. 

Future Research Implications 

• Researchers should focus on conducting studies that will lead to the development of 

evidenced-based guidelines for maternal glucose control in gestational diabetes and 

physician recommendations for labor induction, elective cesarean, or expectant 

management. 

• Well-designed RCTs with a priori hypotheses, power analysis, appropriate effect sizes, 

and intention-to-treat analysis can provide better data on treatment efficacy. 

• Consistency in the definition and collection of maternal and infant outcome measures is 

essential to our ability to draw confident conclusions about potential benefits and harms 

of treatment options among women with gestational diabetes. 

• The best evidence for delivery management in women with gestational diabetes will be 

garnered from the conduct of well-designed RCTs comparing elective induction and 

cesarean delivery to expectant management. Alternatively, observational studies with 

consistency in outcomes measures and multivariate adjustment for potential confounders 

can provide important, relevant information. 

• Those conducting longitudinal studies of women with a history of gestational diabetes 

should develop and follow standard protocols for retention in an effort to improve 

followup rates. Future studies should collect data on pertinent covariates and adjust for 

relevant confounders in multivariate analysis. 

• Studies measuring the sensitivity, specificity, and reproducibility of screening tests for 

type 2 diabetes in women with a history of gestational diabetes can help physicians in the 
11 

early identification of women with type 2 diabetes and avoid potential medical 

complications of diabetes. 

• A comparison of screening and reference tests in certain subgroups (i.e., those with a 

family history type 2 diabetes or prior gestational diabetes) is also warranted. 

• In order to develop broadly acceptable guidelines for postpartum screening for type 2 

diabetes in women with prior gestational diabetes, additional research should be 

conducted to assess test reproducibility as well as test performance based on varying 

intervals of postpartum screening.
Evidence Report 
15 

Chapter 1. Introduction 

The American College of Obstetricians and Gynecologists (ACOG) has requested an 

evidence report from the Agency for Healthcare Research and Quality (AHRQ) through the 

Evidence-based Practice Center program (EPC) to systematically and critically examine the 

literature on specific aspects of the management of gestational diabetes mellitus (gestational 

diabetes). With the ongoing increase in obesity and sedentary lifestyles, the prevalence of 

diabetes mellitus among reproductive-aged women is rising, both globally and in the United 

States.1

 There are currently 1.85 million reproductive-aged women in the United States with 

gestational diabetes, type 1 or type 2 diabetes mellitus (type 2 diabetes), or glucose intolerance.2

Gestational diabetes, the most common medical complication of pregnancy, is defined as 

carbohydrate intolerance of variable degree, with an onset or first recognition occurring during 

pregnancy. Population-based studies estimate that gestational diabetes affects about 200,000 (7 

percent) of the over 4 million births occurring annually in the United States and is associated 

with both maternal and neonatal complications.3-5 Furthermore, women with gestational diabetes 

are at high risk for future diabetes; 15 to 60 percent will develop type 2 diabetes mellitus within 

5 to 15 years of delivery.6

 Therefore, the diagnosis and subsequent management of gestational 

diabetes after delivery has important implications for the prevention of type 2 diabetes. A 

systematic review of evidence to guide decisions about glucose management, labor management, 

postpartum risk assessment, and screening of women with gestational diabetes would be useful 

for clinicians and public health officials. 

In an effort to promote maternal wellbeing and avoid adverse neonatal outcomes, such as 

macrosomia, birth trauma, and neonatal hypoglycemia, clinical recommendations have been 

developed by the ACOG7 and the American Diabetes Association (ADA) for the obstetrical 

management of gestational diabetes. The guidelines emphasize the importance of glucose control 

to minimize the risk of macrosomia and its associated complications. When dietary management 

fails to achieve adequate glucose control, an anti-hyperglycemic medication should be used. 

Traditionally, insulin has been considered the gold standard for management because of the 

ability to achieve tight maternal glucose control without the risk of transfer of insulin across the 

placenta.8

 However, an oral diabetes medication (i.e., glyburide) is being used increasingly in 

women with gestational diabetes despite the lack of approval by the Food and Drug 

Administration for this indication.8-10 Metformin is currently used in the non-pregnant woman 

with polycystic ovarian syndrome (PCOS) to treat insulin resistance and normalize ovulation.11

Metformin use in women with gestational diabetes is still in the experimental stages. Given the 

increasing use of different medications for gestational diabetes, it is time for a critical appraisal 

of the literature regarding the potential benefits and harms associated with the medications that 

can be used for the treatment of gestational diabetes. 

To date, the evidence has been somewhat limited regarding the comparative effectiveness 

and safety of oral diabetes agents and insulin preparations for women with gestational diabetes. 

The Cochrane Collaboration has conducted a review of randomized clinical trials comparing the 

effects of alternative management strategies (e.g., dietary management, insulin, or an oral 

diabetes agent) in women with impaired glucose tolerance or gestational diabetes.12 The final 

analysis included three trials involving women with impaired glucose tolerance, but no trials 

involving women with gestational diabetes. No statistically significant differences were found in 

terms of cesarean delivery rates, neonatal intensive care unit admissions, or large-for-gestational 

age (LGA; weight greater than 90th percentile) infants among women with impaired glucose 
16 

tolerance undergoing intensive treatment with insulin, as compared to those receiving dietary 

advice alone. Further review is needed to assess the evidence now available on the value of 

medical therapies for glucose control in gestational diabetes. In the current report, one of our 

goals was to synthesize current knowledge regarding the medical treatment benefits and harms 

associated with the metabolic management of gestational diabetes, by comparing insulin therapy 

to oral diabetes medications, including the sulfonylureas and metformin. Our maternal and 

neonatal outcomes of interest were chosen on the basis of established measures of maternal and 

infant morbidity and guidance by our team of technical experts, as described in the Methods 

chapter. 

Both the ACOG and the ADA have provided guidelines for labor management of 

pregnancies complicated by gestational diabetes. The ACOG states that primary cesarean 

delivery may be indicated in women with gestational diabetes whose estimated fetal weight 

(EFW) is 4,500 grams (gm) or greater.7

 The ADA recommends delivery during the 38th week, 

unless obstetric considerations dictate alternative management.13 Many institutions have 

implemented protocols for labor management of women with gestational diabetes, based largely 

on anecdotal or individual institutional experience. Variations in clinical management continue 

because patients and health care providers have differing perceptions of the potential benefits 

and risks of different management strategies. Neither health care providers nor patients are 

armed with the knowledge necessary to adequately weigh the potential benefits and harms 

associated with these strategies. The lack of consensus has led to controversy regarding best 

practices for labor management. Evidence relating to labor management can provide valuable 

epidemiological evidence to clinicians in daily practice as well as to professional organizations 

that seek to make clinical policy recommendations about the optimal delivery of obstetrical care 

to women with gestational diabetes. 

In this report, we have systematically reviewed and summarized the available literature on 

outcomes associated with a range of labor management strategies, including elective induction of 

labor, elective cesarean delivery, and expectant management of labor. For the purposes of this 

report, we refer to “elective” cesarean delivery as a procedure performed after discussion 

between the provider and patient with the goal of avoiding adverse neonatal outcomes that occur 

more often in diabetic pregnancy, such as shoulder dystocia, nerve palsy, or fracture. We have 

also reviewed the evidence regarding the effect of gestational age and EFW on maternal and 

neonatal outcomes in pregnancies complicated by gestational diabetes. 

There is growing interest in the effect of childbearing on the development of chronic medical 

conditions, including type 2 diabetes. Many studies have examined traditional risk factors for 

type 2 diabetes, including age, race/ethnicity, and a family history of type 2 diabetes. However, 

no review to date has systematically examined risk factors for type 2 diabetes in women with a 

history of gestational diabetes. Such a review is needed and should cover the available data on 

metabolic or hormonal risk factors in this population as well as emerging data on other risk 

factors such as homocysteine levels14 15 and glutamic acid decarboxylase (GAD) antibodies.16 A 

review of this body of evidence could assist policymakers in the development of guidelines 

targeted at primary prevention of type 2 diabetes. We have therefore systematically reviewed the 

evidence on risk factors for type 2 diabetes in women with gestational diabetes, assessing the 

magnitude of individual risk factors and study quality. 

Because women with gestational diabetes are at high risk for future diabetes, postpartum 

testing is crucial for early diagnosis of type 2 diabetes and the prevention or delay of onset of 

diabetic complications. The ACOG recognizes the increased risk of diabetes in women with 
17 

gestational diabetes but offers no standard recommendation for postpartum testing.7

 The ADA 

recommends postpartum screening at 6 weeks postpartum using either a fasting blood glucose 

(FBG) or an oral glucose tolerance test (OGTT).13 17 Women with a normal result should be 

reassessed every 3 years. Women with impaired fasting glucose or impaired glucose tolerance 

should receive annual testing. The 4th International Workshop on Gestational Diabetes has 

recommended that postpartum glucose testing be performed at 6 to 12 weeks postpartum.18 

Despite the general recommendation for postpartum screening, no consensus exists regarding 

the overall performance characteristics of the OGTT or FBG in the postpartum period or in 

women with a history of gestational diabetes. Emerging data suggest that many women with 

gestational diabetes do not receive appropriate postpartum testing,19 20 perhaps because of limited 

knowledge regarding the performance of the screening tests in postpartum women, differences in 

the recommendations by professional organizations, and the challenges posed by the 2- to 3-hour 

(hr) timeframe required for an OGTT for a busy new mother. Knowledge of the performance of 

the FBG in comparison to the standard OGTT could help to improve patient adherence to 

postpartum testing. In addition, evidence related to the sensitivity and specificity of screening 

tests for type 2 diabetes may inform the development of evidence-based guidelines by 

professional organizations, prevent provider confusion about the timing of testing, and facilitate 

provider adherence to recommendations for testing. We have therefore investigated the 

performance of currently used screening tests for type 2 diabetes of pregnancies for women with 

a history of gestational diabetes, assessing their sensitivity and specificity and summarizing the 

evidence with regard to reproducibility. 

To improve the outcomes of pregnancies in women with gestational diabetes, several 

approaches should be considered, including: (1) novel approaches to maternal glycemic control; 

(2) modifications of the clinical assessment for timing and method of delivery; (3) identification 

of risk factors for subsequent development of type 2 diabetes; and (4) clarification of the 

performance characteristics of postpartum glucose screening tests. The use of oral diabetes 

agents and/or new insulin preparations, for example, might promote better glucose control, 

decrease maternal hypoglycemia, and reduce abnormal fetal growth. The adaptation of new 

guidelines for cesarean delivery and labor induction in women with diabetes might reduce the 

incidence of birth trauma or nerve damage (e.g., brachial plexus palsy). A better understanding 

of the efficiency of postpartum glucose screening tests and screening intervals might help to 

identify a greater number of reproductive-aged women who are at risk of type 2 diabetes and 

who could be targeted for primary prevention. For example, it is possible that screening women 

beyond the currently recommended time interval of 6 weeks after delivery might increase the 

sensitivity of diabetic screening protocols. A greater number of women could then receive 

counseling on lifestyle modifications (i.e., nutrition, exercise). Furthermore, among those women 

who screen negative for glucose intolerance after the index pregnancy, lifestyle modifications 

might reduce the risk of development of gestational diabetes in subsequent pregnancies. 

Conceptual Framework and Key Questions 

As shown in our conceptual framework (see Figure 1), we focused our evidence review on 

four independent, yet interrelated, areas of clinical management. The solid lines summarize the 

four key questions that are the focus of our review. Key Questions 1 and 2 include maternal 

management prior to and at the time of delivery. Also, prior clinical studies have supported a 
* Outcome was evaluated only for Key Question 1. 

† Outcome was evaluated only for Key Question 2. FBG = fasting blood glucose; gm = gram; KQ = key question; LGA = large for gestational age; NICU = neonatal intensive care unit; OGTT = oral glu

respiratory distress syndrome; SGA = small for gestational age; type 2 diabetes = type 2 diabetes mellitus 

Key Question 3

• Demographics • Pregnancy 

characteristics 

• Characteristics of 

delivery 

• Maternal lifestyle • Postpartum factors • Serum markers during 

pregnancy 

• Serum markers post 

pregnancy 

• Physiological factors • Progestins and oral 

contraception 

• Glucose tolerance 

Figure 1. Conceptual framework for labor and postpartum management of women with gestational diabetes mellitus 

Maternal Outcomes 

(KQ 1 and KQ 2)

• Cesarean delivery • Glycemic control* • Hemorrhage • Hypoglycemia* • Infection† • Operative vaginal 

delivery 

• Perineal tears • Pre-eclampsia* • Weight* Neonatal Outcomes 

(KQ 1 and KQ 2)

• Anoxia • Birth trauma • Birth weight • Congenital 

malformation 

• Hyperbilirubinemia • Hypoglycemia • LGA • Macrosomia • Mortality • NICU admission • RDS • Shoulder dystocia • SGA 

Key Question 1

Effectiveness of treatment modalities • Diet versus metformin • Diet versus glyburide • Metformin versus 

insulin 

• Metformin versus 

glyburide 

• Glyburide versus 

insulin 

• Insulin versus insulin 

Key Question 4

Efficiency of glucose tolerance testing after delivery • 75-gm OGTT • FBG 

Developm

interven

Key Question 2

Evidence-based management • Gestational age at 

induction 

• Trial of labor or 

cesarean delivery 

• Intrauterine fetal 

weight 

• Gestational age 

18 
19 

direct association between prenatal maternal glucose management and EFW and the timing of 

delivery, two areas of focus in Key Question 2. The link between Key Questions 1 and 2 is 

reflected in the commonality of several of the maternal and neonatal outcomes. From a 

biological perspective, metabolic control can directly influence the effects of intrauterine weight 

and gestational age on clinical decisionmaking in labor management. 

Maternal outcomes of interest included maternal hypoglycemia, glycemic control, preeclampsia, postpartum hemorrhage, maternal weight, and cesarean delivery, representing 

measures of maternal morbidity and quality of care. Neonatal outcomes of interest included 

macrosomia, neonatal hypoglycemia, birth trauma, birth weight, and respiratory distress 

syndrome, representing measures of neonatal morbidity and subsequent childhood wellbeing. 

In Key Question 3, we examined multiple risk factors for development of type 2 diabetes. 

Assessment of the literature yielded two primary categories of risk factors: traditional 

epidemiological factors and physiological factors. As shown in the conceptual framework, these 

factors may be instrumental in the development of targeted interventions for this particular 

population of women. In Key Question 4, we assessed the performance of screening tests in 

detecting type 2 diabetes in women with gestational diabetes. 

Our key questions were: 

1. What is the evidence for the risks and benefits of oral diabetes agents (e.g., secondgeneration sulfonylureas and metformin), as compared to all types of insulin, for both the 

mother and neonate in the treatment of women with gestational diabetes? 

a. How does maternal outcome vary based on the level of glucose at the initiation of a 

medication? 

b. How does neonatal outcome vary based on the level of glucose at the initiation of a 

medication? 

Maternal outcomes 

• cesarean delivery 

• glycemic control (FBG, 1-hr 

and 2-hr postprandial glucose 

(PPG) 

• hemorrhage 

• hypoglycemia 

• operative vaginal delivery 

• perineal tears 

• pre-eclampsia 

• weight 

Neonatal outcomes 

• anoxia 

• birth trauma 

• birth weight 

• congenital malformations 

• hyperbilirubinemia 

• hypoglycemia 

• LGA 

• macrosomia 

• mortality 

• neonatal intensive care admissions 

• respiratory distress syndrome 

• shoulder dystocia 

• small for gestational age (SGA) 

2. What is the evidence that elective cesarean delivery or the choice of timing of induction 

in women with gestational diabetes results in beneficial or harmful maternal and neonatal 

outcomes? 

a. What is the evidence for elective cesarean delivery at term, as compared to an attempt 

at vaginal delivery (spontaneous or induced) at term, with regard to beneficial or 

harmful maternal and neonatal outcomes in gestational diabetes? 
20 

i. cesarean versus spontaneous labor and vaginal delivery 

ii. cesarean versus induced labor and vaginal delivery 

iii. cesarean versus any attempt at vaginal delivery at term 

b. What is the evidence for labor induction at 40 weeks, as compared to labor induction 

at an earlier gestational age (less than 40 weeks) or spontaneous labor, with regard to 

beneficial or harmful maternal and neonatal outcomes in gestational diabetes? 

i. labor induction at less than 40 weeks versus labor induction at 40 weeks 

ii. labor induction at 40 weeks versus spontaneous labor 

iii. labor induction at less than 40 weeks versus spontaneous labor 

c. How is the EFW related to outcomes of management of gestational diabetes with 

elective cesarean delivery or the timing (i.e., gestational age range) of labor 

induction? 

d. How is gestational age related to outcomes of management of gestational diabetes 

with elective cesarean delivery or the choice of timing (i.e., gestational age range) of 

labor induction? 

Maternal outcomes 

• cesarean delivery 

• hemorrhage 

• infection 

• operative vaginal delivery 

• perineal tears 

Neonatal outcomes 

• anoxia 

• birth trauma 

• birth weight 

• congenital malformations 

• hyperbilirubinemia 

• hypoglycemia 

• LGA 

• macrosomia 

• mortality 

• neonatal intensive care admissions 

• respiratory distress syndrome 

• shoulder dystocia 

• SGA 

3. What risk factors, including but not limited to family history, physical activity, prepregnancy weight, and gestational weight gain, are associated with short-term and longterm development of type 2 diabetes following a pregnancy with gestational diabetes? 

4. What are the performance characteristics (sensitivity, specificity, and reproducibility) of 

tests for diagnosing type 2 diabetes after pregnancy in patients with a history of 

gestational diabetes? Are there differences in the performance characteristics of the test 

results based on subgroup analysis? 

A systematic review of the evidence on labor and postpartum management of gestational 

diabetes can provide support for clinical guidelines, thereby arming clinicians with the 

knowledge necessary to provide evidenced-based, quality care to a growing population of 

women. For the current 200,000 pregnancies that are complicated by gestational diabetes 

annually in the United States, evidence-based clinical practice will be essential in promoting 

treatment effectiveness, evidenced-based labor management, effective assessment of risk factors 
21 

for later development of type 2 diabetes in women with gestational diabetes, and efficient 

postpartum screening for type 2 diabetes. 
23 

Chapter 2. Methods 

 The ACOG has requested an evidence report to review and synthesize published literature 

regarding the intrapartum management and postpartum followup of women with gestational 

diabetes. Our EPC established a team and a work plan to develop the evidence report. The 

project consisted of recruiting technical experts, formulating and refining the specific questions, 

performing a comprehensive literature search, summarizing the state of the literature, 

constructing evidence tables, synthesizing the evidence, grading the strength of the evidence, and 

submitting the report for peer review. 

Topic Development 

 The topic for this report was nominated in a public process. At the beginning of the project, 

we recruited a panel of external technical experts to provide input at key steps, including the 

selection and refinement of the questions to be examined. The panel included external experts 

who have strong expertise in gestational diabetes (see Appendix Aa

). 

 We worked with the technical experts and representatives of the AHRQ and ACOG to 

develop the key questions that are presented in the Conceptual Framework and Key Questions 

section of Chapter 1 (Introduction). The key questions focused on: (1) the risks and benefits of 

using oral diabetes medications and any type of insulin to treat gestational diabetes affecting the 

mother and neonate, (2) the risks and benefits of medically indicated cesarean delivery and the 

choice of timing of induction for the mother and neonate, (3) the risk factors associated with the 

short-term and long-term development of type 2 diabetes following a pregnancy with gestational 

diabetes, and (4) the performance characteristics (i.e., sensitivity, specificity, and reproducibility) 

of tests for diagnosing type 2 diabetes when conducted in postpartum gestational diabetes 

patients. 

Search Strategy 

 Searching the literature involved identifying reference sources, formulating a search strategy 

for each source, and executing and documenting each search. We also searched for medical 

subject heading (MeSH) terms that were relevant to gestational diabetes. We used a systematic 

approach for searching the literature, with specific eligibility criteria, to minimize the risk of bias 

in selecting articles for inclusion in the review. The systematic approach was intended to help 

identify gaps in the published literature. 

Our comprehensive search plan included electronic and hand searching. We ran searches of 

four databases, MEDLINE® (1950 through January 2007), EMBASE® (1974 through January 

2007), The Cochrane Central Register of Controlled Trials (CENTRAL; Issue 1, 2007), and the 

Cumulative Index to Nursing & Allied Health Literature (CINAHL®; 1982 through January 

2007), to identify primary literature on the association of intrapartum management and 

postpartum followup of women with gestational diabetes with various maternal and neonatal 

 

a Appendixes cited in this report are provided electronically at: http://www.ahrq.gov/clinic/tp/gdmparttp.htm
24 

outcomes. Hand searching for possibly relevant citations took two forms. First, from our 

electronic search, we identified the 13 journals (see Appendix Ba) that were most likely to 

publish articles on this topic (i.e., these journals had the highest number of abstracts and articles 

included in the review). We scanned the table of contents of each issue of these journals for 

relevant articles from August 2006 through January 2007. For the second form of hand 

searching, reviewers received eligible articles and flagged references of interest for the team to 

compare to the existing database. 

 Search strategies specific to each database were designed to enable the team to focus the 

available resources on articles that were the most likely to be relevant to the key questions. We 

initially developed a core strategy for MEDLINE®, accessed via PubMed®, based on an analysis 

of the MeSH terms and text words of key articles identified a priori. The PubMed® strategy 

formed the basis for the strategies developed for the other electronic databases (see Appendix 

Ca

). 

 The results of the searches were downloaded and imported into ProCite® version 5 (the 

Thompson Corporation, Stamford, CT). We used the duplication scan feature in ProCite® to 

delete citations already retrieved. From ProCite®, the articles were uploaded to SRS 4.0 

(TrialStat! Corporation, Ottawa, Ontario, Canada), a Web-based software package developed for 

systematic review data management. This database was also used to store citations in portable 

document format (PDF) and to track the search results at the title review, abstract review, article 

inclusion/exclusion, and data abstraction levels. A list of excluded articles is presented in 

Appendix Da. 

Study Selection 

 The study team scanned all titles. Two independent reviewers conducted title scans in a 

parallel fashion. For a title to be eliminated at this level, both reviewers had to indicate that it 

was obviously ineligible. If the two reviewers did not agree on the eligibility of an article, it was 

promoted to the next level (see Appendix Ea, Title Review Form). The title review phase was 

designed to capture as many studies as possible that reported on the association of intrapartum 

management and postpartum followup of women with gestational diabetes with various maternal 

and neonatal outcomes. All titles that were identified as potentially addressing these issues were 

promoted to the abstract review phase. 

 Abstracts were reviewed independently by two investigators. Abstracts were excluded if 

both investigators agreed that the article met one or more of the following exclusion criteria: (1) 

not written in English; (2) did not include any human data; (3) contained no original data that 

was published in a peer-reviewed journal (i.e., was a meeting abstract, editorial, commentary, or 

letter); (4) did not evaluate women with gestational diabetes; (5) was a case report or case series; 

(6) did not base the diagnosis of gestational diabetes on either a 3-hr, 100-gm OGTT or a 2-hr, 

75-gm OGTT; (7) did not evaluate an outcome relevant to the key questions (see Table 1); (8) 

did not include a medication of interest for Key Question 1; (9) did not have an appropriate 

comparison group for Key Questions 1 or 2; or (10) did not apply to a key question. We included 

publications that did not explicitly state the test used to diagnosis gestational diabetes if we were 

able to confirm through referenced publications or through personal communications with the 

author that the study used one of the accepted diagnostic tests. Differences of opinion regarding 

 

a

 Appendixes cited in this report are provided electronically at: http://www.ahrq.gov/clinic/tp/gdmparttp.htm
25 

abstract eligibility were resolved through consensus adjudication. At this level of review, the 

reviewers were also asked to identify to which key question(s) the article might apply if it was 

eligible for review. 

Table 1. List of outcomes reviewed

KQ1 Maternal Outcomes 

• Cesarean delivery 

• Glycemic control 

• Hemorrhage 

• Hypoglycemia 

• Operative vaginal delivery 

• Perineal tears 

• Pre-eclampsia 

• Weight 

Neonatal Outcomes 

• Anoxia 

• Birth trauma 

• Birth weight 

• Congenital malformation 

• Hyperbilirubinemia 

• Hypoglycemia 

• LGA 

• Macrosomia 

• Mortality 

• Neonatal intensive care unit admissions 

• RDS 

• SGA 

• Shoulder dystocia 

KQ2 Maternal Outcomes 

• Cesarean delivery 

• Hemorrhage 

• Infection 

• Operative vaginal delivery 

• Perineal tears 

Neonatal Outcomes 

• Anoxia 

• Birth trauma 

• Birth weight 

• Congenital malformation 

• Hyperbilirubinemia 

• Hypoglycemia 

• LGA 

• Macrosomia 

• Mortality 

• Neonatal intensive care unit admissions 

• RDS 

• SGA 

• Shoulder dystocia 

KQ3 • Type 2 diabetes (diagnosed by FBS > 125 mg/dL, 75-gm OGTT, 2-hr glucose > 200 mg/dL, random 

glucose > 200 mg/dL, self-reported type 2 diabetes, or current use of an antidiabetic medication) 

KQ4 • Sensitivity 

• Specificity 

• Reproducibility 

dL = deciliter; FBS = fasting blood sugar; gm = gram; hr = hour; KQ = key question, LGA = large for gestational age; mg = 

milligrams; OGTT = oral glucose tolerance test; RDS = respiratory distress syndrome; SGA = small for gestational age; type 2 

diabetes = type 2 diabetes mellitus 

 Because of the broad array of potentially eligible articles obtained at the abstract review 

phase, full articles initially selected for review underwent another independent parallel review by 

the investigators to determine whether the articles should be included in the full data abstraction. 

In addition to the exclusion criteria used for the abstract review, studies were excluded if less 

than 90 percent of the sample was diagnosed with gestational diabetes and there was no separate 

analysis for gestational diabetes patients. We limited the studies for Key Question 1 to all 

randomized controlled trials (RCTs) and observational studies that compared two types of 

treatment. For Key Question 1, we decided not to include observational studies that compared 

either an oral diabetes medication or insulin to diet, because most of these studies had a 

selection-by-indication bias (i.e., treatment was determined by the severity of the diabetes). 

 At this phase of the review, the investigators determined which of the key questions each 

article addressed (see Appendix E, Article Inclusion/Exclusion Form). If the articles were still 
26 

deemed to have applicable information, they were included in the full data abstraction. 

Differences of opinion regarding article eligibility were resolved through consensus adjudication. 

Data Abstraction 

 We used a systematic approach for extracting data to minimize the risk of bias in this 

process. By creating standardized forms for data extraction, we sought to maximize consistency 

in identifying all pertinent data available for synthesis. 

 Each article underwent double review by study investigators for full data abstraction and 

assessment of study quality. For all data abstracted from studies, we used a sequential review 

process. In this process, the primary reviewer completed all data abstraction forms. The second 

reviewer checked the first reviewer’s data abstraction forms for completeness and accuracy. 

Reviewer pairs were formed to include personnel with both clinical and methodological 

expertise. A third reviewer re-reviewed a random sample of articles by the first two reviewers to 

ensure consistency in the classification of the articles. Reviewers were not masked to the articles’ 

authors, institutions, or journal.21 In most instances, data were directly abstracted from the 

article. If possible, relevant data were also abstracted from figures. Differences of opinion were 

resolved through consensus adjudication. For assessments of study quality, each reviewer 

independently judged study quality and rated items on quality assessment forms (see Appendix 

E, Data Abstraction Review Forms). 

 For all included articles, reviewers abstracted information regarding the general study 

characteristics (e.g., exclusion criteria, study design, study period and followup, and country) and 

study participants (e.g., maternal age, race, weight/body mass index [BMI], parity/gravida, 

gestational age, method of gestational diabetes management, and the type, timing, and results of 

the OGTT). For articles that applied to Key Questions 1 and 2, we abstracted information on the 

type of intervention, the outcomes measures and the method of ascertainment, and the results of 

each outcome, including the measures of variability. For articles that applied to Key Question 3, 

we abstracted information on the diagnosis of type 2 diabetes, the length of followup, the 

covariates considered and included in the models, and the measure of association and variability. 

For articles that applied to Key Question 4, we abstracted information on the reference test, the 

comparison test, the length of followup, and the results of the tests. 

 All information from the article review process was entered into the SRS 4.0 database by the 

individual completing the review. Reviewers entered comments into the system whenever 

applicable. The SRS 4.0 database was used to maintain and clean the data, as well as to create 

detailed evidence tables and summary tables (see Appendix F and Summary Tables). 

Study Quality Assessment 

The study aspects considered in our quality assessment varied according to the question 

being addressed and the type of study design. As part of our dual, independent review of study 

quality, we judged articles on several aspects of each study type’s internal validity. Quality 

assessment of trials for Key Questions 1 and 2 was based on the Jadad criteria22 and included: (1) 

appropriateness of the randomization scheme, (2) appropriateness of the blinding, and (3) 

description of withdrawals and drop-outs. For each trial, we awarded a score from 5 (high 

quality) to 0 (low quality). Quality assessment of observational studies for Key Questions 1, 2, 
27 

and 3 involved selecting elements from the Standards for Reporting of Observational Studies 

(STROBE) checklist of the reporting of observational studies;23 it included items about reporting 

on the hypotheses, inclusion/exclusion criteria, study population, power and sample size 

calculations, definition of outcomes, loss to followup, and missing data. Quality assessment of 

the diagnostic test studies for Key Question 4 was designed by selecting elements from the 

Standards for Reporting of Diagnostic Accuracy (STARD) Initiative24 and included items about 

reporting of the sampling design, loss to followup, information about diagnostic accuracy, 

verification of positive and negative tests, independent interpretation of tests, reproducibility, and 

subgroup analyses. 

Data Synthesis 

 For each key question, we created a set of detailed evidence tables containing all the 

information extracted from the eligible studies. The investigators reviewed the tables and 

eliminated items that were rarely reported. 

 We conducted meta-analyses when there were sufficient data (three or more studies) and the 

studies were homogeneous with respect to key variables (population characteristics, study 

duration, intervention/exposure/comparison tests, and length of followup). When the data were 

not sufficient to combine the studies in a meta-analysis, we prepared a qualitative summary of 

the results. 

 In the meta-analysis, we recorded the mean difference in infant birth weight between groups, 

along with its measure of dispersion. We calculated a pooled estimate (weighted mean 

difference) of infant birth weight from the eligible RCTs using a random effects model with the 

DerSimonian and Laird formula for calculating between-study variance.25 The random effects 

model was used because unmeasured heterogeneity was likely to exist among the trials. 

 We assessed heterogeneity among the trials considered for meta-analysis using a standard 

chi-squared test and a significance level of alpha ≤ 0.10. We also examined heterogeneity among 

studies with an I2 statistic, which describes the variability in effect estimates that is due to 

heterogeneity rather than random chance.26 A value greater than 50 percent may be considered to 

have substantial variability. 

 All statistical analyses were conducted using STATA (Intercooled, version 8.2, StataCorp, 

College Station, TX). 

Data Entry and Quality Control 

 Initial data were abstracted by the investigators and entered directly into Web-based data 

collection forms using SRS® 4.0 (TrialStat! Corporation, Ottawa, Ontario, Canada). After a 

second reviewer reviewed the data, the adjudicated data were re-entered into the Web-based data 

collection forms by the second reviewer. Second reviewers were generally more experienced 

members of the research team, and one of their main priorities was to check the quality and 

consistency of the first reviewers’ answers. In addition to the second reviewers checking the 

consistency and accuracy of the first reviewers, a lead investigator examined a random sample of 

the reviews to identify problems with the data abstraction. If problems were recognized in a 

reviewer’s data abstraction, the problems were discussed at a meeting with the reviewers. In 
28 

addition, research assistants used a system of random data checks to assure data abstraction 

accuracy. 

Rating the Body of Evidence 

 At the completion of our review, we graded the quantity, quality, and consistency of the best 

available evidence addressing the key questions by adapting an evidence-grading scheme 

recommended by the GRADE Working Group.27 We assessed the strength of the study designs, 

with RCTs considered to be best, followed by non-randomized controlled trials and 

observational studies. To assess the quantity of evidence, we focused on the number of studies 

with the strongest design. We also assessed the quality and consistency of the best available 

evidence, including assessment of the limitations affecting individual study quality (using the 

individual study quality assessments), certainty regarding the directness of the observed effects 

in the studies, the precision and strength of the findings, and the availability (or lack) of data to 

answer the key question. We classified evidence bodies pertaining to the key questions into the 

following categories: (1) “high” grade, indicating confidence that further research is very 

unlikely to change our confidence in the estimated effect in the abstracted literature; (2) 

“moderate” grade, indicating that further research is likely to have an important impact on our 

confidence in the estimates of effects and may change the estimates in the abstracted literature; 

(3) “low” grade, indicating the further research is very likely to have an important impact on 

confidence in the estimates of effects and is likely to change the estimates in the abstracted 

literature; (4) “very low” grade, indicating any estimate of effect is very uncertain; and (5) 

“insufficient” grade, indicating the lack of enough evidence to make any estimate of effect. 

Peer Review 

A draft of the completed report was sent to the technical experts and peer reviewers, as well 

as to the representatives of AHRQ. In response to the comments of the technical experts, peer 

reviewers, and AHRQ, revisions were made to the evidence report, and a summary of the 

comments and their disposition was submitted to AHRQ. 
29 

Chapter 3. Results 

We present the findings of our review using a standard format for each of the four key 

questions. First, we present the conceptual framework for each question, incorporating relevant 

background information and potential implications for clinical practice. Next, we summarize the 

population characteristics of each study. We then summarize the findings, emphasizing those 

results that are most relevant to our conceptual framework. We outline the methodological issues 

related to the heterogeneity of study design and outcome analyses and then summarize our 

assessment of the quality of each study using established quality criteria published in the 

literature. Finally, we assign a grade to the overall body of evidence on each question or subquestion. 

Search Results 

A summary of the search results for the primary literature review is presented in Figure 2. 

From the search, we retrieved 11,400 unique citations. After a review of the titles and abstracts, 

552 were deemed eligible for further review, and the full articles were retrieved. A total of 45 

articles were included in this review. 

Key Question 1 

What is the evidence for the risks and benefits of oral diabetes agents (e.g., second-generation 

sulfonylureas and metformin), as compared to all types of insulin, for both the mother and 

neonate in the treatment of women with gestational diabetes? 

a. How does maternal outcome vary based on the level of glucose at the initiation of a 

medication? 

b. How does neonatal outcome vary based on the level of glucose at the initiation of a 

medication? 

Background and Conceptual Framework 

Understanding the risks and benefits of the use of insulins or oral diabetes agents during 

pregnancy for both maternal and neonatal outcomes is essential to the care of women with 

gestational diabetes and their offspring.28 29 As shown in the conceptual framework (see Figure 

3), our objective for Key Question 1 was to review RCTs and observational studies to compare 

the risks and benefits of medical treatment for the management of glucose levels in women with 

gestational diabetes. As previously highlighted, pregnancies with gestational diabetes are often 

characterized by many maternal and neonatal complications, including poor maternal glucose 

control, cesarean delivery, and neonatal hypoglycemia. Our primary goal was to summarize the 

maternal and neonatal outcomes across treatment modalities, to derive pooled estimates where 

possible, and to summarize the relevant conclusions based on the available literature. 
30 

Figure 2. Summary of the literature search and review process (number of articles) 

Electronic databases 

MEDLINE® (5628) 

EMBASE® (5306) 

Cochrane CENTRAL 

(225) 

CINAHL® (2905) 

Retrieved 

14092 

Title review 

11400 

Abstract review 

2547 

Article review 

552 

Hand searching 

28 

Duplicates 

2692 

Excluded 

8853 

Excluded 

1995 

Included studies 

45 

Excluded 

507 

Reasons for exclusion at the abstract review level* 

Not in English: 0 

Did not include human data: 2 

Contained no original data: 480 

Did not include women with gestational diabetes: 

318 

Case report or case series with fewer than 50 

cases: 64 

Did not base diagnosis of gestational diabetes on a 

3-hr, 100-gm OGTT or a 2-hr, 75-gm OGTT: 7 

Did not evaluate a maternal or fetal outcome of 

interest: 97 

Did not include a medication of interest for KQ1: 61 

Had no appropriate comparison group for KQ1, 2: 

91 

Did not apply to a key question: 1592 

Other reason: 60 

* Total may exceed number in corresponding box, as articles could be excluded for more than one reason at this level. 

CENTRAL = Central Register of Controlled Trials; CINAHL = Cumulative Index to Allied Health and Nursing Literature; 

gm = gram; hr = hour; KQ = key question; OGTT = oral glucose tolerance test; RCT = randomized controlled trial 

Reasons for exclusion at the article review level* 

Not in English: 1 

Did not include human data: 0 

Contained no original data: 128 

Did not include women with gestational diabetes: 

74 

Case report or case series with fewer than 50 

cases: 11 

Did not base diagnosis of gestational diabetes on a 

3-hr, 100-gm OGTT or a 2-hr, 75-gm OGTT: 42 

Did not evaluate a maternal or fetal outcome of 

interest: 20 

Did not include a medication of interest for KQ1: 10 

Had no appropriate comparison group for KQ1, 2: 

49 

Did not apply to a key question: 178 

Observational study that did not have an 

appropriate comparison group for KQ1: 57 

Study that would apply to KQ3 but did not have a 

relative measure: 13 

Other reason: 42 

KQ1: 8 RCTs 

and 5 cohorts 

KQ3: 16 cohorts KQ4: 8 cohorts

KQ2: 1 RCT and 

7 cohorts 
Figure 3. Conceptual framework of treatment effects on maternal and neonatal outcomes 

Treatment: Physiologic; Site of action Antepartum maternal effects Intra/postpartum maternal outcomes 

Diet: Decreases glucose 

intake; intestinal absorption 

Insulin: Increases glucose 

uptake by cells; muscle and organs 

Oral agents of interest: 1. Sulfonylureas - 

Increases insulin secretion by pancreatic beta cells 2. Metformin - Inhibits 

glucose production by liver 

Major intermediate maternal effects: 1. Glycemic control (FBG, 

1-hr PPG, 2-hr PPG) 

2. Psychological impact of 

treatment 

3. Weight 4. Hypoglycemia 

Effect modifiers 1. Intensity of management (target glycemic control used)2. Cut-off blood sugar used for diet versus oral versus insulin use3. Adherence 4. Need for insulin if other agent used first 

Maternal outcomes:2. Cesarean delivery 3. Pre-eclampsia 4. Hemorrhage 5. Operative vaginal 

delivery 

6. Perineal tears 

Neon1. A2. B3. B4. C

m

5. H6. H7. L8. M9. M10. N11. R12. S13. S

Outcomes in boldface type represent those evaluated in this systematic review. FBG = fasting blood glucose; hr = hour; LGA = large for gestational age; NICU = neonatal intensive care unit; PPG = postprandial glucose; RDS = 

SGA = small for gestational age 

31
32 

Results 

Overview and population characteristics of eight RCTs comparing insulins, insulin 

analogues, and oral diabetes medications. We identified eight RCTs with a total of 845 

participants that met our inclusion criteria for review.30-37 Evidence Table 1 describes the 

primary characteristics of each of the trials. Four of the studies reported study durations of 8 

months to 4 years,30 34 35 37 while the other four studies did not report a study duration.31-33 36 The 

studies were published between 1990 and 2006. For the four studies that reported the starting 

year of the study,30 34 35 37 the earliest starting year was 1985. The trials were conducted in 

diverse countries and populations: Three trials were conducted in the United States,30 32 36 one in 

Italy,34 one in Finland,31 one in India,33 one in Brazil,37 and one in Israel.35 The trials also 

compared different treatment interventions: Two clinical trials32 33 compared insulin to glyburide; 

one trial37 compared insulin, glyburide, and acarbose; two studies34 36 compared regular human 

insulin and insulin lispro; one study31 compared long-acting and short-acting insulins; one 

study38 compared insulin administered two-times-daily and four-times-daily; and one study30

compared diet and insulin. 

The average maternal age ranged from 25 to 34 years and did not substantially differ across 

groups. Only three studies reported the racial distribution of the study participants:33 34 36

Anjalakshi et al.33 reported that 100 percent of the study participants were Indian. Most 

participants (95 percent) in the study by Jovanovic et al.36 were reported as Hispanic. All of the 

participants in the study by Mecacci et al.34 were reported as Caucasian. 

In the studies that reported maternal weight, the weight measures were similar between 

groups. Five studies30 34-37 reported gravidity, and three studies30 32 36 reported the parity of study 

participants, which ranged from nulliparity to 2.5 prior births. 

Consistent with our study selection criteria, each of the eight RCTs reported the test used to 

diagnose gestational diabetes. Three studies31 33 37 used the 75-gm OGTT World Health 

Organization (WHO) criterion. Two studies30 35 used the National Diabetes Data Group (NDDG) 

criterion, and three studies32 34 36 used the 3-hr, 100-gm OGTT with threshold values based on the 

Carpenter and Coustan criterion. Langer et al.32 used the FBG threshold of 95 mg/deciliter (dL) 

based on the 100-gm OGTT Carpenter and Coustan criteria to determine eligibility and as the 

threshold value for treatment with insulin or glyburide. Bertini et al. used a FBG greater than 90 

mg/dL or a 2-hr PPG greater than 100 mg/dL as threshold values for initiation of treatment with 

glyburide or insulin. Anjalakshi et al.33 initiated medical therapy if the 2-hr PPG was 120 mg/dL 

or greater after two weeks of nutritional therapy. The average gestational age at screening and 

diagnosis of gestational diabetes varied across studies from 22 to 28 gestational weeks. Mecacci 

et al.34 reported a median gestational age at diagnosis of 28 weeks (range: 25 to 32). PolyhonenAlho31 reported a gestational age range of 24 to 28 weeks. 

Maternal and neonatal outcomes in eight RCTs of insulin, insulin analogues, and oral 

diabetes medications. Data were available for abstraction for five of the eight maternal 

outcomes of interest and 11 of the 13 neonatal outcomes in Key Question 1. As shown in Table 

2, data were abstracted on several maternal outcomes, including: (1) average glycemic control 

(mg/dL), (2) episodes of maternal hypoglycemia, (3) mean difference in maternal weight; (4) 

cesarean delivery, and (5) episodes of pre-eclampsia. Neonatal outcomes included: 1) infant birth 

weight, (2) macrosomia, (3) LGA, (4) SGA, (5) hypoglycemia, (6) hyperbilirubinemia, (7) 

perinatal mortality, (8) respiratory distress syndrome, (9) congenital malformations, (10) birth 

trauma, and (11) neonatal intensive care admissions. 
33 

Table 2. List of maternal and neonatal outcomes for which data were abstracted from RCTs of medications 

for gestational diabetes 

Insulin versus glyburide 

Insulin versus 

insulin lispro 

Insulin versus 

insulin 

Diet 

versus 

insulin 

Maternal 

outcomes 

Anjalakshi, 

200633 Bertini, 

200537 Langer, 200032

Jovanovic, 

199936 Mecacci, 200334 Nachum, 199935

Poyhon

en-Alho, 

200231

Thompson, 

199030

Cesarean delivery 

for CPD • 

Cesarean delivery, 

total • • • • • • 

Glycemic control* • • • • • • 

Hemorrhage 

Hypoglycemia • • • • 

Operative vaginal 

delivery 

Perineal tears 

Pre-eclampsia • 

Weight • • • 

Neonatal outcomes 

Anoxia 

Birth trauma • • 

Birth weight • • • • • • 

Congenital 

malformations • • 

Hyperbilirubinemia • • • • 

LGA • • • • 

Macrosomia • • • • • 

Mortality • • • 

Hypoglycemia • • • • • 

NICU admission • 

RDS • 

SGA • • • 

Shoulder dystocia 

A dot (•)indicates that the outcome was evaluated in that study. 

* Includes FBG, 1-hr PPG, 2-hr PPG, HbA1c, combined glucose, preprandial glucose 

2-hr PPG = 2 hour postprandial glucose; CPD = cephalopelvic disproportion; FBG = fasting blood glucose; HbA1c = hemoglobin 

A1c; LGA = large for gestational age; NICU = neonatal intensive care unit; RCTs = randomized controlled trials; RDS = 

respiratory distress syndrome; SGA = small for gestational age 

Insulin versus glyburide. 

Maternal outcomes. Three RCTs32 33 37 compared the effects of insulin and glyburide on five 

different maternal outcomes (see Appendix F, Evidence Table 2). Because of the sparseness of 

the data and diversity of outcomes, we were unable to combine any of the studies in metaanalyses; therefore, we have described the results qualitatively here. 

Two RCTs32 33 evaluated maternal glycemic control. Langer et al.32 randomized 404 women 

to receive insulin (n=203) or glyburide (n=201). The insulin regimen was based on maternal 

weight, with two-thirds of the units administered as neutral protamine Hagedorn (NPH) and onethird of the units as regular insulin. In the study by Langer, glyburide was initiated at a dose of 

5.0 milligrams (mg) or 2.5 mg and increased to a maximum dose of 20 mg/day. In the study by 

Anjalakshi,33 glyburide was initiated at a dose of 0.625 mg. No maximum or average dose was 

reported. Langer et al.32 reported no statistically significant differences in average final FBG or 

2-hr PPG levels between those receiving insulin and those on glyburide. The average (mean ± 

standard deviation [SD]) FBG levels were 96 ± 16 for insulin and 98 ± 13 for glyburide (p = 
34 

0.17). The average 2-hr PPG levels were 112 ± 15 for insulin and 113 ± 22 for glyburide (p = 

0.6). 

A smaller randomized trial33 of 26 participants comparing glyburide to insulin also reported 

no statistically significant differences in mean 2-hr PPG levels during pregnancy in the insulin 

versus the glyburide group. 

The two larger RCTs32 37 compared the percentage of women undergoing cesarean delivery 

in each group. Langer32 reported that 49 (24 percent) of the women on insulin underwent 

cesarean delivery, as compared to 46 (23 percent) of the women on glyburide (p > 0.05). Bertini 

et al.37 reported no significant differences in the rate of cesarean delivery among three groups of 

women receiving insulin (44 percent), glyburide (50 percent), or acarbose (52 percent). 

Bertini37 and Langer32 both reported on maternal hypoglycemia. Bertini defined maternal 

hypoglycemia based on the need for hospitalization and reported no episodes of hospitalization 

in any of the three treatment groups. Langer did not define maternal hypoglycemia but reported a 

significantly higher percentage of women with a blood glucose level under 40 mg/dL in the 

insulin group than in the glyburide group (20 percent versus 4 percent; p = 0.03). 

Bertini37 also compared the mean difference in maternal weight at delivery to the baseline 

value in each treatment group and found no significant differences. 

We have concluded that maternal outcomes did not differ significantly between insulin and 

glyburide. However, two33 37 of the three studies presented were limited by their small sample 

size and limited power to detect significant differences in some outcomes. Furthermore, we were 

unable to fully assess other relevant outcomes, such as maternal hypoglycemia, because of 

inconsistencies in the definition of outcomes. Taking into consideration the quantity, quality, and 

consistency of the studies comparing the effects of glyburide versus insulin on maternal 

outcomes, we graded the strength of evidence as very low (see Appendix F, Evidence Table 3). 

Neonatal outcomes. Three RCTs reported on nine different neonatal outcomes (see Appendix 

F, Evidence Table 4). We have described most of the results qualitatively because of the 

sparseness of the data and the diversity of the outcomes (see Table 2). Three studies with 

relatively similar populations and interventions reported data on the mean differences in infant 

birth weight between the insulin and glyburide groups. As shown in Table 3, all three 

RCTs32 33 37 reported lower mean birth weights for the infants in the insulin group than for the 

infants in the glyburide group. In the three RCTs, infants in the insulin group were reported as 

being 120 gm, 244 gm, and 62 gm smaller, respectively, than the infants in the glyburide group. 

We performed a meta-analysis using a random effects model, combining data from the 

Anjalakshi 2006 RCT33 with data from the Bertini 200537 and Langer 200032 RCTs. We report 

the results as the weighted mean difference in infant birth weight in the insulin group as 

compared to the glyburide group. These three RCTs, with a total of 478 infants, provided a 

weighted mean infant birth weight difference of 93 gm (95 percent confidence interval (CI): -191 

to 5 gm). Infants in the insulin group were on average 93 gm smaller than infants in the 

glyburide group (see Table 3 and Figure 4). This finding is not statistically significant, and the 

clinical relevance of such a small difference is unclear. While exclusion of any one study’s 

results would not have markedly altered our results, the largest study by Langer et al. contributed 

the most to the overall mean difference in birth weight. 

Langer et al. reported no significant differences between treatment groups in the percentage 

of infants with hypoglycemia. Among the 201 women on glyburide, 9 percent of the infants 

experienced hypoglycemia, as compared to 6 percent of those with mothers on insulin (p = 0.25). 

Bertini et al. reported a higher percentage of infants with macrosomia (birth weight greater than 
35 

Favors insulin Favors glyburide 

Table 3. Meta-analysis of three RCTs on the effect of insulin and glyburide on infant birth weight: random 

effects model 

Author, year N for analysis 

Mean difference in birth 

weight,┼

 grams 

(standard error) 

Regression 

coefficient 

95% CI 

Anjalakshi, 

200633 23 -120 (161) -90 -193, 12 

Bertini, 200537 51 -244 (133) -68 -174, 37 

Langer, 200032 404 -62 (57) -194 -395, 7.3 

Pooled 

estimates 

Total participants 

= 478 

-93 -191, 5 

95% CI = 95 percent confidence interval 

┼Mean difference = the average difference in birth weight between infants in the insulin group and infants in the glyburide group. 

Figure 4. Meta-analysis of three RCTs on the effect of insulin and glyburide on mean difference in infant birth 

weight 

Figure legend. The shaded boxes represent the mean difference in infant birth weight between the treatment groups in each study. 

The diamond represents the pooled mean difference in birth weight between infants born to mothers treated with insulin and 

infants born to mothers treated with glyburide. 

4,000 gm) and LGA among the women on glyburide than among those on insulin or acarbose. A 

significantly higher percentage of infants had hypoglycemia in the glyburide group than in the 

insulin or acarbose groups (33 percent compared to 4 percent and 5 percent, respectively; p = 

0.006). However, Bertini reported no difference in SGA infants or in perinatal mortality between 

the group on insulin and the group on glyburide. 

We concluded that the use of insulin may be associated with an average 93-gm lower infant 

birth weight when compared to glyburide. However, this difference was not statistically 

significant. It is unlikely that this finding has substantial clinical relevance, given the small 

difference in infant size. We graded the strength of the evidence as very low (see Appendix F, 

Evidence Table 3) for studies comparing the effects of glyburide and insulin on neonatal 

outcomes. While there was consistent evidence on infant birth weight from the three RCTs, the 

lack of consistency in the reporting of other relevant neonatal outcomes across the three studies 

made it difficult to draw firm conclusions. The large trial by Langer and colleagues32 certainly 

Mean difference in infant birth weight

-500 -250 0 250 500

 Combined

 Langer, 2000

 Bertini, 2005

 Anjalakshi, 2006 33 

37 

32 
36 

provided credible estimates for several neonatal comparisons, but the findings were limited to 

one sample of women and had limited generalizability. 

Regular insulin versus insulin lispro. 

Maternal outcomes. Two RCTs34 36 compared the effects of regular insulin and insulin lispro 

on at least one of three maternal outcomes: cesarean delivery, average blood glucose level, and 

maternal hypoglycemia (see Appendix F, Evidence Table 2). Jovanovic36 and Mecacci34

recruited 42 and 49 participants, respectively, in two trials comparing regular insulin to insulin 

lispro. In the trial by Jovanovic, the initial dose of both regular insulin and insulin lispro was 0.7 

units/kilogram (kg) combined with NPH two times per day and adjusted weekly. In the trial by 

Mecacci and colleagues, regular insulin and insulin lispro were started at a dosage of 1 unit/10 

gm of carbohydrates in meals three times per day. The mean dosage was 34.3 units/day in the 

regular insulin group and 35.1 units/day in the lispro group. 

The mean decrease in glycosylated hemoglobin from the time of entry into the study until 

delivery was greater in the women on lispro (mean difference from baseline -0.35 percent) than 

in those on regular insulin (mean difference from baseline -0.07 percent; p = 0.002).36 Maternal 

hypoglycemia, reported as the mean (standard error [SE]) percentage of all blood determinations 

in the hypoglycemic range, was not significantly different in the insulin lispro group and the 

group receiving regular insulin (0.88 percent ± 0.25 percent versus 2.2 percent ± 0.86 percent; p 

> 0.05).36 Mecacci reported significantly higher maternal 1-hr PPG levels in the insulin lispro 

group than in the regular insulin group (108 mg/dL ± 11 versus 88 mg/dL ± 11, respectively; p < 

0.001).34 However, both pre-prandial and 2-hr PPG levels were similar in the two groups (p > 

0.05 for pre-prandial and 2-hr PPG). Both Jovanovic and Mecacci reported no significant 

differences in the proportion of women undergoing cesarean delivery; Jovanovic reported no 

differences across all cesarean deliveries,36 and Mecacci reported no differences between groups 

for cesarean delivery specifically for cephalopelvic disproportion.34

We concluded that maternal glucose control, as measured by glycosylated hemoglobin or 1-

hr glucose levels, did not differ between women treated with insulin lispro and those receiving 

regular insulin. The rate of cesarean delivery in the two groups was also similar. However, 

taking into consideration the quantity, quality, and consistency of the studies comparing the 

effects of regular insulin and insulin lispro on maternal outcomes, we graded the overall body of 

evidence as very low (see Appendix F, Evidence Table 3). There were only a limited number of 

maternal outcome measures reported in either RCT: Only cesarean delivery and maternal glucose 

control were reported by both studies. While there was consistency in the findings reported 

across both studies, the available data were limited to two RCTs with small sample sizes (total N 

= 92). Also, there was only a limited ability to detect differences in outcomes. The absence of a 

difference in the rate of cesarean delivery, for example, was likely a reflection of the small 

number of participants in each RCT and the limited power to detect clinically or statistically 

significant differences. 

Neonatal outcomes. While Jovanovic and colleagues did not provide actual data, they 

reported no difference in the proportion of infants with macrosomia or neonatal hypoglycemia 

who were born to women receiving regular insulin, as compared to women receiving insulin 

lispro (see Appendix F, Evidence Table 4).36 Mecacci et al. reported no difference in mean infant 

birth weight or the number of LGA or SGA infants born to women receiving regular insulin and 

those receiving insulin lispro.34 

Based on limited evidence from these two studies, we concluded that neonatal outcomes do 

not differ substantially between regular insulin and insulin lispro. Taking into consideration the 
37 

quantity, quality, and consistency of the studies comparing the effects of regular insulin versus 

insulin lispro on neonatal outcomes, we graded the strength of the evidence as very low (see 

Appendix F, Evidence Table 3). 

Long-acting insulin versus short-acting insulin. 

Maternal outcomes. Polyhonen-Alho et al. randomized 23 participants to short-acting or 

long-acting insulin (see Appendix F, Evidence Table 2).31 Three doses of short-acting 

insulinwere given before breakfast (4 international units [IU]), lunch (6 IU), and dinner (4 IU). 

Long-acting insulin was administered at 14 IU each morning. There were no reported maternal 

outcomes in the study by Poyhonen-Alho et al.Therefore, for this comparison, we graded the 

strength of the evidence regarding maternal outcomes as insufficient (see Appendix F, Evidence 

Table 3). 

Neonatal outcomes. In their comparison of long-acting to short-acting insulin, PoyhonenAlho et al.31 reported a higher percentage of infants with macrosomia in the group receiving 

long-acting insulin than in the group receiving short-acting insulin (see Appendix F, Evidence 

Table 4). They reported no statistically significant differences in the occurrence of nerve palsy or 

infant metabolic abnormalities between the two groups. We concluded that long-acting insulin 

may be associated with a greater risk of macrosomia than is short-acting insulin. We graded the 

strength of evidence on neonatal outcomes for this comparison as very low (see Appendix F, 

Evidence Table 3) because of the sparseness of the data, the limited sample size, and the fact that 

the available data came from only one study. 

Twice-daily versus four-times-daily insulin. 

Maternal outcomes. Nachum et al. compared outcomes in 136 women randomized to receive 

regular insulin twice-daily with those in 138 women randomized to receive regular insulin fourtimes-daily.35 The exact units of insulin were not reported. There was no risk difference in 

cesarean delivery between the two groups (see Appendix F, Evidence Table 2). Maternal weight 

gain during pregnancy was also similar between the two groups, and the average maternal 

glucose levels were similar. Both groups reported one participant with hypoglycemia. We 

concluded that no evidence exists to suggest a difference in maternal outcomes between twicedaily and four-times-daily use of insulin. For this comparison, we graded the strength of the 

evidence on maternal outcomes as very low (see Appendix F, Evidence Table 3). 

Neonatal outcomes. In contrast to their findings for maternal hypoglycemia, Nachum et al. 

reported a higher proportion of neonatal hypoglycemia in infants born to women on twice-daily 

insulin, as compared to four-times-daily insulin (6 percent versus 1 percent; p = 0.02) (see 

Appendix F, Evidence Table 4).35 The proportion of infants with hyperbilirubinemia was also 

higher in the group treated with twice-daily dosing, as compared to four-times-daily dosing (21 

percent versus 11 percent; p = 0.02). The proportion of infants with macrosomia (birth weight > 

4,000 gm) was similar in the twice-daily and four-times-daily insulin groups (19 percent versus 

16 percent, respectively). The proportion of LGA infants (30 percent versus 26 percent) was also 

similar in the two groups. There was no difference in the proportion of infants with congenital 

abnormalities, birth trauma, or respiratory distress syndrome. Average infant birth weight was 

not reported. Based on this single study, we concluded that twice-daily use of insulin may be 

associated with worse neonatal outcomes than four-times-daily use, but we graded the strength of 

the evidence on neonatal outcomes as very low (see Appendix F, Evidence Table 3). 

Diet versus insulin.

Maternal outcomes. Thompson30 randomized 95 women to dietary management or insulin 

plus dietary management. The diet regimen was 35 kilocalories per kg of ideal body weight. A 
38 

fixed dose of 20 units NPH and 10 units regular insulin was administered daily. There was no 

reported difference in the proportion of women undergoing cesarean delivery (see Appendix F, 

Evidence Table 2). Baseline and FBG levels during the study were also similar between the two 

treatment groups. 

Taking into consideration the quantity, quality, and consistency of the evidence comparing 

the effects of diet versus insulin on maternal outcomes, we graded the strength of the evidence as 

very low (see Appendix F, Evidence Table 3). Thus, the strength of evidence was too low to 

allow us to draw a meaningful conclusion about whether maternal outcomes differ for the two 

treatments. 

Neonatal outcomes. In that same study, there were significant differences in the proportion of 

infants with macrosomia (> 4,000 gm) and in mean birth weight (see Appendix F, Evidence 

Table 4).30 For example, only 5.9 percent of the infants in the diet and insulin group met the 

criteria for macrosomia (≥ 4,000 gm), as compared to 26.5 percent of infants in the group treated 

with diet alone. Similarly, infant birth weight was higher in the diet-alone group than in the diet 

and insulin group (p = 0.002). There was no difference in neonatal hypoglycemia or 

hyperbilirubinemia. Although this one study suggested that neonatal outcomes might be better 

with the use of insulin plus dietary management as compared to diet alone, we graded the 

strength of the evidence as very low (see Appendix F, Evidence Table 3). Additional studies in 

diverse samples of gestational diabetics with well-defined measures of neonatal outcomes are 

needed to make it possible to draw meaningful conclusions regarding these outcomes. 

Metformin versus insulin. There is no currently published evidence on maternal and 

neonatal outcomes in women with gestational diabetes who have been treated with metformin 

versus insulin.39 Recently published data on metformin treatment in pregnancy are primarily 

based on small cohort studies in women with PCOS, in whom it has been used to treat 

infertility.40-43 Women with PCOS and women with type 2 diabetes who continue to receive 

metformin through the first trimester of pregnancy have demonstrated few adverse pregnancy 

events. An ongoing prospective RCT (the Metformin in Gestational Diabetes [MiG] trial) 

comparing metformin with insulin in women with gestational diabetes is currently underway in 

New Zealand and Australia.44 The goal of the trial is to recruit 750 women over a 2-year period, 

collecting data on multiple maternal and neonatal outcomes. The primary outcome is a 

composite of neonatal morbidity, including hypoglycemia, respiratory distress, phototherapy, 

birth trauma, low 5-minute Apgar score, and prematurity. The secondary outcomes include 

maternal glycemic control, neonatal body composition, and markers of neonatal insulin 

sensitivity. An interim report of 453 participants showed no adverse events.44 We anticipate that 

the results of this trial will provide meaningful insight into the potential risks and benefits of 

metformin therapy. The results of the MiG trial are likely to provide further evidence on the 

short-term (e.g., congenital anomalies) and as yet potentially unrecognized long-term effects of 

placental transfer and in utero fetal exposure to metformin. 

Adverse drug events. We found little data concerning the potential risks of oral diabetic 

agents, insulin analogues, or insulin. Table 4 summarizes the potential adverse drug events for 

the newborn, which include: (1) congenital anomalies, (2) hyperbilirubinemia, (3) perinatal 

mortality, (4) birth trauma, (5) respiratory distress syndrome, and (6) neonatal hypoglycemia. As 

shown in Table 4, Langer32 reported no difference in the number of infants with 

hyperbilirubinemia in the glyburide group compared to the insulin group (4 percent versus 6 

percent, respectively; p = 0.36). Langer32 also reported essentially no difference in the number of 

infants with a congenital anomaly between pregnant women treated with glyburide and those 
39 

treated with insulin. There were five infants with a congenital anomaly in the glyburide group 

and four infants in the insulin group (p = 0.74). Nachum,35 in a comparison of twice-daily 

insulin versus four-times-daily insulin, found no difference in the number of infants with a 

congenital anomaly (2 percent versus 1 percent, respectively) or birth trauma (2 percent versus 1 

percent, respectively) in either group (see Table 4). Although the data were limited, there was no 

evidence of differences in neonatal intensive care admission with twice-daily or four-times-daily 

insulin (p = 0.68). Further investigations with sufficient power to detect meaningful differences 

will provide much needed evidence regarding potentially adverse neonatal and early childhood 

effects of medical treatments. While there is currently little evidence on metformin, long-term 

followup of infants will provide evidence on the downstream consequences of placental transport 

and intrauterine exposure to metformin. 

There were few reports of maternal hypoglycemia. Bertini37reported none; Langer32 reported 

a higher number of women with FBG less than 40 mg/dL in the glyburide than in the insulin 

group. Maternal hypoglycemia was not significantly different in the insulin lispro group and the 

group receiving regular insulin (0.88 percent ± 0.25 percent versus 2.2 percent ± 0.86 percent; p 

> 0.05).36 The twice-daily insulin and four-times-daily insulin groups each had one case of 

maternal hypoglycemia.35

Quality assessment of the RCTs. We assessed five parameters of quality for each of the 

RCTs. Participants were randomized in each of the eight RCTs, with five of the studies30 32 35-37

describing the randomization scheme (see Appendix F, Evidence Table 5). None of the trials 

were blinded. Only half of the trials30 34 36 37 reported and described participant withdrawals and 

the reasons for losses to followup. 

Limitations. There are specific limitations of the RCTs that deserve further comment. First, 

as outlined in Table 2, maternal and neonatal outcomes were not consistent across studies. Few 

of the same outcome measures were included in two or more studies. Furthermore, the 

definitions of outcomes varied across studies. For example, among the three trials of the effects 

of insulin and glyburide, the diagnosis of maternal hypoglycemia was based on three different 

measures (< 40 mg/dL; < 40 mg/dL on two or more occasions; hypoglycemia requiring 

hospitalization). The small number of the trials comparing medical treatments also limited our 

ability to draw substantial conclusions. None of the trials included a power analysis or effect size 

estimation for various outcome measures. None of the trials included an intention-to-treat 

analysis (see Appendix F, Evidence Table 2). 

Observational studies of the effect of insulin and oral diabetes medications on maternal 

and neonatal outcomes. 

Overview and population characteristics of five observational studies. We identified five 

observational studies that examined a total of 911 patients with gestational diabetes and met our 

inclusion criteria for review.45-49 Evidence Table 6 (see Appendix F) describes the characteristics 

of each study. Each of the five studies was conducted in the United States between 1999 and 

2005. The study duration ranged from 2 to 3 years across the five studies. Two studies46 48

compared maternal and neonatal outcomes in women treated with insulin and women treated 

with glyburide. Two studies45 47 examined factors related to glyburide success or glyburide 

failure. Glyburide “successes” were women with gestational diabetes who maintained target 

glucose levels on glyburide alone. Glyburide “failures” were those who were switched to insulin 

or for whom insulin was added to the glyburide therapy. One study49 compared maternal and 

neonatal outcomes in women treated with insulin and women treated with glyburide and also 

reported on factors related to glyburide failure.
Table 4. Adverse events reported in RCTs of medications for gestational diabetes. Numbers are n (%) 

Author, year Treatment, N 

Hyperbilirubinemia Congenital malformation Perinatal mortality Birth trauma Other neo

outcom

Insulin versus glyburideAnjalakshi, G1: Insulin, 13 200633 G2: Glibenclamide, 10 

G1: Insulin, 27 0 (0) G2: Glyburide, 24 0 (0) 

Bertini, 200537

G3: Acarbose, 19 0 (0) 

G1: Insulin, 203 8 (4)║ 4 (2) 2 (1) NICU admi

14 (7) 

Langer, 200032

G2: Glyburide, 201 12 (6)║ p = 0.36† 5 (2) p = 0.74† 2 (1) p = 0.99† NICU admi

12 (6) p = 0

Insulin versus insulin lisproJovanovic, G1: Regular human insulin, 23 1999 36 G2: Insulin lispro, 19 Mecacci, G1: Regular human insulin, 24 2003 34 G2: Insulin lispro, 25 Insulin versus insulinNachum, G1: Insulin twice daily, 136 29 (21)^ 2 (2) 1 (1) 3 (2) RDS: 0 (0.01999 35 G2: Insulin four times daily, 138 15 (11)^ 1 (1) 0 (0.00) 2 (1) RDS: 1 (1) Poyhonen- G1: Short-acting insulin, 11 3 (27.27) 0 (0.00) Alho, 2002 31 G2: Long-acting insulin, 12 3 (25.00) 1 (8.33) Diet versus insulin

G1: Diet, 50 0 (0.00)Ω Thompson, 

1990 30 G2: Diet and insulin, 45 0 (0.00)Ω

† Comparing G1 to G2. ║ Serum bilirubin > 12 mg/dL. 

^ Serum bilirubin > 205mmol/L at >= 34 weeks of gestation or > 137 mmol/L at < 34 weeks. 

Ω Serum bilirubin > 10 mg/dL. 

RCT = randomized controlled trial; dL = deciliter; G = group; L = liter; mg = milligram; mmol = millimole; NICU = neonatal intensive care unit; RDS 

syndrome

40 
41 

Four studies45-47 49 used the 100-gm Carpenter and Coustan criterion (2003 ADA criterion), 

and one study48 used the NDDG criterion to diagnose gestational diabetes. Four studies45 47-49

reported the percentage of participants with prior gestational diabetes. All five studies reported 

the gestational age of pregnancies at the time of diagnosis of gestational diabetes; these ages 

ranged from 18 to 33 weeks of gestation. 

All five studies reported the average maternal age at gestational diabetes diagnosis, which 

ranged from 26.4 to 32.8 years. Three studies reported the racial distribution of the 

participants.46 48 49 The majority of the participants (87 percent) in the study by Chmait et al.45

were of Hispanic origin. Jacobson and Rochon reported a racially diverse cohort of AfricanAmerican, Caucasian, Asian, and Hispanic women (see Appendix F, Evidence Table 6). Three 

studies47-49 reported baseline measures of body weight in terms of the mean pre-pregnancy BMI 

(ranging from 26 to 33.9 kg/m2

). One study47 did not report the actual BMI but also reported no 

significant differences in BMI between study groups. The proportion of nulliparous women 

ranged from 7.7 percent to 33 percent across the five studies. 

The initial glyburide dose was 2.5 mg daily in three of the four studies. Two studies reported 

an initial dose between 2.5 mg and 5 mg per day. Dosages were escalated on the basis of glucose 

control to a maximum of 20 mg/day in each study.45-49 The initial insulin dose in three45-47of the 

four studies was 0.7 units/kg. One study49 reported a standard regimen consisting of a 

combination of NPH and regular insulin injected subcutaneously three times daily. One study48

did not report the initial insulin dose. Insulin levels were adjusted, with four studies reporting no 

maximum dose. Jacobson48 reported a mean dose of 34.4 units per day in 249 of the 268 women 

treated with insulin. 

Observational studies. Because of the differences in study design, the use of noncomparable groups, and the differences in outcome measures, we chose not to conduct a metaanalysis of the five observational studies included in our review. We offer a summary of the 

relevant findings and study conclusions and discuss their potential relevance for future research. 

We include the data on 5 maternal and 11 neonatal outcomes from the observational studies. The 

maternal outcomes were: (1) operative vaginal delivery, (2) pre-eclampsia, (3) cesarean delivery, 

(4) glucose control, and (5) maternal hypoglycemia. The neonatal outcomes were: (1) 

hypoglycemia, (2) hyperbilirubinemia, (3) macrosomia, (4) LGA, (5) SGA, (6) perinatal 

mortality, (7) infant birth weight, (8) neonatal intensive care admissions, (9) birth trauma, (10) 

congenital malformations, and (11) shoulder dystocia. 

Summary of the observational studies of maternal and neonatal outcomes. Jacobson et 

al.48 retrospectively compared 268 women treated with insulin between 1999 and 2000 to 236 

women treated with glyburide between 2001 and 2002. Their study also included 80 women 

treated with insulin from 2001 to 2002. Sociodemographic data were collected from clinical 

databases and a retrospective chart review. Jacobson reported a higher final average FBG (97.7 

mg/dL ± 12.2 [standard deviation (SD)] versus 90.2 ± 12.7; p < 0.001), 1-hr PPG (137.8 mg/dL 

± 23.6 [SD] vs 131.4 ± 23.3; p < 0.001) and 2-hr PPG (118.8 mg/dL ± 19.6 versus 117.6 ± 23.2; 

p < 0.05) in the insulin group than in the glyburide group (see Appendix F, Evidence Table 7). 

Conversely, the average number of FBG levels that met the criterion for maternal hypoglycemia 

was significantly higher in the glyburide group than in the insulin group (p < 0.001). Also, in 

multivariate analysis, women treated with glyburide had a higher likelihood of developing preeclampsia (odds ratio [OR] = 2.32; 95 percent CI: 1.17 to 4.63) than did women on insulin 

therapy. There were no differences in cesarean delivery (p = 0.7) or operative vaginal delivery (p 

= 0.8) rates between the two groups. 
42 

In multivariate analysis, after adjustment for race/ethnicity, FBG on OGTT, BMI, and 

gestational age at diagnosis of gestational diabetes, the use of glyburide therapy was not 

statistically associated with neonatal hypoglycemia, hyperbilirubinemia, macrosomia, or delivery 

of LGA or SGA infants when compared to insulin therapy (see Appendix F, Evidence Table 8).48

As shown in Evidence Table 8, the 95 percent CI for each outcome included 1. However, 

glyburide therapy was significantly associated with a lower likelihood of neonatal intensive care 

admission (OR = 0.5; 95 percent CI: 0.34 to 0.93). While Jacobson concluded that glyburide was 

as effective as insulin in the management of gestational diabetes, baseline differences between 

the two treatment groups suggested that the women on glyburide may have been healthier or had 

less underlying insulin resistance than those in the insulin group. Women in the original insulin 

group (1999 - 2000), for example, had a higher average BMI (31.9 kg/m2

 ± 6.8 versus 30.6 ± 7.0; 

p = 0.04) and higher FBG on the baseline OGTT (105.4 mg/dL ± 12.9 versus 102.4 ± 14.2; p = 

0.005) than did women in the glyburide group. While Jacobson et al. adjusted for several 

important covariates, they did not adjust for prior gestational diabetes status, which might also 

indicate underlying insulin resistance. 

Conway et al.47 followed 75 women who elected to be treated with glyburide after failing to 

achieve adequate glucose control with diet alone.47 The study compared pregnancy outcomes in 

12 women with glyburide failure who were converted to insulin therapy to the outcomes in 63 

women who were successfully treated with glyburide until delivery. The initial glyburide dose 

was 2.5 mg/day and was escalated on the basis of glucose control to a maximum of 20 mg/day. 

There was no difference in the proportion of macrosomic infants in the glyburide failure group 

and the glyburide success group (8 percent versus 11 percent; p = 1.0) (see Appendix F, 

Evidence Table 8). Also, there was no difference in average infant birth weight (3267 gm ± 815 

in the failure group versus 3327 gm ± 634 in the success group; p = 0.78). The absence of 

significant differences may be due in part to the limited power of the study to detect a small 

difference between groups. 

Chmait45 conducted a prospective, cohort study of 69 women with gestational diabetes who 

failed diet alone and elected to proceed with glyburide therapy. Of the 69 participants, 13 

participants were started on glyburide therapy but later required the addition of insulin or were 

transitioned from glyburide to insulin therapy because of inadequate glucose control. Fifty-six 

(81 percent) of the participants achieved adequate glucose control on glyburide. 

While the mean FBG and 1-hr PPG levels on the diagnostic OGTT were similar for the 

glyburide failure group (105 mg/dL and 206 mg/dL, respectively) and the glyburide success 

group (94 mg/dL and 199 mg/dL respectively; p > 0.1 for both measures), there were significant 

differences in glucose values during treatment (see Appendix F, Evidence Table 7).45 The mean 

FBG levels during treatment with glyburide (114 mg/dL) and the mean 1-hr PPG levels (145 

mg/dL) were both significantly greater for the glyburide failure group than for the glyburide 

success group (FBG 88 mg/dL; 1-hr PPG 124 mg/dL; p < 0.001 for both measures). There was 

no difference in the proportion of cesarean deliveries between the two groups (38 percent in 

failure group versus 34 percent in success group; p > 0.05). Also, there were no differences in the 

proportion of macrosomic infants (10 percent in the failure group versus 18 percent in the 

success group; p = 1.0) or average infant birth weight (3608 gm ± 398 in the failure group versus 

3430 gm ± 714 in the success group; p = 0.78) (see Appendix F, Evidence Table 8). There were 

no differences in hyperbilirubinemia or neonatal intensive care admissions. 

Chmait concluded that women with gestational diabetes with FBG levels under 110 mg/dL 

and 1-hr PPG levels under 140 mg/dL were more likely to successfully continue glyburide 
43 

therapy throughout pregnancy. However, these findings were based on a small sample size 

without any reported adjustment for confounders. Also, because the majority of participants were 

Hispanic, the findings may not apply to other populations. 

Yogev et al.46 conducted a prospective study of 82 participants recruited from a diabetes 

clinic in which they sought to determine the rate of asymptomatic maternal hypoglycemia in 

women treated with diet, insulin, or glyburide. Of these 82 participants, 27 were treated with diet 

alone, 25 with glyburide, and 30 with insulin. As compared to the women on glyburide, the 

women on insulin had a 4.4-fold higher likelihood of having an episode of asymptomatic 

hypoglycemia (OR = 4.4; 95 percent CI: 1.4 to 13.9) (see Appendix F, Evidence Table 7). There 

were no episodes of hypoglycemia among the participants treated with diet alone. 

Finally, Rochon et al. conducted a retrospective study of 101 participants recruited from a 

prenatal diabetes clinic in order to identify characteristics that might predict failure of glyburide 

therapy and to evaluate whether those women who had failed glyburide were more likely to 

undergo adverse pregnancy outcomes.49 These gestational diabetics, who had undergone a 1-

week trial of diet but were not meeting glycemic goals (FBG between 60 and 90 mg/dL and 2-hr 

PPG of 120 mg/dL or less), were then started on glyburide. Those who were consistently 15 

percent to 25 percent above the FBS or 2-hr PPG target values were switched to insulin therapy. 

Eighty (79 percent) of the 101 participants were identified as glyburide “successes” compared to 

21 (21 percent) who were categorized as glyburide “failures.” Rochon and colleagues reported 

few statically significant differences in the maternal or neonatal outcomes for the success and 

failure groups. The rate of neonatal intensive care admissions was higher in the glyburide 

success group than in the glyburide failure group (33 percent versus 10 percent; p = 0.04). Infant 

birth weight was similar between the success and failure groups (3,415 gm ± 620 compared to 

3,319 ± 559; p = 0.5). The absence of significant differences in birth weight may reflect, at least 

in part, the limited power of the study to detect a small difference between groups. 

There was no difference in the percentage of cesarean deliveries (38 percent versus 43 

percent) between the success and failure groups. The rate of shoulder dystocia (10 percent versus 

11 percent) was also similar in both groups. Although congenital anomalies were not included as 

one of the outcomes, Rochon and colleagues reported two neonatal intensive care admissions in 

the glyburide success group that were due to a congenital anomaly. Also, most admissions to the 

neonatal intensive care unit were related to neonatal hypoglycemia (10 infants in the success 

group and 2 in the failure group). The authors concluded that there are few adverse maternal or 

neonatal outcomes in pregnancies in which glyburide therapy has failed and insulin is required. 

They also concluded that the rate of neonatal intensive care admissions was higher in the 

glyburide success group than in the glyburide failure group, primarily because of neonatal 

hypoglycemia. 

Quality assessment of cohort studies. The quality of each of the five cohort studies was 

assessed using a modified version of the STROBE criteria.23 Each study reported reproducible 

inclusion and exclusion criteria and recruited participants using a consecutive sample of 

participants (see Appendix F, Evidence Table 9). Only two of the five studies had a prespecified, 

clearly presented hypothesis.46 48 None reported power analyses to estimate effect size. As 

previously stated, insufficient power may have accounted for the absence of detectable 

differences in infant birth weight in the studies by Conway47 and Rochon.49 While the loss-tofollowup rate was reported in four45-47 49 of the five studies, only one study45 described the 

characteristics of those lost to followup. Two studies reported the actual percentage of missing 
44 

data,45 46 but only one of these two studies45 described how the missing data were handled in the 

analysis. 

Limitations. In addition to the quality assessment outlined above, two additional limitations 

deserve further comment: First, only one study48 adjusted for potential confounders. Jacobson 

adjusted for several relevant covariates, including race/ethnicity, FBG, BMI, and gestational age 

at diagnosis of gestational diabetes. Additional adjustment for relevant labor complications, such 

as maternal hypertension or intrapartum infection, might help to elucidate the association of 

insulin therapy with maternal and neonatal outcomes. Second, there was no discussion of 

potential selection bias in the conduct of the observational study or the potential influence of this 

bias on the associations reported. Because of the observational design and lack of adjustment for 

confounders, it is difficult to draw conclusions with confidence. 

Given the limitations of the observational studies, we based our conclusions on the available 

RCTs. None of the observational studies was strong enough to justify a modification of the 

conclusions drawn from the RCTs. 

Key Question 1a. How does maternal outcome vary based on the level of glucose at the initiation 

of a medication? 

Key Question 1b. How does neonatal outcome vary based on the level of glucose at the initiation 

of a medication? 

Maternal glycemia and maternal and neonatal outcomes. We found no evidence for 

variation in maternal or neonatal outcomes on the basis of the glucose level at the initiation of 

treatment with an oral agent or insulin. One ongoing study may provide evidence to address this 

important clinical question. We look forward to the publication of the findings from the 

Hyperglycemia and Adverse Pregnancy Outcomes (HAPO) Study.50 The HAPO Study is a 5-

year, prospective, observational study designed to examine the association of various levels of 

maternal glycemia in the third trimester with adverse pregnancy outcomes in a multi-national, 

multicultural, ethnically diverse cohort of women. This investigator-initiated observational study 

has recruited 23,325 pregnant women from nine countries. All participants undergo glucose 

tolerance testing. Those participants with levels below the pre-defined threshold are provided 

with standard obstetrical care, and their providers are blinded to their glucose levels. Maternal 

blood is obtained for measurement of serum C-peptide and hemoglobin A1c (HbA1c) and cord 

blood for serum C-peptide and plasma glucose; a capillary specimen is obtained between 1 and 2 

hr after delivery for measurement of neonatal plasma glucose. Neonatal anthropometrics are 

obtained, and followup data are collected at 4-6 weeks post-delivery. The primary outcomes are 

cesarean delivery, increased fetal size (macrosomia/LGA/obesity), neonatal morbidity 

(hypoglycemia), and fetal hyperinsulinemia. Preliminary findings, presented at the 67th Annual 

Scientific Session of the ADA,51 suggest a linear association between rising maternal glucose 

levels in the third trimester and the likelihood of cesarean delivery. Large babies (defined as 

being in the largest 10 percent of the newborn population) were born to only 5 percent of women 

with the lowest fasting plasma glucose levels (less than 75 mg/dL) but to 27 percent of those 

with the highest levels (greater than 100 mg/dL). Women with the highest glucose levels had a 

6.6 times greater risk of delivering an infant with macrosomia than did women with the lowest 

glucose levels (OR = 6.6; 95 percent CI: 4.6 to 9.6). Rising glucose levels were also associated 

with a linearly higher likelihood that the newborn would be above the 90th percentile for total 
45 

skinfold thickness (5.4 percent at the lowest glucose levels versus 28 percent at the highest, OR = 

1.52, 95 percent CI: 1.40 to 1.59). These findings suggest that the likelihood of adverse outcomes 

increases linearly with rising maternal glucose levels even when the range of maternal glucose 

levels is considered normal. These findings should provide further information on the level of 

glycemia at which adverse events may occur, although the glucose levels may be below the 

threshold values for gestational diabetes. Also, these findings may provide insight into the level 

of glucose at which therapy with an oral agent or insulin should be added to diet therapy. 

Conclusions 

We found limited evidence on the risks and benefits of oral diabetes agents, insulin 

analogues, and insulin. The available evidence, to date, suggested little difference in maternal or 

neonatal outcomes for treatment with oral agents versus any type of insulin, but inconsistencies 

in clinical outcomes measures across studies and lack of data make it difficult to draw firm 

conclusions. No studies compared metformin to insulin or other oral agents. Our meta-analysis 

showed a small, non-significant lower infant birth weight in pregnant women treated with insulin 

as compared with those treated with glyburide. This small difference of 93 gm is unlikely to have 

significant clinical relevance. Further studies are needed to determine whether there is a 

consistent and clinically definable difference in infant birth weight. There appeared to be little 

difference in various reported measures of maternal glucose control in women treated with 

glyburide versus insulin (FBG and 2-hr PPG) or in women treated with insulin lispro versus 

regular insulin (glycosylated hemoglobin and 1-hr PPG). It is unclear whether differences in 

maternal hypoglycemia are associated with different treatment regimens: Only one study of 

glyburide and insulin37 defined threshold values for maternal hypoglycemia as part of the study 

protocol. In one study comparing insulin lispro to regular insulin, maternal hypoglycemia was 

based on the need for hospitalization rather than threshold glucose values. No available evidence 

met our inclusion criteria for variations in maternal or neonatal outcomes being based on glucose 

levels at the initiation of oral agents or insulin. However, as we have indicated above, ongoing 

investigations, such as the HAPO Study, may provide evidence to suggest threshold values at 

which clinicians should add oral diabetic agents, insulin analogues, or insulin to diet therapy. 

The results of the MiG trial should provide evidence regarding the relative benefits and harms of 

treatment with metformin versus insulin. Finally, additional data regarding congenital anomalies, 

the long-term consequences of glyburide use, and the effects of metformin transport across the 

placenta should inform clinical practice and clinical guidelines for the use of oral diabetic agents 

in pregnancy. 

Key Question 2 

What is the evidence that elective cesarean delivery or the choice of timing of induction in 

women with gestational diabetes results in beneficial or harmful maternal and neonatal 

outcomes? 

a. What is the evidence for elective cesarean delivery at term, as compared to an attempt at 

vaginal delivery (spontaneous or induced) at term, with regard to beneficial or harmful 

maternal and neonatal outcomes in gestational diabetes? 

i. cesarean versus spontaneous labor and vaginal delivery 
46 

ii. cesarean versus induced labor and vaginal delivery 

iii. cesarean versus any attempt at vaginal delivery at term 

b. What is the evidence for labor induction at 40 weeks, as compared to labor induction at an 

earlier gestational age (less than 40 weeks) or spontaneous labor, with regard to beneficial or 

harmful maternal and neonatal outcomes in gestational diabetes? 

i. labor induction at less than 40 weeks versus labor induction at 40 weeks 

ii. labor induction at 40 weeks versus spontaneous labor 

iii. labor induction at less than 40 weeks versus spontaneous labor 

c. How is the EFW related to outcomes of management of gestational diabetes with elective 

cesarean delivery or the timing (i.e., gestational age range) of labor induction? 

d. How is gestational age related to outcomes of management of gestational diabetes with 

elective cesarean delivery or the choice of timing (i.e., gestational age range) of labor 

induction? 

Maternal outcomes 

• cesarean delivery 

• hemorrhage 

• infection 

• operative vaginal delivery 

• perineal tears 

Neonatal outcomes 

• anoxia 

• birth trauma 

• birth weight 

• congenital malformations 

• hyperbilirubinemia 

• hypoglycemia 

• LGA 

• macrosomia 

• mortality 

• neonatal intensive care admissions 

• respiratory distress syndrome 

• shoulder dystocia 

• SGA 

Background and Conceptual Framework 

Clinicians use a variety of clinical parameters in their clinical decisionmaking for intrapartum 

management. Estimates of fetal weight, gestational age, and maternal glucose control are 

measures of particular importance in pregnancies complicated by gestational diabetes. Clinical 

management can also be influenced by patient preference and provider perception. Management 

options include expectant management, labor induction, or “elective” cesarean delivery. In the 

context of diabetic pregnancies, we refer to “elective” cesarean delivery as a procedure 

performed following discussion between the patient and clinician, with the goal of avoiding 

adverse neonatal outcomes such as shoulder dystocia, nerve palsy, or fracture. 

Medical institutions have traditionally developed protocols for labor management of women 

with gestational diabetes, incorporating a combination of anecdotal experience, published 

literature, and recommendations by national clinical organizations. Both the ACOG and the 

ADA7 13 have provided guidance with regard to labor management of pregnancies complicated 

by gestational diabetes. The current guidelines, however, are based primarily on retrospective 

studies that summarize individual hospitals’ experiences with maternal and neonatal outcomes. 

Limitations in the available literature on the management of women with gestational diabetes 
47 

may have contributed to delays in the development of broadly accepted guidelines for clinical 

management and to the current variation in practice patterns and clinical outcomes. 

Our objective was to conduct a systematic review of the available literature on the effect of 

EFW and gestational age on maternal and neonatal outcomes in pregnancies involving 

gestational diabetes. We also focused on the effect of delivery options (i.e., expectant 

management, induction, and elective cesarean delivery). We developed a conceptual framework 

to guide the review of Key Question 2, incorporating the key steps in clinical decisionmaking for 

labor management (see Figure 5). We focused on gestational age and EFW and the potential 

influence of these measures on options for delivery. Although they are outside the scope of this 

review, we include contributing maternal and metabolic factors in the conceptual framework, 

since these are key elements in the broader context of labor management of women with 

gestational diabetes. 

Figure 5. Conceptual framework of the effects of gestational age, fetal weight, and labor management on 

maternal and neonatal outcomes 

GDM = gestational diabetes mellitus; kg =kilogram; NICU = neonatal intensive care unit 

Results 

Overview and population characteristics of studies of the effect of labor management on 

outcomes. Evidence Table 10 describes the characteristics of each of the eight studies that met 

our criteria for review (see Appendix F). Five studies were conducted in the United States52-56

and three in Israel.57-59 The studies were conducted between 1983 and 2004, and the study 

periods ranged from 4 to 19 years. We identified one RCT that compared the effect of two labor 

induction protocols on maternal and perinatal outcomes.55 We also identified four observational 

studies that examined the effect of EFW and/or gestational age on delivery management and 

outcomes.53 57-59 One observational study56 compared the effect of labor induction in a class A2 

gestational diabetes sample at 38 weeks of gestation to expectant management of a class A1 

Sociodemographics

Age 

Race 

Family history 

Obesity 

GDM history 

Macrosomia 

Glucose 

management in 

pregnancy 

(diet versus insulin or 

oral hypoglycemics) 

Macrosomia 

≥ 4kg versus 

≥ 4.5 kg 

Weight relative to 

gestational age 

OR 

“Elective” 

cesarean 

Elective induction 

Planned delivery 

management 

Maternal outcomes

Cesarean delivery 

Pre-eclampsia 

Eclampsia 

Postpartum hemorrhage 

Operative vaginal delivery 

(forceps or vacuum) 

Perineal tears 

Placental abruption 

Postpartum infection 

Neonatal outcomes

Birth weight 

Macrosomia (> 4 or 4.5 kg) 

Birth trauma 

Nerve palsy or fracture 

Anoxia or acidosis 

Hypoglycemia 

Hyperbilirubinemia 

Length of NICU stay 

Gestational age or fetal 

weight range 

Gestational age 

Clinical decisionmaking 
48 

sample. Gestational diabetes class A1 is managed with diet alone, while gestational diabetes 

class A2 requires insulin or glyburide in addition to diet to manage glucose levels. One 

retrospective cohort study compared a trial of labor to repeat cesarean delivery in a sample of 

women with gestational diabetes and a prior cesarean delivery.52 Another study54 examined the 

risk of shoulder dystocia in gestational diabetes patients undergoing a trial of labor. 

Outcomes from eight studies. The eight studies identified for this review were 

heterogeneous with regard to methodology, comparison groups, the time period in which the 

study was conducted, the length of the study period, the populations included, and the outcome 

measures of maternal and infant well-being (see Table 5 and Appendix F, Evidence Table 10). 

Because of the extent of this heterogeneity, we were unable to provide any quantitative synthesis 

of the literature. We have summarized each study individually, incorporating a summary of the 

objectives, study design, results, and conclusions presented by the authors. Also, we identify 

methodological issues that might influence these conclusions. We have categorized our summary 

of the studies first in terms of study design (RCTs followed by observational studies) and then in 

terms of the primary exposure (i.e., fetal weight, gestational age, delivery method) under study. 

The categories we considered were: (1) gestational age and timing of induction, (2) EFW and 

elective cesarean or timing of labor induction, (3) gestational age or EFW and timing of labor 

induction, (4) gestational age at delivery, and (5) gestational age and/or EFW and timing of labor 

induction and/or elective cesarean delivery. 

Impact of gestational age on the timing of labor induction. We identified one RCT that 

addressed the impact of labor induction at term, as compared to expectant management, on 

maternal and neonatal outcomes in gestational diabetes.55 Kjos 1993 recruited 200 women from 

one tertiary care center. The study sample included 187 women with class A2 gestational 

diabetes and 13 women with pre-existing (class B non-insulin-requiring) diabetes. Inclusion 

criteria were clearly stated: good glucose control in at least 90 percent of measured levels, 38 

completed weeks of gestation, good compliance with clinic appointments and home glucose 

monitoring, no antepartum testing abnormalities, singleton gestation with cephalic presentation, 

EFW less than 3800 gm at 38 weeks with no evidence of fetal growth restriction, no other 

medical or obstetrical complications, and no more than two previous cesarean deliveries. Women 

who met the inclusion criteria, agreed to randomization, and had an established diagnosis of 

diabetes were eligible to participate in the study. Women were randomized to either expectant 

management or induction of labor at 38 weeks. Of those with pre-existing diabetes, nine were in 

the active induction group and four were in the expectant management group. The two treatment 

groups did not differ significantly in terms of maternal age, gravidity, parity, maternal weight, or 

gestational age at entry into the study. The racial distribution of the study participants was not 

reported. Gestational age was calculated from the first day of the last menstrual period and 

adjusted if ultrasound estimation (before 22 weeks) differed from the menstrual age by 10 days 

or more. Amniocentesis and measurement of the lecithin-to-sphingomyelin (L/S ratio) was used 

if gestational age could not be accurately determined. Labor was induced with intravenous 

oxytocin at 38 weeks or in the presence of fetal lung maturity. Vaginal prostaglandin was used 

for cervical ripening if indicated (Bishop’s score less than four) and if the patient had no 

contraindications to therapy. 

Maternal outcomes. Thirty of 100 women in the active induction group had spontaneous 

labor or cesarean delivery prior to scheduled induction, and 56 of 100 women in the expectant 

management group required induction or cesarean delivery prior to the onset of labor for medical 

indications (see Appendix F, Evidence Table 11).55 
Table 5. Summary table of eight studies examining the effect of delivery management on maternal and neonatal outcomes 

Author, year Type of study 

Control group 

intervention/ 

protocol 

Study group 

intervention/ 

protocol Population Key limitations of study 

Kjos, 199355 Randomized 

controlled trial 

Expectant management 

Induced at 38 weeks GDMA2 

Pre-gestational diabetics (6.5%) 

Randomization process not descHigh rate of induction in control g

Conway, 199853 Prospective cohort study with HC; 

protocol-based 

Expectant management 

US at 37-38 weeks CD if EFW>4,250gm Induced if LGA and EFW<4,250gm 

GDMA1 GDMA2 Pre-gestational diabetics (8.6%) 

No adjustment for confounders No stratified analysis for GDM clNo power calculation 

Lurie, 199658 Prospective cohort 

study with HC; protocol-based 

Induced if EFW>4000gm CD if EFW>4,500gm (sub-group analysis: delivered > 40 weeks)

Induced at 38 weeks, CD if EFW>4,500gm 

GDMA1 GDMA2 

No adjustment for confounders No stratified analysis for GDM clSmall number of subjects 

Lurie, 199257 Retrospective cohort 

study; groups based on gestational age at delivery 

Induced if EFW>4000gm CD if EFW>4,500gm, delivery > 40 weeks 

Induced if EFW>4,000g CD if EFW>4,500gm, delivery < 40 weeks 

GDMA1 GDMA2 Stratified analysis 

No adjustment for confounders Outcomes not clearly defined 

Peled, 200459 Retrospective cohort 

study comparing four protocol periods 

HC A: Induced at 42 wks CD if EFW>4,500gm HC B: Induced at 40 weeks if LGA CD if EFW>4,000gm HC C: Induced at 40 weeks if LGA CD if EFW>4,000gm 

Period D: Induced at 38 weeks if LGA CD if EFW>4,000gm 

GDMA1 GDMA2 

No adjustment for confounders Limited information on baseline characteristics Exclusion criteria not reported No stratified analysis for GDM clLong study period (19 years) 

Rayburn, 200556 Retrospective cohort study; protocol-based Expectant management of 

GDMA1 

Induction of GDMA2 at 38 weeks 

GDMA2 versus GDMA1 

Significant differences in baselincharacteristics between groups Outcomes not clearly defined 

Marchiano, 200452 Retrospective cohort study Trial of labor Elective repeat CD GDMA1 with previous CD Results only generalizable to pat

with previous CD 

Keller, 199154 Retrospective cohort 

study 

Trial of labor GDMA1 

GDMA2 

No adjustment for confounders Lack of appropriate comparison Limited information on baseline characteristics 

CC = concurrent control group; CD = cesarean delivery; EFW = estimated fetal weight; GDM = gestational diabetes mellitus; GDMA1 = diet-controll

GDMA2 = gestational diabetes requiring medical therapy; gm = gram; HC = historical control group; LGA=large for gestational age; US=ultrasound 

49 
50 

In the final intention-to-treat analysis, there was no difference in cesarean delivery rates 

between the two groups (25 percent in the active induction group versus 31 percent in the 

expectant management group; p = 0.43). The average gestational age at delivery in the induction 

group was 1 week less than the gestational age in the expectant management group (39 weeks 

versus 40 weeks; p < 0.05). 

Neonatal outcomes. Even after adjustment for gestational age at delivery, maternal weight, 

and maternal age, the average infant birth weight in the expectant management group (3,672 gm; 

95 percent CI: 3,595 to 3,749 gm) was significantly greater than that in the active induction 

group (3,446 gm; 95 percent CI: 3,368 to 3,522 gm; p < 0.01) (see Appendix F, Evidence Table 

12).55 The proportion of infants with macrosomia, defined as a birth weight of 4,000 gm or more, 

was higher in the expectant management than in the active induction group (27 percent versus 15 

percent; p = 0.05). When defined as a birth weight greater than the 90th percentile, the proportion 

of infants with macrosomia was also higher in the expectant management than in the induction 

group (23 percent versus 10 percent; p = 0.02). There was no significant difference in the number 

of cases of shoulder dystocia or in the average 5-minute Apgar score between the two groups. 

Also, there were no episodes of neonatal hypoglycemia requiring treatment and no perinatal 

deaths in either treatment group. 

The findings of this RCT suggested that infants born to women undergoing induction at 38 

weeks have significantly lower average birth weights and perhaps a lower risk of macrosomia 

than do those born to women treated with expectant management. The absence of any difference 

in cesarean delivery rates suggested that maternal morbidity among women undergoing 38-week 

induction is similar to that of women undergoing expectant management. The similarity in 

demographics of the two groups suggested appropriate randomization. Adjustment for key 

covariates, including gestational at delivery, maternal weight, and age strengthened our 

confidence in the observed associations. 

Impact of EFW on elective cesarean delivery and timing of labor induction. We 

identified one observational study on the effect of EFW on maternal and neonatal outcomes 

related to elective cesarean delivery and the timing of induction of labor.53 Conway et al. 

prospectively followed diabetic women (91.4 percent with gestational diabetes) who were 

delivered at a tertiary care institution between 1993 and 1995 according to an institutional 

protocol. Based on this protocol, women with diabetes underwent ultrasonographic estimates of 

fetal weight between 37 and 38 weeks of gestation. Women whose EFW was greater than or 

equal to 4,250 gm underwent cesarean delivery; those in whom the EFW was estimated at less 

than 4,250 gm but considered LGA (defined as 90th percentile or greater for the gestational age 

in their population) underwent labor induction. We will refer to this group who delivered 

between 1993 and 1995 as the study group. Outcomes for this study group were compared to 

those of a historical control group of diabetic women who delivered between 1990 and 1992, 

prior to the implementation of the new protocol. The study and control groups did not differ 

significantly in terms of their mean maternal age, racial composition, gestational age at delivery, 

or proportion of women with gestational diabetes or pre-gestational diabetes. Twenty-seven 

percent of the patients in the study group did not undergo ultrasound evaluation. 

Maternal outcomes. As shown in Evidence Table 10 (see Appendix F), the authors reported 

that the average gestational age at delivery was similar for the study group and the historical 

control group (39.2 weeks versus 39.3 weeks; p > 0.05).53 The cesarean delivery rate, however, 

was significantly higher in the study group (25.1 percent versus 21.7 percent; p < 0.04) (see 

Appendix F, Evidence Table 11). The authors suggested that the higher proportion of cesarean 
51 

deliveries in the study group could be attributed to the implementation of the new protocol. 

When the elective cesarean deliveries for EFW of 4,250 gm or more (53/343) and cesarean 

deliveries for failed induction for LGA (7/343) were excluded from the study group, there was 

no difference in cesarean delivery rate between groups. 

Neonatal outcomes. There were significantly fewer macrosomic infants (defined as weighing 

4,000 gm or more) in the study group than in the control group (8.9 percent versus 11.6 percent; 

p = 0.04) (see Appendix F, Evidence Table 12). There was a greater likelihood of shoulder 

dystocia in the control group (OR = 1.9, 95 percent CI: 1.0 to 3.5) than in the study group. In a 

subgroup analysis of the macrosomic infants delivered vaginally, there was also a statistically 

significant greater likelihood (OR = 2.9, 95 percent CI: 1.0 to 8.4) of shoulder dystocia in the 

control than in the study group. 

Based on this prospective, observational study, it appears that in women with gestational 

diabetes, a protocol involving elective cesarean delivery for macrosomia and induction at 38 

weeks for LGA may reduce the number of macrosomic infants and the risk of shoulder dystocia, 

but it may also be associated with an increase in the number of cesarean deliveries. However, 

the lack of adjustment for the severity of the diabetes or other potentially confounding variables 

in this study may have resulted in an overestimate of the effect of the protocol on outcomes. 

Furthermore, temporal changes in the management of women with gestational diabetes may have 

also influenced the outcomes reported. 

Relationship of gestational age and fetal weight to the timing of labor induction. We 

identified one cohort study58 that examined the relationship of gestational age and EFW to the 

timing of induction. Lurie et al58 prospectively followed a sample of women and compared 

outcomes with a historical control group in order to determine whether labor induction at 38 to 

39 weeks of gestation might reduce the incidence of shoulder dystocia in women with gestational 

diabetes class A2. The study group (n = 96) was induced at 38 weeks or, if the EFW was greater 

than 4,500 gm, underwent elective cesarean delivery. The study group was compared to a 

historical cohort of women (n = 164) who delivered between 1983 and 1989 and in whom labor 

was induced only if the EFW was greater than 4,000 gm or, if the EFW was greater than 4,500 

gm, underwent elective cesarean delivery. This historical cohort was the same study population 

described by Lurie et al. in an earlier paper,57 which will be discussed subsequently. Gestational 

age was based on the first day of the last menstrual period and serial crown rump measurements 

in the first trimester. Amniocentesis was performed to assess fetal lung maturity, using the L/S 

ratio prior to induction. Baseline participant characteristics, including maternal age and parity, 

were similar between the two groups. There were no reported data on maternal race, weight, or 

glucose control. 

Maternal outcomes. Women in the study group delivered significantly earlier than did 

women in the control group (38.4 weeks versus 39.2 weeks; p < 0.001) (see Appendix F; 

Evidence Table 11). A slightly higher proportion of women in the study group than in the control 

group underwent cesarean delivery, but the difference was not statistically significant (23 percent 

versus 19 percent; p > 0.05). The rates of vacuum-assisted delivery were similar for the two 

groups (5.2 percent versus 5.5 percent; p > 0.05).58

Neonatal outcomes. Neither infant birth weight nor the proportion of macrosomic infants was 

significantly different between the two groups (see Appendix F, Evidence Table 12). The 

proportion of infants with shoulder dystocia was lower in the elective induction group than in the 

historic control group, but the difference did not reach statistical significance (1.4 percent versus 
52 

5.3 percent; p > 0.05). Clavicular fractures, nerve palsies, mortality, and respiratory distress were 

rare events overall, and their incidence was not significantly different between groups. 

Additional analysis. The authors conducted a second analysis in which the outcomes in the 

study group were compared to those in a subset of the historical cohort of women who delivered 

after 40 weeks of gestation (n = 62). The proportion of deliveries complicated by shoulder 

dystocia was significantly reduced (from 10.2 percent to 1.4 percent; p < 0.05) in the study group 

when compared to this subset of the historical control group. Also, only nine percent of the 

infants in the study group had a weight greater than 4,000 gm, as compared to 24 percent in the 

historical control group (p < 0.05). 

In summary, the authors of this paper found that the decrease in shoulder dystocia in the 

study group was only statistically significant if the study group was compared to the subgroup of 

control patients that delivered after 40 weeks. In addition to a lack of adjustment for severity of 

diabetes and a consideration of the temporal changes that had occurred in the management of 

patients with gestational diabetes, this study was further limited by its small population size. 

Impact of gestational age at delivery. In their 1992 paper, Lurie et al57 conducted a 

retrospective chart review of all gestational diabetic women who delivered over a 5-year period, 

examining maternal and neonatal outcomes for women with gestational diabetes class A1 and A2 

who delivered after 40 weeks of gestation or prior to 40 weeks. The groups were matched with 

regard to age, parity, and fetal presentation. Gestational age was based on the date of the last 

menstrual period and ultrasound measurements of crown rump lengths in the first trimester. 

Outcomes were reported separately for gestational diabetes classes A1 and A2. 

Maternal outcomes. Among women with gestational diabetes class A1 (diet-controlled 

gestational diabetes), the mean gestational age at delivery was 40.9 weeks for those who 

delivered after 40 weeks and 38.2 weeks for those who delivered before 40 weeks (p not 

reported). There were no differences in the numbers of vacuum-assisted vaginal deliveries (0/65 

versus 4/65) or cesarean deliveries (7/65 versus 9/65; p = 0.0997) between women delivering 

after 40 weeks of gestation and those delivering prior to 40 weeks of gestation (see Appendix F, 

Evidence Table 11). 

Similar findings were obtained for the women with gestational diabetes class A2 (insulinrequiring gestational diabetes). The mean gestational age at delivery was 40.5 weeks in the group 

delivering after 40 weeks and 37.5 weeks in the group delivering before 40 weeks (p not 

reported). There were no differences in the number of vacuum-assisted deliveries (1/59 versus 

4/59) or cesarean deliveries (15/59 versus 13/59; p = 0.6216). 

Neonatal outcomes. For women with either class A1 or A2 gestational diabetes, the rate of 

macrosomia (defined as birth weight greater than 4,000 gm) was higher in the group of women 

delivering after 40 weeks than in those delivering prior to 40 weeks, but the difference was not 

statistically significant: for gestational diabetes A1, 24.6 percent in the group delivering after 40 

weeks versus 15.4 percent for those delivering before 40 weeks (p = 0.1853); for gestational 

diabetes A2, 20.3 percent in the group delivering after 40 weeks versus 6.8 percent for those 

delivering before 40 weeks (p = 0.057) (see Appendix F, Evidence Table 12). The mean birth 

weights in the two groups were not significantly different in the case of gestational diabetes A1 

patients (3,439.00 gm versus 3,617.85 gm; p = 0.0619). However, infants of gestational diabetes 

A2 patients who delivered after 40 weeks had a significantly higher mean birth weight (3,639 

gm) than did infants born to those who delivered before 40 weeks (3,275 gm) (p = 0.0003). 

There was no significant difference in the rate of shoulder dystocia, birth trauma, neonatal 
53 

metabolic complications, respiratory distress syndrome, or mortality between the two groups in 

either population. 

In this retrospective cohort study, the only significant difference between patients delivering 

after 40 weeks and those delivering before 40 weeks was a higher mean birth weight in the 

subset of class A2 gestational diabetes patients, which was to be expected, given that gestational 

age is a strong predictor of birth weight. The authors concluded that the timing of delivery does 

not have a significant impact on clinically important maternal or neonatal outcomes. However, 

although the authors did perform a stratified analysis for class of gestational diabetes, the study 

did not adjust for other potential confounders or for delivery management in the groups. 

Impact of gestational age and/or EFW on the timing of labor induction and/or elective 

cesarean delivery. Peled59 conducted a protocol-based chart review to evaluate the effect of 

gestational age and EFW on labor management. In this study, the charts of 2,060 patients with 

gestational diabetes treated over a 19-year period were abstracted for maternal and neonatal 

outcomes. The investigators compared four time periods, each with a distinct management 

protocol for the timing of labor induction or elective cesarean delivery, based on EFW and 

gestational age and target thresholds for maternal glycemia (Period A: 1980-1989; Period B: 

1990-1992; Period C: 1993-1995; Period D: 1996-1999). Gestational age was calculated from 

the first day of the last menstrual period and confirmed by first trimester ultrasound when 

possible. EFW was estimated either clinically or by ultrasound. Outcomes among women in 

Period D (the study group) were compared with outcomes among women in the three prior 

periods (historical control groups). Women in the study group were induced at 38 weeks of 

gestation if the EFW was consistent with LGA (defined as greater than 90th percentile) or 

underwent elective cesarean if the EFW was greater than 4,000 gm. In Period A, patients 

underwent elective cesarean if the EFW was greater than 4,500 gm; otherwise, they were 

induced at 42 weeks. In both Periods B and C, patients underwent elective cesarean delivery if 

the EFW was greater than 4,000 gm, and they were induced at 40 weeks if LGA was diagnosed. 

It is noteworthy that the groups differed in terms of the level of glycemic control in the 

institution’s protocol. For patients in Periods C and D, insulin was started at lower fasting 

glucose levels (> 5.3 mmol/L) and 2-hr postprandial levels (> 6.6 mmol/L) than in Periods A and 

B (> 5.8 mmol/L and > 7.8 mmol/L, respectively). Furthermore, patients had lower glycemic 

goals in Periods C and D (< 5.3 mmol/L) than in Period B (< 5.8 mmol/L) or Period A (no goal 

set). Thus, although glycemic control did not alter decisions regarding delivery, it is important to 

keep in mind that patients in the four periods differed in terms of their level of glucose control. 

Prostaglandin E2 gel or tablets was used for labor inductions over the 19-year period of the 

study. The authors also included both class A1 and A2 gestational diabetes patients but did not 

report outcomes separately for the two groups. The proportions of women treated with insulin 

during the four study periods were variable: 13 percent in Period A, 16.4 percent in Period B, 28 

percent in Period C, and 32 percent in Period D. There was no other comparison of baseline 

characteristics (e.g., age, race, parity) in the four groups. 

Maternal outcomes. The mean gestational age at delivery was similar for all four groups 

(between 38 and 39 weeks). The cesarean delivery rate decreased over time, from 21 percent in 

Period A to 18 percent in Period B and 16 percent in Period C, but it increased to 34 percent in 

Period D (see Appendix F, Evidence Table 11). A similar increase in the cesarean delivery rate 

was noted by the author in a concurrent non-gestational diabetes population included in the same 

study.59
54 

Neonatal outcomes. There was a reduction in the proportion of infants with birth weights 

greater than 4,000 gm (3.86 percent in the study group versus 20.6 percent in Period A, 16.3 

percent in Period B, and 11.7 percent in Period C). The proportion of deliveries complicated by 

shoulder dystocia (none in Period D, versus 1.5 percent in Period A, 1.2 percent in Period B, and 

0.6 percent in Period C) also decreased over the study period. Perinatal mortality rates also 

decreased from 8 percent in Period A to 3 percent in Period B, to 0 percent in Period C, and 0.77 

percent in Period D. While p values were reported for comparisons between the gestational 

diabetes population and the non-gestational diabetes population, they were not reported for 

comparisons between time periods (the relevant comparison groups for this analysis). 

Although this study provides data on a large population of patients with gestational diabetes, 

the lack of information on baseline characteristics (e.g., age, race, parity, severity of disease) in 

the four groups and the lack of adjustment for any differences between groups severely limited 

our ability to draw any substantial conclusions from this study. Also, the authors did not adjust 

for or discuss the influence of other potential obstetrical management patterns over the 19-year 

period. Clinical management of diabetic patients had changed substantially over the 19-year 

period of the study. Modifications in practice patterns have likely influenced the outcomes 

reported in these investigations. While examining trends in outcomes is useful, it is not possible 

to fully adjust for changes in practice patterns, leading to some level of bias in the reported 

associations. 

Additional studies. We identified three additional studies that met our initial inclusion 

criteria but which focused on aspects of labor management that are outside our primary area of 

evidence review for Key Question 2. Nevertheless, given the paucity of data addressing labor 

management among women with gestational diabetes, we believe the findings of these studies 

and their relevance to delivery management deserve limited discussion. 

Impact of gestational age on the timing of induction of labor in patients with different 

levels of disease severity. In a retrospective cohort study, Rayburn examined maternal and 

neonatal outcomes under an institutional protocol in which class A2 gestational diabetes patients 

were routinely induced at 38 weeks and class A1 gestational diabetes patients were managed 

expectantly.56 It is important to note that the control group, the gestational diabetes A1 patients 

who were managed expectantly (n = 137), underwent induction if there were any obstetrical 

indications for delivery, including pre-eclampsia, gestational hypertension, or poor glucose 

control; if the cervix was “favorable” at 40 weeks; or if the patient reached 42 weeks of 

gestation. The authors reported that only 53 percent of patients in the control group required 

induction, a rate that was significantly different from that in the study group (90 percent, p < 

0.001). The gestational age at delivery was significantly different between groups (38.1 weeks in 

the study group as compared to 39 weeks in the control group, p < 0.001). The study found no 

differences in the rates of cesarean delivery or shoulder dystocia, macrosomia, respiratory 

difficulties in the neonate, or neonatal intensive care admissions. 

The significant limitation of this investigation is that the study and control groups by 

definition had different severity levels of disease (class A1 versus class A2). There were also 

significant differences in the racial composition (the study group was 70 percent Hispanic, versus 

60 percent in the control group; p < 0.01) and parity in each group (18 percent were nulliparous 

in the study group, versus 31 percent in the control group, p = 0.01).56

Impact of elective cesarean delivery versus a trial of labor in patients with previous 

cesarean delivery. Marchiano conducted a retrospective cohort study to examine outcomes 

related to elective repeat cesarean delivery versus a trial of labor in a population of women with 
55 

gestational diabetes;52 423 women with class A1 gestational diabetes and singleton pregnancy 

who had undergone one previous cesarean delivery were included in the study. 

The repeat cesarean delivery rate was 30 percent for those who attempted a trial of labor. The 

rate of macrosomia (defined as infant birth weight > 4,000 gm) for those who attempted a trial of 

labor was 18 percent, as compared to 33 percent for those who underwent elective cesarean (p < 

0.0001) delivery. A sub-group analysis of women who attempted a trial of labor indicated a 

cesarean delivery rate of 43 percent for those whose infants weighed 4,000 gm or more, as 

compared to 28 percent for those with infants weighing less than 4,000 gm. 

Although these results are relevant to the management of women with gestational diabetes, 

the results are only generalizable to those with prior cesarean delivery. Furthermore, the authors 

used actual infant birth weight rather than EFW in the analysis. Because EFW can vary from 

actual weight at delivery, it is difficult to draw useful conclusions from these results in terms of 

clinical decisionmaking for elective cesarean delivery versus an attempt at vaginal delivery. 

Shoulder dystocia in patients with gestational diabetes. Keller 199154 performed a 

retrospective chart review of 210 patients with gestational diabetes from a tertiary care center in 

Chicago. Of the 210 patients, 173 underwent a trial of labor, 34 had elective repeat cesarean 

delivery, and 3 had an elective cesarean delivery for EFW greater than 4,000 gm (individual 

patient/provider decision). In those who underwent a trial of labor, the rate of cesarean delivery 

was 30.6 percent and the rate of forceps use was 4.6 percent. When birth weight categories were 

examined, the cesarean delivery rate was 33 percent in the greater than 4,500 gm group, 34 

percent in the 4,000 to 4,499 gm group, and 29 percent in the 3,500 to 3,999 gm group. 

The risk of shoulder dystocia in those patients who delivered vaginally was 12.5 percent 

overall and ranged from 9 percent in the lowest birth weight group to 14 percent in those 

weighing 4,000 to 4,499 gm and 38 percent in those infants weighing over 4,500 gm. Fractures 

and nerve injuries were rare (seven total) and were not related to birth weight category. The 

study also reported that the risk of shoulder dystocia in patients with class A1 gestational 

diabetes was not significantly different (OR = 0.78, 95 percent CI: 0.25 to 2.27) from that in 

patients with class A2 gestational diabetes.54 

These findings by Keller offer a descriptive analysis of labor outcomes in women with 

gestational diabetes. Given the lack of a comparison group and any adjustment for confounders, 

as well as the limited sociodemographic and clinical information on the study sample, it is 

difficult to draw any reasonable conclusions from this study regarding labor management in 

women with gestational diabetes. 

Quality assessment. We assessed the quality of the single RCT55 identified for this review 

using the Jadad criteria.22 The study reported pre-specified hypotheses, the inclusion criteria 

were clearly stated, power calculations were presented with effect sizes, the outcomes were 

clearly described, and adjustment was performed for several potential confounders. However, the 

methods for randomization, including sequence generation and assurance of allocation 

concealment, were not clearly described (see Appendix F, Evidence Table 13). 

No observational studies met all of our quality criteria (see Appendix F, Evidence Table 13). 

Of the seven observational studies, only two had pre-specified hypotheses.53 58 Of the eight 

studies, all but one59 reported inclusion and/or exclusion criteria, and sampling was consecutive 

in all eight studies. Outcomes were not clearly defined in two of the studies.56 57 Power 

calculations were only performed in two studies.56 58 The analysis was adjusted for potential 

confounders in two studies.52 56
56 

Limitations. Several limitations to these studies deserve further comment. First, there was 

heterogeneity in the severity of the gestational diabetes reported in the one RCT and four 

primary observational studies, making it difficult to assess the magnitude and direction of any 

association of the effect of gestational age or EFW with labor management. All four of the 

primary observational studies included women with gestational diabetes A1 and gestational 

diabetes A2, but only one reported outcomes stratified by insulin requirement.57 Furthermore, the 

RCT55 and one of the observational studies53 included pre-gestational diabetics, even though this 

condition represented only a small proportion of the sample (less than 10 percent). The results of 

these studies might have varied substantially if the study population had been limited to women 

with gestational diabetes class A1 or A2 or if the outcomes were stratified by severity. 

Second, the four primary observational studies were conducted over a wide timeframe. It is 

difficult to account for the rise in the prevalence of gestational diabetes during this timeframe or 

the modifications in physician practice patterns and obstetrical technology that have certainly 

influenced maternal and neonatal outcomes. For example, while the intention of the study by 

Peled59 was to assess the impact of different management approaches over the 19-year period, it 

was impossible to discern the potential contribution of changes in glycemic target levels to 

delivery management over the four time periods. 

Third, none of the four primary observational studies adjusted for potential confounders. 

Therefore, the magnitude of the associations between gestational age or EFW and outcomes may 

have been overestimated. 

Fourth, the high rates of induction of labor in the expectant management group (49 percent) 

and of cesarean delivery in both groups in the RCT by Kjos et al55 illustrate the low threshold for 

intervention in current practice for patients with diabetes. They also highlight the potential role 

of medical liability in the design of studies of labor management. Physicians’ concerns regarding 

medical liability, provider perception of risk, and maternal demand for cesarean delivery may 

limit the ability to conduct well-designed clinical trials of labor management. 

Conclusions 

One experimental study in this field suggested that active induction of labor at 38 weeks of 

gestation reduces birth weight, macrosomia, and LGA without increasing the rate of cesarean 

section. It was difficult to fully assess these outcomes, however, on the basis of a single clinical 

trial of only 200 patients. The current body of observational studies also suggested a potential 

reduction in macrosomia and shoulder dystocia with elective labor induction and elective 

cesarean delivery for macrosomia or LGA infants. We systematically searched the literature for 

evidence that the choice of timing of induction or elective cesarean delivery resulted in beneficial 

or harmful maternal or neonatal outcomes, as described in detail in the Key Question. Given the 

substantial heterogeneity in the studies reviewed and the serious limitations in study design and 

analysis of the existing literature, we were unable to draw any firm conclusions about the role of 

elective induction or cesarean delivery in the management of gestational diabetes. 

Taking into consideration the quantity, quality, and consistency of the studies comparing the 

effects of labor management on maternal and neonatal outcomes, we graded the strength of 

evidence as very low (see Appendix F, Evidence Table 14). 
57 

Key Question 3 

What risk factors, including but not limited to family history, physical activity, pre-pregnancy 

weight, and gestational weight gain, are associated with short-term and long-term development 

of type 2 diabetes following a pregnancy with gestational diabetes? 

Background and Conceptual Framework 

We conducted our systematic review of this question according to the framework outlined in 

Figure 6. Our objective was to include a range of risk factors that incorporated 

sociodemographics and pre-pregnancy measures as well as antenatal and delivery factors in both 

the immediate and long-term postpartum periods. The risk factors included were based on (1) 

traditional, established epidemiologic and physiologic risk factors for type 2 diabetes and (2) risk 

factors identified in the literature during our initial review of titles and abstracts. 

We identified a number of studies that examined the risk factors for type 2 diabetes among 

women with previous gestational diabetes. These studies varied widely in terms of their design, 

population, measurement of risk factors, and method of analysis. No single study included all the 

risk factors we enumerated. Although longitudinal studies and well-done case-control studies 

that use multiple regression methods provide the best evidence about the independent 

contribution of risk factors, we also included studies that used univariate analytic methods if they 

reported a relative measure of association. 

Based on our conceptual model in Figure 6, we grouped the risk factors into the following 

nine categories: 

1. Anthropometry 

2. Pregnancy-related factors 

3. Postpartum factors 

4. Parity 

5. Family history of type 2 diabetes 

6. Maternal lifestyle factors 

7. Sociodemographics 

8. Oral contraceptive use 

9. Physiologic factors 

Results 

Overview and population characteristics of 16 observational studies of risk factors for 

the development of type 2 diabetes. We identified 16 prospective or retrospective/nonconcurrent cohort studies that evaluated at least one risk factor in our categories (see Appendix 

F, Evidence Table 15). However, none of the studies addressed the lifestyle factors depicted in 

our conceptual model. The studies were conducted in diverse populations and included 10 

studies in North America; three studies were conducted in Asia, two in Europe, and one in 

Australia. Patients were recruited from a hospital or hospital-based clinic in all cases. The 

followup time for the studies ranged from 6 weeks to 12 years (see Appendix F, Evidence Table 

16). 
58 

Figure 6. Conceptual framework for Key Question 3 on risk factors for developing type 2 diabetes following a 

pregnancy with gestational diabetes mellitus 

BMI = body mass index; GDM = gestational diabetes mellitus; hr = hour; OGTT = oral glucose tolerance test; SI = sensitivity 

index; type 2 diabetes = type 2 diabetes mellitus 

GDM 

Type 2 diabetes 

Pregnancy-related factors 

• Gestational age at GDM diagnosis 

• Fasting plasma glucose at time of diagnosis 

• Temporal pattern of hyperglycemia 

o Persistent fasting hyperglycemia 

o Postprandial hyperglycemia 

• Method of glucose control 

o Diet 

o Oral hypoglycemic 

o Insulin requirement 

• Poor glycemic control 

• Prior pregnancies complicated by GDM 

• Spontaneous abortions 

Postpartum factors 

• Preterm 

• Macrosomia 

• Postpartum depression 

• Recurrent GDM 

• Breastfeeding 

Maternal lifestyle 

• High saturated fat diet 

• Physical activity level 

Sociodemographics 

• Age 

• Race 

• Socioeconomic status 

Family history of type 2 diabetes

Parity

Physiologic factors 

• Number of abnormal OGTT results 

• 1-hr plasma glucose 

• Diagnostic OGTT 

• 2-hr glucose 

• Antepartum 30 minutes 

incremental plasma 

• Insulin/glucose ratio 

• Antepartum OGTT 

• Glucose area under the curve 

• Basal glucose production rate 

• Beta cell compensation index 

• Blood pressure 

• Clamp SI 

Anthropometry 

• Height 

• Weight 

• BMI 

• Waist circumference 

• Waist-to-hip ratio 

• Subscapular skinfold thickness 

• Tricep skinfold thickness 

• Weight change 

Oral contraceptive 

• Duration
59 

The studies varied with respect to quality (see Appendix F, Evidence Table 17). All of the 

studies reported inclusion and exclusion criteria, and most stated how the outcome of type 2 

diabetes was defined (93.3 percent). Most reported loss to followup (75 percent), with 75 percent 

of these having a loss to followup of greater than 20 percent. Comparisons between those 

participants who were successfully followed up and those who were lost to followup were 

reported in 33 percent of the studies. Only 50 percent of the studies stated pre-specified 

hypotheses. None of the studies reported power or sample size calculations or the strategy used 

to handle missing data. Studies varied in terms of their reporting of the baseline characteristics of the participants. 

Fifty-six percent of the studies reported the racial makeup of the population, 75 percent reported 

parity status, and all of them reported the ages of the participants (see Appendix F, Evidence 

Table 16). 

Family history of type 2 diabetes. We identified five studies that evaluated family history 

of type 2 diabetes as a risk factor for the development of type 2 diabetes in women with previous 

gestational diabetes (see Appendix F, Evidence Table 18).60-64 The duration of followup for 102 

to 909 participants ranged from 6 weeks to 8 years. All five studies conducted multivariate 

analyses, but only one study reported a relative measure of association.61 Cho et al. reported that 

after adjusting for age, gestational age at diagnosis, pre-pregnancy BMI, FBG at diagnosis, and 

homocysteine level, women with a family history of type 2 diabetes were more likely to develop 

type 2 diabetes than were women without such a history (RR = 1.7; 95 percent CI: 0.6 to 4.6), 

but the relative risk was not statistically significant. Because of the limited data, we were unable 

to draw firm conclusions regarding the magnitude of the association between a family history of 

diabetes and the risk of type 2 diabetes in women with gestational diabetes. 

Sociodemographics. We identified six studies that evaluated a total of four 

sociodemographic factors as risk factors for the development of type 2 diabetes in women with 

previous gestational diabetes (see Appendix F, Evidence Table 19).60-63 65 66 The four 

sociodemographic factors examined were age, race, working status, and hospital. The duration of 

followup for the six samples of 100 to 909 participants ranged from 6 weeks to 11 years. 

Age. Six studies60-63 65 66 assessed age as a risk factor; five of the six studies used multivariate 

analysis.60-63 66 Only one study reported the relative measure of association resulting from the 

multivariate analysis: Cho et al. reported that after adjustment for gestational age at the time of 

diagnosis, pre-pregnancy BMI, family history of type 2 diabetes, FBG at diagnosis, and 

homocysteine level, women greater than 30 years of age had a two-fold increased likelihood of 

developing type 2 diabetes (RR = 2.0; 95 percent CI: 0.68 to 6.0), but this association was not 

statistically significant, as evidenced by the 95 percent CI that included one.61 In one univariate 

analysis, Dacus et al. observed that older age did not appear to be associated with the risk of type 

2 diabetes (RR = 0.68; 95 percent CI: 0.24 to 1.9).65

Hospital location. Cheung et al. were able to evaluate the hospital attended for antenatal 

clinic visits as a risk factor for the development of type 2 diabetes in women with previous 

gestational diabetes, since they had recruited women from two hospitals.60 Although they 

included age, parity, FBG at gestational diabetes diagnosis, BMI during pregnancy, 2-hr OGTT, 

number of prior gestational diabetes pregnancies, method of glucose control, and family history 

of type 2 diabetes, these investigators did not report a relative measure of association for the 

hospital attended and type of diabetes. 

Work status. Cho et al. evaluated working status as a risk factor for the development of type 

2 diabetes in eight multivariate models, including age, parity, family history of type 2 diabetes, 
60 

working status, blood pressure, lipid profile, and one of eight measures of adiposity (postpartum 

BMI, waist circumference, weight, subscapular skin fold thickness, suprailiac skin fold 

thickness, tricep skin fold thickness, body fat weight, or waist-to-hip ratio).62 However, the 

relative measure of association was not reported for the association between working status and 

development of type 2 diabetes for any of the eight models. 

Race. In a univariate analysis, Dacus et al. evaluated race as a risk factor for the development 

of type 2 diabetes in women with previous gestational diabetes. They reported that as compared 

to other race groups, blacks had a 50 percent increased risk of developing type 2 diabetes, but 

this association was not statistically significant (RR = 1.5; 95 percent CI: 0.45 to 5.0).65

We concluded that there are only limited data on which to base any meaningful conclusions 

regarding sociodemographic factors and the short- or long-term risk of type 2 diabetes among 

women with gestational diabetes. 

Maternal lifestyle factors. We did not identify any studies that examined the relationship 

between lifestyle factors, such as physical activity and diet, and the development of type 2 

diabetes in women with prior gestational diabetes. We therefore concluded that no evidence 

exists to determine whether maternal lifestyle affects the risk of developing type 2 diabetes after 

having gestational diabetes. 

Parity. We identified four studies that evaluated parity as a risk factor for the development of 

type 2 diabetes in women with previous gestational diabetes (see Appendix F, Evidence Table 

20).60 62 66 67 The duration of followup for the samples of 102 to 909 participants ranged from 6 

weeks to 11 years. All four studies conducted multivariate analyses, but only two studies 

reported a relative measure of association for parity with type 2 diabetes.66 67 After adjustment 

for GAD and insulinoma antigen-2 (IA-2) antibody status, method of glucose control, BMI, age, 

and serum C-reactive protein (CRP) at 9 months, Lobner et al. found that compared to 

gestational diabetics who were nulliparous, gestational diabetics with more than two previous 

births had an almost three-fold increased risk of developing type 2 diabetes (relative hazard [RH] 

= 2.5; 95 percent CI: 1.1 to 5.3).66 There was a 20 percent increased risk of developing type 2 

diabetes associated with having had one to two previous births, as compared to nulliparity, but 

this association was not statistically significant (RH = 1.2; 95 percent CI: 0.8 to 1.7).66 Metzger 

et al. evaluated parity as a continuous variable and reported that for each unit increase in parity, 

there was no statistically significant change in the log odds of developing type 2 diabetes (β = 

0.19; p = 0.09).67 We concluded that higher parity may be associated with an increased risk for 

type 2 diabetes among women with gestational diabetes, but further evidence is needed to draw 

firm conclusions regarding this potential association. 

Pregnancy-related factors. We identified nine studies that evaluated seven pregnancyrelated factors as risk factors for the development of type 2 diabetes in women with previous 

gestational diabetes (see Appendix F, Evidence Table 21).60 61 63 65 66 68-71 These factors were: 

gestational age at diagnosis, method of glucose control, dosage of bedtime intermediate-acting 

insulin required, class A2 gestational diabetes (defined as any FBG ≥ 105 mg/dL), previous 

gestational diabetes, number of prior gestational diabetes pregnancies, 50-gm glucose challenge 

test (GCT), and spontaneous abortions. The duration of followup for the 88 to 1,636 participants 

ranged from 6 weeks to 12 years. 

Gestational age at diagnosis of gestational diabetes. Five studies61 63 65 68 70 assessed 

gestational age at diagnosis of gestational diabetes as a risk factor, and four of the five studies 

used multivariate analysis.61 63 68 70 The studies varied in terms of their categorization of 

gestational age at gestational diabetes diagnosis: Two studies divided gestational age at 
61 

gestational diabetes diagnosis into quartiles and used the first quartile as the reference:68 70 Both 

Kjos et al.68 and Schaefer-Graf et al.70 reported a protective effect of gestational age at 

gestational diabetes diagnosis in the fourth quartile as compared to gestational age at gestational 

diabetes diagnosis in the first quartile, with the effect ranging from a 52 percent to a 65 percent 

reduction in the likelihood of developing type 2 diabetes (RH = 0.48; 95 percent CI: 0.29 to 0.82; 

and OR = 0.35; 95 percent CI: 0.23 to 0.54) respectively. Both studies varied with respect to the 

covariates included in the multivariate model, and they did not share any common covariates. 

Schaefer-Graf et al.70 included FBG at gestational diabetes diagnosis, class A2 gestational 

diabetes, area under the glucose curve of pregnancy OGTT, previous gestational diabetes and 50-

gm GCT, while Kjos et al.68 included postpartum OGTT glucose area under the curve, 

antepartum OGTT glucose area under the curve, and highest antepartum FBG. When thirdquartile gestational age at gestational diabetes diagnosis was compared to the first quartile, a 

smaller protective effect was observed in both studies. Schaefer-Graf et al. reported a 55 percent 

reduction in the likelihood of developing type 2 diabetes (OR = 0.45; 95 percent CI: 0.27 to 

0.76).70 Kjos et al. reported a 27 percent reduction in the likelihood of developing diabetes, but 

this association was not statistically significant (RH = 0.73; 95 percent CI: 0.45 to 1.2).68 For 

both studies, when second-quartile gestational age at gestational diabetes diagnosis was 

compared to the first quartile, no significant difference in the development of type 2 diabetes was 

found (Schaefer-Graf et al., OR = 1.1; 95 percent CI: 0.72 to 1.7; and Kjos et al., RH = 0.66; 95 

percent CI: 0.39 – 1.1). 

Cho et al. categorized gestational age at gestational diabetes diagnosis into two groups, 

women who were diagnosed with gestational diabetes at greater than or equal to 26 weeks and 

women who were diagnosed at less than 26 weeks. There was no significant difference in the 

development of type 2 diabetes between the two groups after adjusting for age, pre-pregnancy 

BMI, family history of type 2 diabetes, FBG at diagnosis, and homocysteine level (RR = 2.4; 95 

percent CI: 0.88 to 6.6).61 

Jang et al. assessed gestational age at gestational diabetes diagnosis as a continuous variable 

and found that for each week of increase in gestational age at gestational diabetes diagnosis, 

there was a 0.01 decrease in the log odds of developing type 2 diabetes (β = -0.01; SE = 0.05; p = 

0.008).63 

In a univariate analysis, Dacus et al. categorized gestational age at gestational diabetes 

diagnosis into two groups, comparing women who were diagnosed with gestational diabetes at 

less than 24 weeks and those diagnosed with gestational diabetes greater than or equal to 24 

weeks. No significant difference was observed between the two groups in terms of the 

development of type 2 diabetes (RR = 2.5; 95 percent CI: 0.9 to 6.9).65 

Method of glucose control. Five studies evaluated the method of glucose control during 

pregnancy as a risk factor for the development of type 2 diabetes.60 65 66 69 71 Three of these 

studies60 66 69 included a multivariate analysis, but only two of them60 66 reported a relative 

measure of association for this risk factor. These two studies varied considerably. Cheung et al. 

found that as compared to women who did not use insulin, those that did use insulin during 

pregnancy had a three-fold higher risk of developing type 2 diabetes after adjusting for age, 

parity, FBG at diagnosis, BMI at index pregnancy, 2-hr OGTT, number of prior pregnancies 

complicated by gestational diabetes, family history of type 2 diabetes, and hospital location (RR 

= 3.2; 95 percent CI: 1.6 to 7.0).60 Lobner et al. reported that as compared to women who were 

diet-controlled, women who received insulin during pregnancy had an almost five-fold increased 

risk of developing type 2 diabetes after adjustment for age, parity, GAD and IA-2 antibody 
62 

status, BMI during pregnancy, and serum CRP (RH = 4.7; 95 percent CI: 3.2 to 7.1; p < 

0.0001).66 

Two studies included a univariate analysis, but only Steinhart et al. reported a relative 

measure of association for the method of glucose control. This study reported an almost threefold increased likelihood of developing type 2 diabetes in women requiring insulin as compared 

to those not on insulin, but this association was not statistically significant (OR = 2.8; 95 percent 

CI: 0.8 to 11.2).71 

One study by Cheung et al. examined the required dosage of bedtime intermediate-acting 

insulin as a risk factor. For each unit (unspecified) increase in dosage, there was a 9 percent 

increased likelihood of developing type 2 diabetes after adjustment for FBG (RR = 1.1; 95 

percent CI: 1.0 to 1.2).60 The clinical relevance of this finding, however, is unclear, given that it 

is based on data from one study and is of borderline statistical significance. 

50-gm GCT. The 50-gm GCT is routinely performed during pregnancy as the baseline 

screening test for gestational diabetes. Only one study evaluated the results of the 50-gm GCT 

performed during pregnancy as a risk factor for the development of type 2 diabetes.70 SchaeferGraf et al. categorized the GCT results into quartiles, using the first quartile as the reference. 

They reported that as compared to women with 50-gm GCT results in the first quartile, women 

with results in the second, third, and fourth quartiles had an increasingly higher risk of 

developing type 2 diabetes (OR = 2.9; 95 percent CI: 1.2 to 6.6; OR = 3.8; 95 percent CI: 1.7 to 

8.5; and OR = 3.5; 95 percent CI: 1.6 to 7.6 for the second, third, and fourth quartiles, 

respectively), after adjusting for FBG at diagnosis, class A2 gestational diabetes, area under the 

glucose challenge curve of pregnancy OGTT, gestational age at diagnosis of gestational diabetes, 

and previous pregnancy complicated by gestational diabetes. 

Class A-2 (insulin-requiring gestational diabetes). One study evaluated class A2 gestational 

diabetes, defined as requiring insulin therapy because of FBG levels greater than or equal to 105 

mg/dL, as a risk factor for the development of type 2 diabetes.70 Schaefer-Graf et al. reported 

that as compared to women with gestational diabetes class A1, women with gestational diabetes 

class A2 were 2.4 times more likely to develop type 2 diabetes, after adjusting for FBG at 

diagnosis, 50-gm GCT, area under the curve for a pregnancy OGTT, gestational age at diagnosis 

of gestational diabetes, and previous pregnancy complicated by gestational diabetes (OR = 2.4; 

95 percent CI: 1.2 to 4.7). 

Previous pregnancies complicated by gestational diabetes. Two studies evaluated previous 

pregnancies complicated by gestational diabetes as a risk factor for the development of type 2 

diabetes.60 70 These studies included multivariate analysis, but only one study reported a relative 

measure of association for this risk factor.70 Schaefer-Graf et al. reported that as compared to 

women without a previous pregnancy complicated by gestational diabetes, those with a such a 

pregnancy were 60 percent more likely to develop type 2 diabetes, after adjusting for FBG at 

diagnosis, 50-gm GCT, area under the glucose challenge curve of pregnancy OGTT, gestational 

age at gestational diabetes diagnosis, and previous pregnancy complicated by gestational 

diabetes (OR = 1.6; 95 percent CI: 1.1 to 2.5). 

Spontaneous abortion. One study that included a univariate analysis examined spontaneous 

abortion as a risk factor for the development of type 2 diabetes in women with previous 

gestational diabetes.71 Steinhart et al. reported that as compared to women without spontaneous 

abortions, those with spontaneous abortions were 36 percent more likely to develop type 2 

diabetes, but this association was not statistically significant (OR = 1.4; 95 percent CI: 0.5 to 

3.5). 
63 

We concluded that the overall grade of evidence for pregnancy-related factors was moderate. 

Postpartum factors. We identified five studies that evaluated a total of four postpartum 

factors as risk factors for the development of type 2 diabetes in women with previous gestational 

diabetes (see Appendix F, Evidence Table 22).62 64 69 71 72 The four postpartum factors examined 

were additional pregnancy, breastfeeding, duration of followup, and recurrent gestational 

diabetes. Duration of followup for the 88 to 909 participants ranged from 6 weeks to 12 years. 

Additional pregnancy. Two studies assessed additional pregnancy as a risk factor for the 

development of type 2 diabetes in women with previous gestational diabetes, and both used 

multivariate analysis.69 72 However, only one study reported a relative measure of association for 

this risk factor.72 After adjusting for postpartum weight change (per 10 pounds), OGTT glucose 

area, postpartum BMI, and breastfeeding, Peters et al. found that as compared to women with no 

additional pregnancy, those with an additional pregnancy had a three-fold increased risk of 

developing type 2 diabetes (RH = 3.3; 95 percent CI: 1.8 to 6.2).72

Breastfeeding. Two studies assessed breastfeeding as a risk factor for the development of 

type 2 diabetes, and both constructed multivariate models.64 72 However, neither of these studies 

reported relative measures of association for this risk factor. 

Duration of followup. One study evaluated the duration of followup as a risk factor for the 

development of type 2 diabetes in women with previous gestational diabetes and constructed 

eight multivariate models, involving age, parity, family history of type 2 diabetes, working 

status, blood pressure, lipid profile, and one of eight measures of adiposity (postpartum BMI, 

waist circumference, weight, subscapular skin fold thickness, suprailiac skin fold thickness, 

tricep skin fold thickness, body fat weight, or waist-to-hip ratio).62 However, the relative 

measure of association was not reported for the association between duration of followup and 

development of type 2 diabetes for any of the eight models. 

Recurrent gestational diabetes. One study evaluated recurrent gestational diabetes as a risk 

factor for the development of type 2 diabetes in women with previous gestational diabetes and 

conducted a univariate analysis.71 Steinhart et al. reported that as compared to women without 

recurrent gestational diabetes, those with recurrent gestational diabetes had a 24-fold increased 

risk of developing type 2 diabetes (OR = 24.8; 95 percent CI: 3.0 to 1132.2). The width of this 

confidence interval, however, suggests substantial variability in the point estimate and makes it 

impossible for us to draw any firm conclusions from these data. 

We concluded that the overall grade of the evidence for postpartum factors was very low. 

Measures of anthropometry. We identified 11 cohort studies that evaluated a total of 11 

different anthropometric measures: weight, height, BMI, body fat weight, subscapular skin fold 

thickness, suprailiac skin fold thickness, tricep skin fold thickness, waist circumference, waistto-hip ratio, percent ideal body weight, and weight change (see Appendix F, Evidence Table 

23).60-67 69 72 73 The number of participants ranged from 17061 to 909.62 Followup of participants 

ranged from 6 weeks to 12 years. Of the 11 studies, 9 reported a relative measure of 

association.60-63 65-67 72 73 Eight studies 60-63 66 67 72 73 reported an adjusted relative measure of 

association. We have included these adjusted relative measures in Figure 7. One study reported 

an unadjusted relative measure from a univariate model.65 The studies varied in terms of the time 

period in which the assessment of anthropometry was conducted. 

Of the 11 studies, three used pre-pregnancy measures of obesity.61 63 73 Two of these studies 

reported a significant positive association between pre-pregnancy anthropometric measures and 

the development of type 2 diabetes.63 73 One study reported a protective effect of a higher 

anthropometric measure,61 and one study did not report the measure of association.63 Pallardo et 
64 

al. found that as compared to women with a pre-pregnancy BMI less than or equal to 27 kg/m2

, 

women with a BMI greater than 27 kg/m2

 had an eight-fold increased risk of developing type 2 

diabetes, after adjusting for the number of abnormal glucose results from the OGTT and Cpeptide glucose score (OR = 8.7; 95 percent CI: 2.3 to 32.9).73 Jang et al. reported that for every 

1-kg increase in pre-pregnancy weight, there was a 0.36 increase in the log odds of developing 

type 2 diabetes, although this relationship was not statistically significant (β = 0.36, SE = 0.10).63

One study61 reported a reduction in the likelihood of type 2 diabetes with higher BMI: Cho et 

al.61 reported that as compared to women with a pre-pregnancy BMI less than or equal to 23 

kg/m2

, women with a pre-pregnancy BMI greater than 23 kg/m2 were less likely (RR = 0.78; 95 

percent CI: 0.27 to 2.2) to develop type 2 diabetes, after adjusting for age, gestational age at 

diagnosis of gestational diabetes, family history of type 2 diabetes, FBG at diagnosis, and 

homocysteine level. This reported association, however, was not statistically significant. We 

concluded that pre-pregnancy measures of obesity are associated with an increased likelihood of 

type 2 diabetes. 

Three of the 11 studies used anthropometric measures during pregnancy. These studies 

reported a positive association between anthropometric measures and the development of type 2 

diabetes.60 66 67 For example, Lobner et al. reported that women with a BMI greater than 30 kg/m2

were 50 percent more likely to develop type 2 diabetes than were women with a BMI less than 

30 kg/m2, after adjusting for GAD and IA-2 antibody status, method of glucose control, parity, 

age, and serum CRP at 9 months (RH = 1.5; 95 percent CI: 1.0 to 2.2).66 In addition, Metzger et 

al. reported that as compared to women who were non-obese (<120 percent ideal body weight), 

women who were obese (≥ 120 percent ideal body weight) had an almost three-fold increased 

likelihood of developing type 2 diabetes, after adjusting for 3-hr integrated insulin level and 

parity.67 For each kg/m2 increase in BMI, Cheung et al. reported a 10 percent increase in the risk 

of developing type 2 diabetes (relative risk [RR] = 1.1; 95 percent CI: 1.0 to 1.2), after adjusting 

for age, parity, FBG at diagnosis, 2-hr OGTT, the number of prior pregnancies complicated by 

gestational diabetes, method of glucose control, family history of type 2 diabetes, and hospital 

location.60

Five studies62-65 72evaluated anthropometric measures assessed during the postpartum period, 

but only four studies62 64 65 72 reported a relative measure of association. As shown in Figure 7, 

Cho et al. assessed eight anthropometric measures, comparing women in the highest quartile to 

those in the lowest quartile.62 Each of the eight measures was positively associated with the 

development of type 2 diabetes, after adjusting for age, duration of followup, parity, family 

history of type 2 diabetes, working status, blood pressure, and lipid profile, including 

triglycerides, high-density lipoprotein (HDL) cholesterol, and low-density lipoprotein (LDL) 

cholesterol. As compared to women in the lowest quartile of postpartum BMI and weight, 

women in the highest quartile had a three-fold increased likelihood (OR = 3.3; 95 percent CI: 1.7 

to 6.5 and OR = 3.1; 95 percent CI: 1.6 to 6.0, respectively) of developing type 2 diabetes. In the 

same sample, Cho et al. reported that women in the highest quartile were 3.8 times more likely to 

develop type 2 diabetes (OR = 3.8; 95 percent CI: 1.8 to 7.6) than were women in the lowest 

quartile of body fat weight. The direction and magnitude of the association with type 2 diabetes 

were similar across several additional anthropometric measures. As compared to women in the 

lowest quartile, women in the highest quartile of (1) subscapular skin fold thickness, (2) 

suprailiac skin fold thickness, and (3) tricep skin fold thickness had a 2.0- to 2.8-fold higher 

likelihood of developing type 2 diabetes. Women in the highest quartile were over two times 
65 

3.0

RH = 2.0

RR = 4.1

OR = 3.1

OR = 3.9

OR = 2.0

OR = 2.1

OR = 2.8

OR = 3.8

OR = 3.1

OR = 3.3

RR = 1.1

RH = 1.5

RR = 0.8

OR = 1.4

OR = 8.7

0.1 1 10 100

Figure 7. Summary of reported measures of association between anthropometric measures and the risk of 

developing type 2 diabetes following a pregnancy with gestational diabetes mellitus 

Pre-pregnancy measures 

Pallardo, 199973 (BMI>27 kg/m2

 versus ≤27) 

Jang, 200363 (Weight: 1-kg increase) 

Cho, 200561 (BMI>23 kg/m2 versus ≤23) 

Measures during pregnancy 

Lobner, 200666 (BMI>30 kg/m2

 versus ≤30) 

Metzger, 199367 (PIBW≥120 versus <120) 

Cheung, 200660 (BMI: 1-kg/m2 increase) 

Postpartum measures 

Cho, 200662 (Q4 versus Q1 BMI)* 

Cho, 200662 (Q4 versus Q1 weight)* 

Cho, 200662 (Q4 versus Q1 body fat 

weight)* 

Cho, 200662 (Q4 versus Q1 subscapular 

skin fold thickness)* 

Cho, 200662 (Q4 versus Q1 suprailiac skin 

fold thickness)* 

Cho, 200662 (Q4 versus Q1 tricep skin fold 

thickness)* 

Cho, 200662 (Q4 versus Q1 waist 

circumference)* 

Cho, 200662 (Q4 versus Q1 waist-to-hip 

ratio)* 

Dacus, 199465 (BMI>27 kg/m2 versus ≤27) 

Time-dependent covariates 

Peters, 199672 (10-pound change in 

postpartum weight) 

* Comparison is between the highest and the lowest quartile. 

BMI = body mass index; kg = kilograms; m = meters; OR = odds ratio; PIBW = percent of ideal body weight; Q = quartile; RH = 

relative hazard; RR = relative risk 

more likely to develop type 2 diabetes (OR = 2.8; 95 percent CI: 1.4 to 5.6; OR = 2.1; 95 percent 

CI: 1.2 to 3.7; and OR = 2.0; 95 percent CI: 1.1 to 3.6, respectively). Also, Cho et al. reported 

that as compared to women in the lowest quartile of waist circumference and waist-to-hip ratio, 

women in the highest quartile were over three times as likely to develop type 2 diabetes (OR = 

3.9; 95 percent CI: 1.8 to 8.2 and OR = 3.1; 95 percent CI: 1.7 to 5.6, respectively). Two 

additional studies (Peters et al. and Xiang et al.) assessed postpartum BMI64 72 and postpartum 

weight64 in multivariate models but did not report the measure of association. In an unadjusted 

analysis, Dacus et al. reported a four-fold increased risk (RR = 4.1; 95 percent CI: 0.6 – 29.8) in 
66 

the development of type 2 diabetes in women with a BMI of 27 kg/m2

 or greater as compared to 

women with a BMI of less than 27 kg/m2

, but this difference was not statistically significant.65 

Three studies evaluated anthropometric measures as time-dependent covariates, assessing the 

association of the change in these measures between delivery and followup with type 2 

diabetes.64 69 72 Peters et al. showed that for every 10-pound change in weight, there was a 95 

percent increase in the risk of developing type 2 diabetes, after adjusting for additional 

pregnancy, OGTT glucose area, postpartum BMI, and breastfeeding (RH = 2.0; 95 percent CI: 

1.6 to 2.3).72 Although Kjos et al. and Xiang et al. included weight change in their multivariate 

analyses, the relative association of weight change with type 2 diabetes was not reported.64 69

Height was examined in one study, but the measure of association from the multivariate model 

was not reported.63 Because of multiple cohort studies and measures of association, we graded 

the overall evidence for anthropometric measures as moderate. 

Oral contraceptive use. Two studies evaluated oral contraceptive use and the risk of type 2 

diabetes in women with a prior history of gestational diabetes (see Appendix F, Evidence Table 

24).64 69 Kjos et al. found that as compared to women using a combination oral contraceptive pill, 

those using a progestin-only pill had a greater than two-fold increased risk of developing type 2 

diabetes, following adjustment for the area under the postpartum glucose tolerance test curve, 

prior oral contraceptive use, method of glucose control, completion of a second pregnancy, 

postpartum weight loss, and duration of oral contraceptive use (RH = 2.9; 95 percent CI: 1.6 to 

5.3).69 In that same study, duration of oral contraceptive use was also a significant predictor of 

type 2 diabetes risk. Women using oral contraceptives for 4 to 8 months and more than 8 months 

had, respectively, a three-fold (RH = 3.0; 95 percent CI: 1.4 to 6.5) and nearly five-fold (RH = 

4.9; 95 percent CI: 1.8 to 13.7) increased risk of developing type 2 diabetes when compared to 

those with lower-duration use, following multivariable adjustment for the same variables.69 

Xiang et al. did not find that progesterone-based contraceptives were consistently associated 

with an increased risk of type 2 diabetes. As compared to women who used combination oral 

contraceptives, those using depo-medroxyprogesterone acetate did not have an increased risk of 

type 2 diabetes in the entire cohort, after adjusting for postpartum BMI, breastfeeding, family 

history of type 2 diabetes, HDL cholesterol, triglycerides, and weight gain during followup (RH 

= 1.1; 95 percent CI: 0.6 to 1.9).64 This association did not differ by breastfeeding status.64

However, after adjusting for postpartum BMI, family history of type 2 diabetes, breastfeeding, 

HDL cholesterol, and weight gain during followup, use of depo-medroxyprogesterone acetate in 

women with triglycerides above the median of the population was associated with a two-fold 

greater risk of developing type 2 diabetes when compared to the use of a combination oral 

contraceptive and triglyceride levels below the population median (RH = 2.3; 95 percent CI: 1.1 

to 4.8).64 We concluded that the limited number of studies available and the overall very low 

grade of evidence made it difficult to draw any firm conclusions regarding the relationship 

between progestin-only contraception and the development of type 2 diabetes among women 

with gestational diabetes. 

Metabolic risk factors.

FBG: antepartum. Five studies examined antepartum FBG at gestational diabetes diagnosis 

as a risk factor, and in all of these studies, FBG was a significant predictor of type 2 diabetes (see 

Figure 8 and Appendix F, Evidence Table 25).60 61 68 70 71 Cheung et al. found that each increasing 

mmol/L increment in FBG was associated with a 37 percent increase in the risk of type 2 

diabetes, after adjustment for the dose of bedtime intermediate-acting insulin (RR = 1.4; 95 

percent CI: 1.1 to 1.7).60 In that same study, FBG at diagnosis was associated with a 1.5-fold 
67 

OR = 15

OR = 3.64

RH = 2.13

RR = 1.3

OR = 1.03

OR = 1.02

RH = 2.47

OR = 21.0

RR = 4.00

OR = 11.1

RR = 1.37

RR = 1.5

1 10 100 1000

Figure 8. Summary of selected reported measures of association between measures of metabolic risk factors 

and the risk of developing type 2 diabetes following a pregnancy with gestational diabetes mellitus 

FBG at antepartum 

Cheung, 200660 (FBG – 1 mmol/L increase) 

Cheung, 200660 (FBG at diagnosis – 1 

mmol/L increase) 

Steinhart, 199771 (fasting blood sugar >5.83 

mmol/L vs. ≤5.83) 

Cho, 200561 (FBG at diagnosis >5.3 mmol/L 

vs. ≤5.3) 

Schaefer-Graf, 200270 (Q4 vs. Q1 FBG at 

diagnosis) 

Kjos, 199568 (Q4 vs. Q1 FBG at diagnosis) 

2-hr glucose during diagnostic OGTT 

Jang, 200263 (mmol/L increase) 

Metzger, 199367 (mmol/L increase) 

Cheung, 200660 (mmol/L increase) 

Antepartum OGTT glucose area under the 

curve 

Kjos, 199568 (Q4 vs. Q1 mmol/L/min) 

Schaefer-Graf, 200270 (Q4 vs. Q1 

gm*min/dL) 

Buchanan, 199974 (T3 vs. T1 min/mol/L) 

dL = deciliter; FBG = fasting blood glucose; gm = gram; hr = hour; L = liter; min = minute; mmol = millimole; OGTT = oral 

glucose tolerance test; Q = quartile; T = tertile 

increased risk of type 2 diabetes, after adjusting for age, parity, BMI at the index pregnancy, 2-hr 

OGTT result, number of prior pregnancies, method of glucose control, family history of type 2 

diabetes, and hospital (RR = 1.5; 95 percent CI: 1.3 to 1.9).60 

In unadjusted analyses, Steinhart et al. found that as compared to women with an FBG less 

than or equal to 5.83 mmol/L, those with an FBG greater than 5.83 mmol/L had an 11-fold 

increased risk of developing type 2 diabetes (OR = 11.1; 95 percent CI: 2.3 to 103.4).71 Cho et al. 

found that women with an FBG greater than 5.3 mmol/L had a four-fold increased risk of 

developing type 2 diabetes, after adjusting for age, gestational age at gestational diabetes 

diagnosis, pre-pregnancy BMI, family history of type 2 diabetes, and homocysteine level (RR = 

4.0; 95 percent CI: 1.4 to 11.4).61 In another study, Schaefer-Graf et al. found an increased risk 

of type 2 diabetes with increasing quartiles of FBG, such that women in the highest quartile had 

a 21-fold increased risk of developing type 2 diabetes when compared to those in the lowest 

quartile (OR = 21.0; 95 percent CI: 4.6 to 96.3).70 Finally, Kjos et al. also found an increased risk 

of type 2 diabetes with increasing tertiles of FBG, with women in the highest tertile having a 
68 

greater than two-fold increased risk when compared to those in the lowest tertile, after adjusting 

for postpartum OGTT glucose area under the curve, gestational age at gestational diabetes 

diagnosis, and antepartum OGTT glucose area under the curve (RH = 2.5; 95 percent CI: 1.3 to 

4.9).68 

Characteristics of the OGTT. 

Antepartum OGTT results.

Number of abnormal OGTT results. One study examined the number of abnormal OGTT 

results as a risk factor for subsequent development of type 2 diabetes.73 In this study, there was a 

three-fold increased risk of type 2 diabetes with each increase in the number of abnormal OGTT 

results, after adjusting for pre-pregnancy BMI and C-peptide glucose score (OR = 3.0; 95 percent 

CI: 1.4 to 6.4).73 

Glucose tolerance test total. One study examined the OGTT total as a risk factor for type 2 

diabetes. As compared to women with OGTT totals less than or equal to 41.63 mmol/L, those 

with a GTT total greater than 41.63 mmol/L had a 15-fold greater risk of developing type 2 

diabetes (OR = 15.5; 95 percent CI: 2 to 678).71

1-hr glucose during the diagnostic OGTT. One study examined the 1-hr glucose level during 

the diagnostic OGTT as a risk factor for the development of type 2 diabetes.74 Buchanan et al. 

found that as compared to women with the lowest tertile of 1-hr plasma glucose during the 

diagnostic OGTT, women in the highest tertile had a 15-fold greater risk of developing type 2 

diabetes, after adjusting for beta-cell compensation index and basal production rate (OR = 15.2; 

95 percent CI: 1.4 to 166.3), and a 22-fold higher risk of developing type 2 diabetes, after 

adjusting for the OGTT 30-min incremental insulin:glucose ratio, basal glucose production rate, 

and insulin sensitivity index (OR = 22; 95 percent CI: 1.5 to 328.5).74 

2-hr glucose during the diagnostic OGTT. Three studies evaluated the 2-hr glucose level 

during the OGTT as a risk factor for subsequent development of type 2 diabetes and found it to 

be a significant predictor in multivariate analyses (see Figure 8).60 63 67 Jang et al. found that for 

every 1-point increase in 2-hr glucose level, there was a 2 percent increased risk of developing 

type 2 diabetes (OR = 1.02; 95 percent CI: 1.00 to 1.03; p = 0.04), after adjusting for prepregnancy weight, gestational age at gestational diabetes diagnosis, 3-hour insulin level on the 

diagnostic OGTT, age, height, pre-pregnancy BMI, family history of type 2 diabetes, and 

postpartum weight.63 Metzger et al. found a similar association after adjusting for 30-minute 

stimulated insulin secretion on the OGTT and basal insulin (OR = 1.03; 95 percent CI: 1.01 to 

1.04).67 Cheung et al. found a stronger association, in that there was a 30 percent increased risk 

of developing type 2 diabetes for each 1-point increase in the 2-hr glucose level during the 

OGTT, after adjusting for age, parity, FBG at gestational diabetes diagnosis, BMI at the index 

pregnancy, number of prior gestational diabetic pregnancies, method of glucose control during 

the index pregnancy, family history of type 2 diabetes, and hospital (RR = 1.3; 95 percent CI: 1.1 

to 1.4).60

3-hr insulin level during the diagnostic OGTT. One study63 examined 3-hr insulin levels and 

found an inverse association between the insulin level and the risk of developing type 2 diabetes, 

after adjusting for pre-pregnancy weight, gestational age at gestational diabetes diagnosis, 2-hr 

glucose level, age, height, pre-pregnancy BMI, family history of type 2 diabetes, and weight at 

postpartum testing. A second study measured 3-hr integrated insulin levels and found no 

association with the development of type 2 diabetes. 

30-minute incremental insulin:glucose ratio. Two studies examined the 30-min incremental 

insulin:glucose ratio from the antepartum OGTT.74 75 Both studies found it to be a predictor of 
69 

type 2 diabetes. One study showed a non-significant 90 percent lower risk of type 2 diabetes in 

the highest versus the lowest tertile, after adjusting for incremental glucose area, diagnostic 

OGTT, frequently sampled intravenous glucose tolerance acute insulin response, basal glucose 

production rate, and insulin sensitivity index (OR = 0.1; 95 percent CI: 0.01 to 2.2), and a 92 

percent lower risk after adjusting for 1-hr plasma glucose level during the diagnostic OGTT, 

basal glucose production rate, and insulin sensitivity index (OR = 0.08; 95 percent CI; 0.01 to 

1.1).74 

Antepartum OGTT glucose area under the curve. Five studies examined the antepartum 

OGTT glucose area under the curve and the subsequent risk of type 2 diabetes (see Figure 

8).68 70 72 74 75 Kjos et al. found a graded association between the glucose area under the curve and 

the risk of type 2 diabetes. As compared to those in the lowest quartile, those in the highest 

quartile had a two-fold increased risk, after adjusting for postpartum OGTT glucose area under 

the curve, gestational age at gestational diabetes diagnosis, and highest antepartum fasting 

glucose (RH = 2.1; 95 percent CI: 1.2 to 3.9).68 Similarly, Schaefer-Graf et al. found that women 

in the highest quartile of glucose area under the curve had a significantly increased risk of type 2 

diabetes when compared to those in the lowest quartile, after adjusting for FBG at diagnosis, 

diabetes pregnancy class, gestational age at gestational diabetes diagnosis, previous gestational 

diabetes, and results of the 50-gm GCT (OR = 3.6; 95 percent CI: 1.9 to 6.8).70 Buchanan et al. 

also found that the OGTT glucose area under the curve was a significant predictor of type 2 

diabetes, after adjusting for the antepartum 30-min incremental plasma insulin:glucose ratio.75 In 

another study, they also found that women in the highest tertile of incremental area under the 

glucose curve had a 15-fold increased risk of type 2 diabetes when compared to women in the 

lowest tertile, after adjusting for frequently sampled intravenous glucose tolerance acute insulin 

response, OGTT 30-min incremental insulin:glucose ratio, basal glucose production rate, and 

insulin sensitivity index (OR = 15; 95 percent CI: 1.1 to 207.9).74 

We concluded that increasing FBS or 2-hr glucose values on the diagnostic OGTT may 

indicate a higher likelihood of development of type 2 diabetes in women with gestational 

diabetes. 

Postpartum OGTT results.

Area under the curve for postpartum OGTT. Two studies by the same author examined the 

postpartum OGTT area under the glucose curve and the risk of developing type 2 diabetes.68 69 In 

the one study in which measures of association were reported, the risk of type 2 diabetes 

increased with increasing quartiles of postpartum OGTT area under the glucose curve (p-value 

for trend < 0.0001), after adjusting for gestational age at gestational diabetes diagnosis, 

antepartum OGTT glucose area under the curve, and highest antepartum fasting glucose.68 As 

compared to those in the lowest quartile, those in the highest quartile had an 11-fold increased 

risk of type 2 diabetes (RH = 11.5; 95 percent CI: 4.5 to 29.1).68

We graded the overall body of evidence for metabolic risk factors as moderate. There was 

consistency in the association of 2-hr PPG and Antepartum OGTT glucose area under the curve. 

Additional measures of glucose metabolism. One study by Buchanan et al. examined 

several additional measures of glucose metabolism as risk factors for type 2 diabetes, including 

basal glucose production rate, beta-cell compensation index, clamp insulin sensitivity, and 

frequently sampled intravenous glucose tolerance acute insulin response.74 A higher basal 

glucose production rate was associated with a non-significantly increased risk of type 2 diabetes 

in several multivariable models that included: (1) incremental glucose area on the diagnostic 

OGTT, frequently sampled intravenous glucose tolerance acute insulin response, OGTT 30-min 
70 

incremental insulin:glucose ratio, and clamp insulin sensitivity (model 1); (2) 1-hr OGTT plasma 

glucose and beta-cell compensation index (model 2); and (3) 1-hr OGTT plasma glucose, OGTT 

30-min incremental insulin:glucose ratio, and insulin sensitivity index (model 3).74 

Greater beta-cell compensation index was associated with a 91 percent lower risk of 

developing type 2 diabetes, after adjusting for OGTT 1-hr plasma glucose level and basal 

glucose production rate. Greater clamp insulin sensitivity was associated with a non-significantly 

lower risk of developing type 2 diabetes, after adjusting for OGTT 1-hr glucose level, OGTT 30-

min incremental insulin:glucose ratio, and basal glucose production rate in model 1 (OR = 0.2; 

95 percent CI: 0.03 to 1.2) and after adjusting for diagnostic OGTT incremental glucose area, 

frequently sampled intravenous glucose tolerance acute insulin response, OGTT 30-min 

incremental insulin:glucose ratio, and basal glucose production rate in model 2 (OR = 0.15; 95 

percent CI: 0.02 to 1.2).74 Finally, women in the highest tertile of frequently sampled intravenous 

glucose tolerance test acute insulin response had a 92 percent lower risk of developing type 2 

diabetes than did those in the lowest tertile, after adjusting for diagnostic OGTT incremental 

glucose area, OGTT 30-min incremental insulin:glucose ratio, basal glucose production rate, and 

clamp insulin sensitivity (OR = 0.08; 95 percent CI: 0.01 to 1.0).74 

One study examined C-peptide glucose score as a risk factor for type 2 diabetes.73 In this 

study, a higher C-peptide glucose score was associated with a 54 percent lower risk of 

developing type 2 diabetes, after adjusting for pre-pregnancy BMI and the number of abnormal 

OGTT results (OR = 0.46; 95 percent CI: 0.25 to 0.85).73 We included these additional measures 

of glucose metabolism in order to provide a comprehensive summary of potential risk factors for 

the development of type 2 diabetes. While we were unable to draw conclusions from this 

emerging area of investigation, this review provided insight into the physiologic pathways that 

are being studied to better define the risk of type 2 diabetes among women with gestational 

diabetes. 

The grade of evidence for both anthropometric measures and metabolic risk factors was 

moderate (see Appendix F, Evidence Table 26). However, after considering the quantity, quality, 

and consistency of the reviewed literature on risk factors, we graded the overall body of evidence 

as very low. 

Other potential risk factors for type 2 diabetes. 

Blood pressure. Cho et al. found postpartum blood pressure to be a predictor of type 2 

diabetes, although a relative measure for blood pressure was not reported in their multivariate 

models.62

Lipids. Two studies examined postpartum lipid parameters as predictors of type 2 diabetes,62 

64 and in both of these studies, HDL cholesterol and triglycerides were risk factors for the 

development of type 2 diabetes; however, a relative measure for the lipid parameters was not 

reported in the multivariate models.62 64

Homocysteine. One study assessed homocysteine levels 6 weeks postpartum and found that 

women with homocysteine levels greater than 6.38 mmol had a greater than three-fold increased 

risk of developing type 2 diabetes when compared to those with homocysteine levels below this 

level, after adjusting for age, gestational age at gestational diabetes diagnosis, pre-pregnancy 

BMI, family history of type 2 diabetes, and FBG at diagnosis (RR = 3.6; 95 percent CI: 1.1 to 

11.9).61

Autoantibodies. One study examined GAD and IA-2 antibodies as risk factors for type 2 

diabetes and found that women with positive GAD or IA-2 antibodies had a four-fold increased 

risk of type 2 diabetes when compared to women who were antibody negative, after adjusting for 
71 

the method of glucose control, BMI, parity, age, and serum CRP (RH = 4.1; 95 percent CI: 2.6 to 

6.7).66 We were unable to draw meaningful conclusions based on the available evidence, but we 

have included summaries of these traditional (i.e., lipids, blood pressure) and novel measures to 

provide a comprehensive review of available risk factors for the development of type 2 diabetes. 

Additional studies of risk factors for type 2 diabetes. We identified 11 studies that 

investigated factors associated with incident type 2 diabetes following a pregnancy complicated 

by gestational diabetes, but these studies did not include relative measures of risk or multivariate 

models.76-86 While these studies are important for qualitatively identifying risk factors, we 

consider them to provide the lowest level of evidence because there was no adjustment for 

potential confounders or relative estimates. The evidence is briefly discussed below by risk 

factor category. 

1. Family history of type 2 diabetes: No additional studies. 

2. Sociodemographics: Two studies investigated maternal age. Greenberg et al.83 compared 

maternal ages according to diabetic status at followup and did not find any statistical differences, 

while Dalfra et al.80 did find an association. Two studies, Kousta et al. and Ali et al.,77 87

examined the incidence of type 2 diabetes as stratified by race. Both studies found a higher 

incidence among black and Asian-Indian women than in European women or women of mixed 

ethnicity. 

3. Maternal lifestyle factors: No additional studies. 

4. Parity: Only one study, Linne et al.,79 compared parity in women with and without type 2 

diabetes at followup. No association was observed. 

5. Pregnancy-related factors: Younger gestational age at diagnosis was consistently 

associated with increased incidence of type 2 diabetes in three studies: Greenberg et al.,83 Bartha 

et al.,82 and Dalfra et al.80 Insulin use during pregnancy was consistently associated with 

increased type 2 diabetes in two studies: Greenberg et al.83 and Dalfra et al.80 Class A2 

gestational diabetes was associated with increased type 2 diabetes in one study, that of Kjos et 

al.85 Greenberg et al.83 found that cesarean delivery, shoulder dystocia, and birthweight 

percentile did not differ between women who did and did not develop type 2 diabetes during 

followup. 

6. Postpartum factors: Kjos et al.84 compared women who did and did not breastfeed 

following a pregnancy complicated by gestational diabetes and found that women who breastfed 

had a decreased incidence of type 2 diabetes. 

7. Anthropometric measures: BMI was investigated in six studies: Bian et al.,81 Greenberg et 

al.,83 Pallardo et al.,78 Dalfraet et al.,80 Linne et al.,79 and Bartha.82 There was a significant 

relationship between higher BMI and increased type 2 diabetes in all but one study.83 Pallardo et 

al.78 found that women who had developed type 2 diabetes during followup had higher current 

weight but did not differ in pre-pregnancy weight, weight change, or body fat percentage from 

women without type 2 diabetes at followup. Waist circumference was found to be associated 

with type 2 diabetes by Pallardo et al.78 but was not found to be associated by Linne et al.79

Waist-to-hip ratio was also not associated with type 2 diabetes in the study by Linne et al.79 

8. Oral contraceptive use: Kjos et al.85 found no difference in the incidence of type 2 diabetes 

in women using non-oral contraceptives, ethinyl estradiol-norethindrone, or ethinyl estradiollevonorgestrel. 

9. Metabolic risk factors: Increased fasting glucose was consistently higher in women 

developing type 2 diabetes during followup in four studies: Xiang et al.,76 Linne et al.,79 Dalfra et 

al.,80 and Greenberg et al.83 Higher HbA1c was consistently associated with increased type 2 
72 

diabetes in two studies: Linne et al.79 and Greenberg et al.83 Decreased beta-cell compensation 

was associated with higher risk of type 2 diabetes in one study, Xiang et al.76 Plasma glucose 

levels at 2- and 3-hr during the diagnostic OGTT were found to be associated with increased type 

2 diabetes in one study, Dalfra et al.,80 but not associated in another, Greenberg et al.83

Greenberg et al.83 did find a difference in 1-hr OGTT between women developing type 2 

diabetes during followup and those who remained normoglycemic. Dalfra et al.80 also found 

postprandial plasma glucose, plasma insulin at 30 min during the OGTT, and postpartum plasma 

glucose area under the curve to be associated with type 2 diabetes. While Linne et al.79 found 

blood pressure and lipids to be similar in women with and without type 2 diabetes at followup, 

Pallardo et al.78 found significant differences in triglycerides and diastolic blood pressure but not 

HDL cholesterol, total cholesterol, or systolic blood pressure in women with and without type 2 

diabetes at followup. 

Additional comments on multivariate models. While a multivariate analytic approach was 

used to evaluate most of the risk factors for the development of type 2 diabetes, the factors 

considered and adjusted for in the models differed between studies. For example, some studies 

focused on anthropometric measures, while others focused on physiologic measures. Still others 

included a broader range of key measures of interest. Studies varied with respect to the 

covariates included in the multivariate models (see Appendix F, Evidence Table 15). Some 

studies determined which variable to include in the multivariate models by identifying the most 

significant predictors from the univariate analysis. Other studies did not report how or why 

specific covariates were chosen to be included in the models. Most studies included a list of key 

covariates known to be associated with type 2 diabetes, including (1) age, (2) parity, (3) family 

history of type 2 diabetes, and (4) method of glucose control (diet versus insulin or oral 

medication). Age was included in all of the multivariate models. However, no one study 

included all of the other three key covariates. Also, no group of covariates common to all of the 

multivariate models was constructed for the evaluation of a given risk factor. 

Two studies60 62 with well-defined approaches to the development of the multivariate models 

deserve further comment. In their investigation of the relationship of eight different obesity 

indices with onset of type 2 diabetes, Cho et al.62 followed 909 Korean women for a mean of 

2.13 ± 1.75 years. The authors first stratified the study population into three groups (normal 

glucose tolerance, impaired glucose tolerance, and type 2 diabetes) and performed a univariate 

analysis, examining the distribution of each of the seven obesity measures and relevant 

sociodemographic and clinical risk factors across the three groups of participants. Data were 

collected on risk factors that had been defined prior to the initiation of the study. Each obesity 

measure was then recategorized into quartiles (75th percentile compared to 25th percentile), and 

the association of each measure with type 2 diabetes was assessed using simple logistic 

regression. Correlations between obesity measures and other covariates were assessed. Only 

those factors that were statistically significantly associated with type 2 diabetes in the univariate 

analysis were included as covariates with the obesity measures in the final prediction model. 

These factors were blood pressure, lipid profile, age, duration of followup, parity, family history 

of type 2 diabetes, and working status. All eight of the obesity measures were associated with 

type 2 diabetes. Waist circumference was the strongest predictor (OR = 5.8; 95 percent CI: 2.0 to 

11.8). After adjustment for covariates, the association of waist circumference with postpartum 

type 2 diabetes was moderately attenuated (OR = 3.4; 95 percent CI: 1.8 to 2.2) but remained 

statistically significant, as did the other six obesity measures. Although there was no R2

 to assess 

the relative fit of the model, we conclude that the reported multivariate model was adjusted for 
73 

covariates that are relevant both clinically and statistically to obesity and type 2 diabetes and 

were appropriately included in the model. Cheung et al.60 reported findings from Cox regression 

analyses. The authors chose to include factors that were clinically related to both type 2 diabetes 

and to underlying insulin resistance (as evidenced by fasting hyperglycemia in pregnancy): age, 

parity, BMI, number of episodes of prior gestational diabetes, family history of type 2 diabetes, 

and insulin use versus diet alone in pregnancy. We concluded that these authors appeared to have 

based the selection and adjustment of covariates on the a priori hypothesis of a relationship with 

hyperglycemia and the established association with type 2 diabetes in the development of the 

best predictive model. Both studies represented a systematic approach to the development of 

multivariate models for assessing the direction and magnitude of association of risk factors with 

type 2 diabetes. 

Key Question 4 

What are the performance characteristics (sensitivity, specificity, and reproducibility) of tests for 

diagnosing type 2 diabetes after pregnancy in patients with a history of gestational diabetes? Are 

there differences in the performance characteristics of the test results based on subgroup 

analysis? 

Background and Conceptual Framework 

The prevalence of type 2 diabetes is increasing in the United States and globally.1 Early 

detection and treatment of diabetes has been associated with improved outcomes related to 

microvascular complications and may prevent macrovascular complications as well.88 Women 

with gestational diabetes are at an increased risk of developing type 2 diabetes. An estimated 16 

to 63 percent of women with gestational diabetes will develop type 2 diabetes in the 5 to 10 years 

immediately following pregnancy.29 While postpartum screening for type 2 diabetes among 

women with gestational diabetes has been supported by the ADA17 and ACOG,7

 there is debate 

about which screening test to use and at what interval to screen. These are important questions 

for both clinical providers and public health officials. The fact that only limited evidence is 

available with regard to screening test performance in women with a history of gestational 

diabetes has prolonged the debate and perhaps delayed a consensus on appropriate screening. To 

further define our efforts in addressing this topic, we developed a conceptual framework (see 

Figure 9). Our model incorporates test performance, as measured by sensitivity, specificity, and 

reproducibility, as well as the time interval for screening. 

Despite the known risk of type 2 diabetes among women with gestational diabetes, only 75 

percent of ACOG fellows reported that they routinely perform postpartum screening with the 75-

gm OGTT. Followup varies widely, and many women do not receive the recommended 

screening for type 2 diabetes.19 89 The barriers to use of the OGTT include the cost and 

inconvenience for a new mother. However, there is insufficient evidence supporting the use of an 

alternative screening test, such as the FBG. A recent cost-effectiveness analysis examined 

models for screening and found the OGTT to be cost-effective if used at 3-year intervals. 

Screening with the FBG was cost-effective if used at 1-year intervals.90 More precise knowledge 

of the performance characteristics of these tests may help improve our estimates of the 

effectiveness and total costs associated with screening. 
74 

Figure 9. Conceptual framework of performance characteristics of tests for diagnosing type 2 diabetes 

mellitus when conducted after pregnancy in patients with a history of gestational diabetes mellitus 

GDM = gestational diabetes mellitus; IGT = impaired glucose tolerance; type 2 diabetes = type 2 diabetes mellitus; gm = gram; 

hr = hour; OGTT = oral glucose tolerance test 

In this report, we summarize and critically appraise the literature on the performance of 

currently available screening tests for postpartum glucose screening in order to support the 

development of clinical guidelines for postpartum glucose surveillance. 

Table 6 summarizes the current tests available for postpartum glucose screening and their 

threshold values. 

Table 6. Threshold values for tests to diagnose type 2 diabetes mellitus postpartum 

FBG AND/OR 2-hr PG after 75-gm OGTT 

NDDG 197991 ≥ 7.8 mmol/L (140 mg/dL) ≥ 11.1 mmol/L (200 mg/dL) 

WHO 198592 ≥ 7.8 mmol/L (140 mg/dL) ≥ 11.1 mmol/L (200 mg/dL) 

WHO 199993 ≥ 7.0 mmol/L (126 mg/dL) ≥ 11.1 mmol/L (200 mg/dL) 

ADA 199717 ≥ 7.0 mmol/L (126 mg/dL) 

≥ 7.0 mmol/L (126 mg/dL) 

NA 

≥ 11.1 mmol/L (200 mg/dL) 

2-hr PG = 2-hr plasma glucose; ADA = American Diabetes Association; dL = deciliter; FBG = fasting 

blood glucose; gm = gram; L = liter; mg = milligram; mmol = millimole; NA = not applicable; NDDG = 

National Diabetes Data Group; OGTT = oral glucose tolerance test; WHO = World Health Organization 

Results 

Overview and population characteristics for screening tests for type 2 diabetes. Our 

literature search identified 8 studies and 10 evaluations of a reference test and comparison test. 

Each of the eight studies had a cohort design. Four studies collected data retrospectively.94-97 

Each of these studies retrospectively applied the threshold glucose values of the comparison test 

to previously collected postpartum OGTT results. These studies used a clinic convenience 

Pregnant 

woman 

with 

GDM 

Type 2 diabetes 

IGT 

Normal glucose tolerance 

Test performance characteristics 

75-gm 2-hr OGTT versus 

Fasting blood sugar 

Postpartum screening intervals 

Sensitivity, specificity, and reproducibility 

of test 

Delivery 

6 weeks 6 months 1 year Beyond 
75 

sample, including all women who returned for postpartum testing within a specified time period. 

Four studies collected data prospectively.98-101 These four studies recruited patients with a 

history of gestational diabetes for screening for type 2 diabetes. Seven studies used the same 

OGTT results, but applied different diagnostic threshold criteria. One study100 independently 

performed the FBG and OGTT as two separate tests for comparison (see Appendix F, Evidence 

Table 27). 

As shown in Evidence Table 27, the population in two studies98 100 was more than 50 percent 

Caucasian. One study,95 performed in the United Arab Emigrates, had mostly Arab (80 percent) 

subjects. One study101 was performed in the United Kingdom and included participants from 

three racial/ethnic groups: European, South Asian, and Afro-Caribbean. Three studies,94 97 99

including the study performed in the United States,97 did not report the racial composition of 

their study populations. The cohort included in the study by Reichelt et al.99 was part of a 

Brazilian Cohort Study, which previously reported high representation from non-white 

populations.102

The majority of the studies screened for type 2 diabetes within 1 year of delivery.94-97 100 Two 

studies98 101 reported wide ranges of postpartum testing intervals, from 1 to 86 months and from 6 

to 72 months, respectively. Only one study99 conducted late screening of all subjects (between 4 

and 8 years postpartum). 

Overview of studies evaluating comparison and reference tests for type 2 diabetes. Our 

review yielded three general comparisons: (1) two different diagnostic threshold values applied 

to the 75-gm OGTT (the WHO 1985 criterion versus the WHO 1999 criterion); (2) FBG level 

greater than 7.0 mmol/L (126 mg/dL) (ADA 1997) and the 75-gm OGTT (WHO 1999); and (3) 

FBG greater than 7.0 mmol/L (126 mg/dL) (ADA 1997) and the 75-gm OGTT (WHO 1985). 

For each eligible study, two of our investigators abstracted data serially to create a two-bytwo table for each comparison test. The two-by-two tables contained data for the number of true 

positives (TP), false positives (FP), false negatives (FN), and true negatives (TN). We then 

calculated the sensitivity [# TP/(# TP + # FN)] and specificity [(# TN/ (# TN + # FP)] for each 

comparison test using the structured two-by-two tables. Since some cells included zero, standard 

errors and confidence intervals were calculated by means of the exact binomial formula using 

Stata command “cii” (Intercooled, version 8.2, StataCorp, College Station, TX).103 An example 

of our calculation of the sensitivity, specificity, and standard errors is shown in Table 7, using 

the study by Costa et al.100

Table 7. Example of the calculation of sensitivity, specificity, and standard errors for tests diagnosing type 2 

diabetes when conducted in postpartum gestational diabetes patients after pregnancy

 REFERENCE TEST 

 Positive by OGTT Negative by OGTT 

COMPARISON Positive by FBG TP = 2 FP = 1 

TEST Negative by FBG FN = 0 TN = 117 

TP + FN = 2 FP + TN = 118 

Sensitivity: # TP/(# TP + # FN)= 2/2= 100 percent, 95 percent CI: 16-100 percent 

Specificity: # TN/ (# TN + # FP)=117/118=99 percent, 95 percent CI: 95-100 percent 

FBG = fasting blood glucose; FN = false negatives; FP = false positives; OGTT = oral glucose tolerance test; TN = true 

negatives; TP = true positives 

Performance characteristics. 

Studies of different diagnostic threshold values applied to the 75-gm OGTT. Two studies97 101

compared different threshold values for the OGTT. They reported the same specificity of 98 

percent for the OGTT using a threshold of FBG greater than 7.0 mmol/L (126 mg/dL) (WHO 
76 

1985) and using a threshold of FBG greater than 7.8 mmol/L (140 mg/dL) (see WHO 1999) (see 

Figure 10 and Appendix F, Evidence Table 28). For this comparison, the sensitivity was fixed at 

100 percent because the threshold values used for the comparison test would by definition 

always meet the criteria of the reference test. 

We concluded that relatively few “false positives” resulted from lowering the FBG threshold 

in the 75-gm OGTT to 7.0 mmol/L. Taking into consideration the quantity, quality, and 

consistency of the two studies of different diagnostic threshold values applied to the 75-gm 

OGTT, we graded the strength of the evidence as very low (see Appendix F, Evidence Table 29). 

Studies of FBG level greater than 7.0 mmol/L (126 mg/dL) (comparison test; ADA 1997) as

compared to the 75-gm OGTT (reference test; WHO 1999). Three studies94 95 99 reported data in 

which a single FBG greater than 7.0 mmol/L (126 mg/dL) (ADA 1997) was compared to an 

FBG greater than 7.0 mmol/L (126 mg/dL) or 2-hr plasma glucose after 75-gm OGTT greater 

than 11.1 mmol/L (200 mg/dL) (WHO 1999). The sensitivity for the FBG greater than 7.0 

mmol/L (126 mg/dL) alone compared with a complete OGTT using the same FBG threshold 

(FBG > 7.0 mmol/L [126 mg/dL]) or 2-hr plasma glucose after 75-gm OGTT greater than 11.1 

mmol/L (200 mg/dL) varied across the three studies, ranging from 46 to 89 percent (see Figure 

11 and Appendix F, Evidence Table 28). For these comparisons, the specificity was fixed at 100 

percent, since the threshold values for the comparison test would by definition meet the criteria 

for the reference test. 

These three studies94 95 99 were heterogeneous because postpartum testing occurred less than 

6 months after delivery in two studies94 95 but 4 to 8 years after delivery in the third study.99 In 

addition to this longer time period after delivery, the study population in the third study99 had a 

high prevalence of non-whites (previously reported by the Brazilian Gestational Diabetes Study 

Group)102, which may have affected the test performance. 

We concluded that use of the FBG alone with a threshold of greater than 7.0 mmol/L (126 

mg/dL) had unpredictable sensitivity. Taking into consideration the quantity, quality, and 

consistency of the studies that compared the FBG level greater than 7.0mmol/L (126mg/dL) to 

the 75-gm OGTT (WHO 1999), we graded the strength of the evidence as very low (see 

Appendix F, Evidence Table 29). 

Studies of FBG greater than 7.0 mmol/L (126 mg/dL) (comparison test; ADA 1997) as 

compared to the 75-gm OGTT (reference test; WHO 1985). Five studies95 96 98 100 101 compared an 

FBG greater than 7.8 mmol/l (140 mg/dL) or a 2-hr plasma glucose level after 75-gm OGTT of 

greater than 11.1 mmol/l (200 mg/dL) (WHO 1985) as the reference test to an FBG greater than 

7.0 mmol/L (126 mg/dL) (ADA 1997) as the comparison test. 

These studies consistently reported high specificity (range: 94 to 99 percent). However, the 

sensitivities ranged from 14 to 100 percent (see Figure 12 and Appendix F, Evidence Table 28). 

Kousta et al.101 reported a sensitivity of 73 percent (95 percent CI: 50 to 89 percent), Agarwal et 

al.95 reported a sensitivity of 69 percent (95 percent CI: 53 to 82 percent), and Cypryk et al.98

reported a sensitivity of 14 percent (95 percent CI: 0.04 to 58 percent). Both Holt et al.96 and 

Costa et al.100 reported sensitivities of 100 percent (with 95 percent CIs of 29 to 100 percent and 

16 to 100 percent, respectively) (see Appendix F, Evidence Table 28). 

One study98 reported very low sensitivity for an FBG greater than 7.0 mmol/L (126 mg/dL) 

when compared to a reference OGTT with an FBG greater than 7.8 mmol/l (140 mg/dL) or 2-hr 

plasma glucose level after 75-gm OGTT greater than 11.1 mmol/l (200 mg/dL). This study 

population differed from the other studies’ samples because 23 percent of the subjects were 

excluded from screening as a result of a new diagnosis of type 1 or 2 diabetes postpartum. Also, 
77 

the study population was entirely Polish. These two study characteristics may have reduced the 

spectrum of risk for type 2 diabetes in the screened population as compared to other clinical 

populations, thereby lowering the test’s sensitivity. 

We concluded that use of the FBG with a threshold greater than 7.0 mmol/L had high 

specificity when compared to the 75-gm OGTT but had highly variable sensitivity. Taking into 

consideration the quantity, quality, and consistency of the studies that compared the FBG level 

greater than 7.0 mmol/L (126mg/dL) to the 75-gm OGTT (WHO 1985), we graded the strength 

of the evidence as very low (see Evidence Table 29). 

Subgroup analysis. Only one study94 included analyses of high-risk subgroups: In this 

study, the FBG greater than 7.0 mmol/L (126 mg/dL) (ADA 1997) alone was compared to a 

complete OGTT (FBG > 7.0 mmol/L (126 mg/dL) or 2-hr plasma glucose after 75-gm OGTT 

greater than 11.1 mmol/L (200 mg/dL) (WHO 1999)). In 168 subjects with a family history of 

type 2 diabetes, the sensitivity was 47 percent (95 percent CI: 24 to 71 percent). In another 168 

subjects who required insulin during pregnancy, the sensitivity was 55 percent (95 percent CI: 32 

to 76 percent). We concluded that the FBG may perform better in subgroups with a family 

history of type 2 diabetes or that required insulin during pregnancy than in the general 

population, as reported in a single study.94 

Test reproducibility. Test reproducibility affects diagnostic test accuracy. Five studies95-97 

100 101 reported the type of laboratory equipment used to test samples as an indicator of quality 

control. Three articles reported the kappa statistic as the measure of agreement between the 

results of the comparison and reference test, but not as a standard measure of single-test 

reproducibility.95 98 100

For quantitative assays such as measures of blood glucose, the STARD Initiative 

recommends calculating imprecision as the coefficient of variation by repeating the test over 

several days.24 One study96 reported the coefficient of variation: Holt et al. reported the 

coefficient of variation for plasma glucose testing using the specified laboratory equipment and 

assay. The coefficient of variation for this assay was 1.2 percent at 3.3 mmol/L and 1.49 percent 

at 16.5 mmol/L.96

One study did not meet our inclusion criteria because it did not report the method of 

diagnosing gestational diabetes, but it is notable because it focused on the question of 

reproducibility of the OGTT using FBG greater than 7.0 mmol/L (126 mg/dL) or 2-hr plasma 

glucose after 75-gm OGTT greater than 11.1 mmol/L (200 mg/dL) (WHO 1999).104 The study 

population consisted of 696 Caucasian women with previous gestational diabetes at a median of 

6.2 years postpartum. Women were administered an OGTT, which was repeated within 3 months 

when it met the criteria for diabetes. Type 2 diabetes was confirmed in only 60 percent of the 

women. 

Quality assessment. No study fulfilled all the criteria related to methodological standards for 

evaluating studies of screening tests (see Appendix F, Evidence Table 30). All of the studies had 

notably high losses to followup (range: 20 to 82 percent). The rates were highest in those that did 

not recruit subjects specifically for the study but instead used a convenience sample,94 95 97 since 

the clinics experienced high rates of postpartum loss to followup. Only two studies96 97 described 

the subjects who were lost to followup. Two studies recruited patients specifically for their study, 

but did not describe the selection process or the response rates.100 101 

Additional methodological comments. Two studies98 101 excluded women who were 

diagnosed with type 1 or 2 diabetes postpartum prior to the screening test, resulting in exclusion 

of 14 to 23 percent of the recruited participants (see Appendix F, Evidence Table 27). Based on 
78 

our qualitative evaluation of the studies included in this review, a quantitative synthesis of the 

data was not feasible. 

Limitations. There were several key limitations of these studies. First, six studies95-98 100 101

used the 2-hr 75-gm OGTT with the FBG greater than 7.8 mmol/L (>140 mg/dL) (WHO 1985) 

threshold as a reference. This test may no longer be clinically useful, given current 

recommendations to use a threshold of FBG greater than 7.0 mmol/L (>126 mg/dL) as part of the 

OGTT (WHO 1999). 

Overall, the study quality was poor. The studies were limited by their sampling methods, 

specifically the use of convenience samples that had high losses to followup. It is not clear 

whether the higher-risk patients are more or less likely to attend their postpartum followup visits 

to receive type 2 diabetes screening, and any such pattern may vary according to the country 

studied. In any case, the high loss to followup clearly limited the generalizability of the results. 
98%

98%

90% 92% 94% 96% 98% 100%

46%

72%

89%

0% 20% 40% 60% 80% 100%

14%

69%

73%

100%100%

0% 20% 40% 60% 80% 100%

99%

94%

98%

99%

99%

85% 90% 95% 100%

Figure 10. Specificity of an FBG > 7.0 mmol/L (126 mg/dL) as compared to an FBG >7.8 mmol/L (140 mg/dL) threshold as part o

TP FP FN TN N 

 Conway, 199997 11 3 0 165 179 

 Kousta, 1999101 22 3 0 140 165 Figure 11. Sensitivity for studies of FBG level > 7.0 mmol/L (126 mg/dL) [comparison test] (ADA 1997) compared to the 75-gm O(WHO 1999) 

TP FP FN TN N 

 Reichelt, 200299 8 0 1 108 117 

 Agarwal, 200495 36 0 14 499 549  Reinblatt, 200694 12 0 14 249 275 

Figure 12. Sensitivity and specificity of studies of FBG > 7.0 mmol/L (126 mg/dL) [comparison test] (ADA 1997) compared to the 

test] (WHO 1985)  Sensitivity Specificity TP FP  Kousta, 1999101 16 3  Costa, 2000100 2 1  Holt, 200396 3 7  Cypryk, 200498 1 2  Agarwal, 200495 31 5 

TP = true positives; FP = false positives; FN = false negatives; TN = true negatives; N = sample size; ADA = American Diabetes Association; dL = de

glucose; gm = gram; L = liter; mg = milligram; mmol = millimole; OGTT = oral glucose tolerance test; WHO = World Health Organization 

79 
81 

Chapter 4. Discussion 

Given the increase in obesity and sedentary lifestyles in the United States, the prevalence of 

gestational and type 2 diabetes among reproductive-aged women is expected to rise over the next 

decade. Both obstetrical and primary care physicians care for a growing number of women with 

gestational diabetes who are at increased risk of developing type 2 diabetes. For decades, 

obstetricians and primary care physicians have debated the optimal labor management and 

postpartum followup of women with gestational diabetes. Clinicians, public health advocates, 

and health policymakers have identified the need for evidenced-based practice guidelines for 

labor and postpartum management of women with gestational diabetes. 

To identify the evidence on labor and postpartum management of gestational diabetes, the 

AHRQ, in conjunction with the ACOG, requested an evidence report on four distinct questions. 

We applied rigorous selection criteria and assessed the quality of each study, using a clinical and 

public health framework to guide our review. Our report is limited to gestational diabetes in 

which the diagnosis was confirmed by an OGTT, thereby ensuring that our review includes 

women with a definitive diagnosis of gestational diabetes. This evidence report outlines a 

comprehensive review of all the available research. In this final chapter, we first review the 

major findings pertaining to each question and the strength of the overall evidence; we then 

present our conclusions, make recommendations for future research, and offer clinical and public 

health perspectives. 

Summary of the Key Findings 

Key Question 1 

What is the evidence for the risks and benefits of oral diabetes agents (e.g., second-generation 

sulfonylureas and metformin), as compared to all types of insulin, for both the mother and 

neonate in the treatment of women with gestational diabetes? 

Relatively few studies have examined the effect of oral agents or insulin analogues, as 

compared to insulin, on a number of significant maternal and neonatal outcomes in women with 

gestational diabetes. Only three RCTs assessing the efficacy of glyburide and insulin met our 

inclusion criteria,32 33 37 and only two maternal outcomes were evaluated in more than one RCT: 

cesarean delivery and maternal glycemic control. There was little difference in maternal 

outcomes between those treated with glyburide and those receiving insulin. In the largest trial (n 

= 404) comparing glyburide and insulin, 49 percent of the women on insulin underwent cesarean 

delivery, as compared to 46 percent of those on glyburide.32 A second trial37 reported no 

difference in cesarean delivery rates for 51 women on glyburide, insulin, or acarbose. Three 

trials found no statistically significant differences in glucose control between women treated with 

insulin and those receiving glyburide.32 32 33 There was one study that considered pre-eclampsia, 

two studies that included maternal weight, and two studies that included information on maternal 

hypoglycemia. There were no available data with regard to perineal tears, operative vaginal 

delivery, or postpartum hemorrhage. Because of the small number of RCTs and the lack of 
82 

consistency in the maternal outcomes measured across studies, we graded the overall strength of 

evidence as very low. 

Only four neonatal outcomes were evaluated by more than one RCT: birth weight, LGA, 

macrosomia, and neonatal hypoglycemia. We conducted a meta-analysis of three RCTs with a 

total of 478 pregnancies. There was a lower average infant birth weight in the insulin group as 

compared to the glyburide group (-93 gm; 95 percent CI: -119 to 5). This difference was not 

statistically significant and is unlikely to have substantial clinical influence. We were unable to 

draw any definitive conclusions regarding neonatal hypoglycemia, given the limited data 

available. Langer et al.32 reported no significant difference between glyburide and insulin in the 

percentage of infants with hypoglycemia (9 percent versus 6 percent, p = 0.25), but Bertini et 

al.37 reported a higher percentage of infants with hypoglycemia in the glyburide group than in the 

insulin or acarbose groups (33 percent compared to 4 percent and 5 percent, respectively; p = 

0.006). Several of our neonatal outcomes of interest were not included in the RCTs reviewed. 

Therefore, we were unable to draw conclusions about anoxia, birth trauma, respiratory distress 

syndrome, or shoulder dystocia. 

We extended our review of the literature on insulin and glyburide to include four 

observational studies.45-48 None of the observational studies were strong enough to justify a 

modification of the conclusions drawn from the RCTs. 

Two RCTs compared the effect of insulin lispro and regular insulin on maternal and neonatal 

outcomes in women with gestational diabetes.34 36 We concluded that there was little difference 

in maternal glucose control (glycosylated hemoglobin or 1-hr glucose levels) between the 

women treated with insulin lispro and those treated with regular insulin. Neither Jovanoic36 nor 

Mecacci34 reported significant differences in mean infant birth weight between the insulin lispro 

and regular insulin groups. We concluded that no evidence exists to suggest that neonatal 

outcomes differ between those treated with regular insulin and those receiving insulin lispro. The 

limited number of trials, limited sample size, and paucity of information on neonatal outcomes 

made it difficult to draw any firm conclusions. 

There was insufficient evidence to draw meaningful conclusions about the effect of longacting versus short-acting insulin, twice-daily versus four-times-daily use of regular insulin, or 

diet alone versus diet plus insulin. In one study comparing long-acting to short-acting insulin, 

there was a higher percentage of infants with macrosomia in the long-acting insulin group than in 

the short-acting insulin group.31 Limited data from one RCT35 suggested that twice-daily insulin 

may be associated with worse neonatal outcomes (neonatal hypoglycemia, macrosomia, LGA, 

and SGA) than four-times-daily use of insulin. We found no evidence to suggest a difference in 

maternal outcomes between twice-daily and four-times-daily use of regular insulin. In the study 

by Thompson,30 women were randomized to diet alone or diet plus a fixed insulin regimen that 

included 20 units of NPH insulin and 10 units of regular insulin. There was no reported 

difference in maternal glucose control or the proportion of women undergoing cesarean delivery 

in the two groups. In terms of neonatal outcomes, infant birth weight was higher in the diet-alone 

group than in the diet and insulin group. Similarly, there was a higher proportion of infants with 

macrosomia in the diet-alone group. These findings must be viewed with caution because the 

overall strength of the evidence for diet compared to insulin and dietary management was very 

low. 

We did not identify any studies that compared metformin with other diabetes medications in 

women with gestational diabetes. Also, we found no evidence regarding maternal or neonatal 

outcomes as related to the level of glucose at the initiation of a medication. 
83 

Key Question 2 

What is the evidence that elective cesarean delivery or the choice of timing of induction in 

gestational diabetes results in beneficial or harmful maternal and neonatal outcomes? 

There is little evidence on the effect of gestational age or EFW on the timing of labor 

induction or performance of elective cesarean delivery in women with gestational diabetes. The 

findings from one experimental study55 suggested that active induction of labor at 38 weeks of 

gestation reduced infant birth weight (3,672 gm versus 3,446 gm; p < 0.01) and rates of 

macrosomia (27 percent versus 15 percent; p = 0.05) when compared to expectant management, 

with no concomitant increase in the rate of cesarean delivery (25 percent in the active induction 

group versus 31 percent in the expectant management group; p = 0.43). While these results 

suggested that maternal outcomes might be better in women who undergo elective induction, we 

were unable to draw firm conclusions based on this one trial. 

Observational studies52-54 56-59 provided some additional evidence of a reduction in 

macrosomia and shoulder dystocia with elective labor induction or cesarean delivery, when 

compared to expectant management. For example, in the study by Conway,53 women with 

diabetes underwent ultrasonographic estimates of fetal weight between 37 and 38 weeks of 

gestation. Women whose EFW was greater than or equal to 4,250 gm underwent cesarean 

delivery; those whose EFW was estimated at less than 4,250 gm but LGA (defined as ≥ 90th

percentile for the gestational age in their population) underwent labor induction. Fewer infants 

were macrosomic (weighing 4,000 gm or more) in the group undergoing elective cesarean or 

labor induction than in the expectant management group (8.9 percent versus 11.6 percent; p = 

0.04). In addition, the incidence of shoulder dystocia was higher in the expectant management 

group (OR = 1.9, 95 percent CI: 1.0 to 3.5) than in the group undergoing elective cesarean or 

labor induction. The overall strength of evidence on this comparison was graded as very low. 

Only one of the observational studies adjusted for potential confounders,56 so any measures of 

association may have been biased. Second, there may have been selection bias in the recruitment 

of women to participate in the studies. Third, there was substantial heterogeneity in terms of the 

comparison groups, length of followup, and outcome measures included in the analysis. Fourth, 

the four primary observational studies were conducted over a wide timeframe. It would be 

difficult to adequately adjust for changes in practice patterns and treatment modalities that 

occurred over the long time periods of the studies. 

Key Question 3 

What risk factors, including but not limited to family history, physical activity, pre-pregnancy 

weight, and gestational weight gain, are associated with short-term and long-term development 

of type 2 diabetes following a pregnancy with gestational diabetes? 

Several factors were associated with the development of type 2 diabetes in women with 

previous gestational diabetes. Anthropometric measures before, during, and after pregnancy were 

found to be positively associated with the development of type 2 diabetes in 10 of 11 cohort 

studies. Waist circumference and BMI were the strongest anthropometric measures associated 

with type 2 diabetes in gestational diabetic women. Early gestational age at diagnosis of 

gestational diabetes (primarily less than 24 weeks) and use of insulin versus diet for glucose 
84 

control were key pregnancy-related clinical factors that were positively associated with type 2 

diabetes. Physiologic measures, including FBG and 2-hr plasma glucose levels during the 

diagnostic OGTT, were also associated with development of type 2 diabetes. Higher blood 

glucose following a screening 50-gm GCT, prior gestational diabetes, and OGTT area under the 

curve during both the antepartum and postpartum periods were positively associated with 

development of type 2 diabetes, but the strength of the associations was not consistent across 

studies. There is conflicting data on progesterone-only contraceptive use and the risk for 

developing type 2 diabetes. Elevated postpartum homocysteine levels were positively associated 

with type 2 diabetes in one study. Surprisingly, there were no studies of lifestyle factors in 

women with gestational diabetes that met our review criteria. 

After a review of the available evidence, we concluded that the strongest epidemiological 

risk factors were anthropometric measures prior to pregnancy and during both the antepartum 

and postpartum periods. Taking into consideration the quantity, quality, and consistency of the 

studies evaluating the association of risk factors for type 2 diabetes following a pregnancy with 

gestational diabetes, we graded the strength of the evidence as very low. While there was 

substantial consistency in the direction of association across studies for many of the risk factors, 

there was considerable variation in the covariates adjusted for in multivariate models across 

studies. 

Key Question 4 

What are the performance characteristics (sensitivity, specificity, and reproducibility) of tests for 

diagnosing type 2 diabetes after pregnancy in patients with a history of gestational diabetes? 

Are there differences in the performance characteristics of the test results based on subgroup 

analysis? 

Several studies have pointed to poor physician compliance with postpartum glucose 

screening for type 2 diabetes among women with a history of gestational diabetes.19 20 We 

reviewed the available studies of the diagnostic accuracy of screening for type 2 diabetes in this 

population. We identified 8 studies and 10 evaluations of screening tests, with three types of 

comparisons: 

1. two different diagnostic fasting value thresholds applied to the 75-gm OGTT (the WHO 1985 

criteria compared to the WHO 1999 criteria); 

2. single FBG level greater than 7.0 mmol/L (126 mg/dL) (ADA 1997) compared to the 75-gm 

OGTT (WHO 1999); and 

3. single FBG greater than 7.0 mmol/L (126 mg/dL) (ADA 1997) compared to the 75-gm OGTT 

(WHO 1985). 

For the first comparison, we concluded that there was acceptable specificity (98 percent) for 

the OGTT using either a FBG value greater than 7.0 mmol/L (126 mg/dL) or greater than 7.8 

mmol/L (140 mg/dL). For the second comparison, we were unable to draw meaningful 

conclusions. The sensitivities for a single FBG greater than 7.0 mmol/L (126 mg/dL), as 

compared to a complete OGTT using the same FBG threshold, ranged from 46 to 89 percent in 

the three studies. For the third comparison, there were five studies, which reported a high 

specificity of the FBG greater than 7.0 mmol/L (126 mg/dL). However, there was a wide range 

of sensitivity, from 14 to 100 percent. 
85 

The six studies95-98 100 101 that used an FBG threshold greater than 7.8 mmol/L (140 mg/dL) in 

the reference test may be obsolete, since current guidelines recommend an FBG greater than 7.0 

mmol/L (126mg/dL)17 93 105 The wide variation in the reported sensitivities for studies that 

compared the OGTT as the reference test to a single FBG greater than 7.0 mmol/L (126 mg/dL) 

may reflect differences in the study samples’ risk for type 2 diabetes, based on heterogeneity of 

study design and population. The overall strength of evidence was very low because of the high 

loss-to-followup rates (22 to 82 percent) for studies using clinic convenience samples. 

Conclusions 

Based on the available data outlined in Chapter 3, we have made the following conclusions: 

Key Question 1: Little evidence exists to guide patients, health care providers, or 

policymakers in the choice of treatment for gestational diabetes. We were unable to draw firm 

conclusions from any of the five treatment comparisons in Key Question 1 because of the 

availability of only a limited number of studies within each category of comparison, a lack of 

consistency in the outcomes measured across studies, and heterogeneity in the definition of 

outcome measures. Limited evidence demonstrated no substantial clinical differences in 

maternal or neonatal outcomes with the use of glyburide or insulin lispro as compared to insulin 

in women with gestational diabetes. Our meta-analysis of three studies showed a small difference 

in infant birth weight. We expect little clinical relevance for the weighted mean difference of 93 

gm. The results of our meta-analysis provide additional information for clinicians to incorporate 

into their discussions with patients about their choice of treatment but are unlikely to affect 

current clinical practice. 

We did not identify any available evidence on variations in maternal or neonatal outcomes 

based on the level of glucose at the initiation of a medication. Each of the clinical trials and 

observational studies reviewed specified threshold glucose levels for the initiation of medical 

treatment as part of the study protocol. However, none of the studies compared outcomes based 

on glucose thresholds in their evaluation of maternal or neonatal outcomes. Findings from the 

HAPO study may provide further insights. Therefore, we were unable to provide evidence for 

this portion of Key Question 1. We were also unable to identify any published studies comparing 

metformin to diet, insulin, or insulin analogues in women with gestational diabetes. However, 

the ongoing MiG trial will likely provide evidence regarding the comparative effects of 

metformin and insulin on maternal and neonatal outcomes. 

Key Question 2: Little evidence exists to guide health care providers in the use of EFW or 

gestational age in making decisions about the timing of labor induction or elective cesarean 

delivery. We identified only one relevant RCT. The findings from the few available 

observational studies were difficult to interpret because of variations in clinical practice over the 

time period of the studies. Furthermore, serious methodological limitations made it difficult to 

draw firm conclusions. While our review does provide physicians and other health care providers 

with a summary of the gaps in the available evidence, further study involving clinical trials or 

well-designed observational studies is necessary to effect modifications in clinical management 

and inform development of clinical pathways. 

Key Question 3: There was consistent evidence that anthropometric measures (i.e., weight, 

BMI, and waist circumference) prior to pregnancy and during both the antepartum and 
86 

postpartum periods were positively associated with development of type 2 diabetes. These 

findings suggested similar risk factors for type 2 diabetes in reproductive and middle-aged 

women. Moreover, it appeared that weight and the distribution of weight were strong predictors 

of type 2 diabetes in this special population of women. Metabolic risk factors, including higher 

FBG at diagnosis of gestational diabetes, high glucose levels in oral glucose tolerance testing, 

insulin-requiring gestational diabetes, and glucose AUC for antepartum glucose tolerance testing, 

were consistently associated with an increased likelihood of type 2 diabetes. The relationship 

between progesterone-only contraception use and the risk of type 2 diabetes in women with a 

prior history of gestational diabetes, however, remains unclear. There was no evidence available 

regarding the potential effect of lifestyle factors (e.g., physical activity) on the development of 

type 2 diabetes in women with a prior history of gestational diabetes. Further investigation, 

ideally involving RCTs, would provide evidence for the primary prevention of type 2 diabetes in 

this high-risk group. Such evidence could then be incorporated into preconception and prenatal 

care education. 

Key Question 4: We were unable to draw meaningful conclusions from the limited evidence 

available for our review. As compared to the 75-gm OGTT, the FBG had high specificity, but the 

sensitivity was variable across studies. As a result of heterogeneity in the study design, recruited 

population, and interval of followup testing, we were unable to draw firm conclusions about the 

performance characteristics of the FBG in women with a history of gestational diabetes. There 

was also insufficient evidence regarding test reproducibility. Until the appropriate intervals for 

followup testing are realized, further investigations would benefit from an interdisciplinary 

clinical approach. While obstetricians may provide immediate postpartum screening, general 

practitioners, internists, and other health care providers will likely provide long-term followup. 

With the increasing prevalence of childbearing among older women, pregnant women more 

commonly receive care from an obstetrician-gynecologist and either an internist or other primary 

care provider. Thus, an interdisciplinary dialogue among providers will be necessary to influence 

future care. 

Future Research 

While basic science research and investigations using animal models have helped us to better 

understand the underlying pathophysiology of gestational diabetes, there is a wide gap in our 

clinical knowledge with regard to how potential treatments and postpartum management can 

benefit both mothers and infants. Future research should be directed toward filling this gap by 

conducting studies that will lead to the development of evidenced-based guidelines for maternal 

glucose control and physician recommendations for labor induction, elective cesarean, and 

expectant management. In addition, future research should focus on risk factors for type 2 

diabetes in this high-risk population and on developing effective screening modalities for 

identifying women who are at risk for developing type 2 diabetes. 

Further RCTs are needed to better assess maternal and neonatal outcomes in women with 

gestational diabetes who are being treated with insulin, insulin analogues, metformin, or 

glyburide. Future trials should specify a priori hypotheses and conduct power analyses prior to 

recruitment to ensure the ability to detect small differences in maternal glucose levels that can 

affect fetal weight and the risk of macrosomia, as well as common outcomes such as cesarean 

delivery. Power analyses will aid researchers in detecting differences in less common but 
87 

critically important outcomes, such as shoulder dystocia and birth trauma. Clinical trials 

designed to capture these differences can offer important information and help us to draw 

reasonable and firm conclusions. Finally, intention-to-treat analysis will be essential to the ability 

to draw firm conclusions from the reported data. Consistency in the collection of outcome 

measures across studies is essential to our ability to draw confident conclusions. Furthermore, it 

would help to have more consistent definitions of clinical outcomes, including maternal and 

neonatal hypoglycemia, so that clinicians and investigators can better compare results across 

multiple studies. Observational studies in this area should be prospective, with protocols 

developed to minimize loss to followup. Adjustment for covariates will be of paramount 

importance for determining true estimates of the association of treatment choice with maternal 

and neonatal outcomes. 

Well-designed RCTs comparing elective induction and cesarean delivery to expectant 

management would provide relevant, critical data to practitioners. These trials should incorporate 

appropriate methods of randomization and an intention-to-treat analysis, as well as power 

calculations with estimated effect sizes for mothers and infants. We acknowledge the potential 

barriers to performing clinical trials in pregnant women. Clinical trials with regard to labor 

management may be particularly difficult in the current obstetrical environment, which is highly 

litigious and influenced by patient and provider preferences for care. Well-designed 

observational studies are a reasonable alternative and can provide the necessary data to guide the 

development of clinical practice guidelines for labor management. Observational studies should 

primarily focus on insulin-requiring gestational diabetics (i.e., class A2), since this population is 

at higher risk of macrosomia or cesarean delivery. Alternatively, observational studies of diet 

and insulin-controlled gestational diabetics might include stratified analyses, which would 

provide outcome data at different levels of severity. Finally, future studies should adjust for other 

potential confounders, including sociodemographics and clinical factors related to intrapartum 

management. 

Our review of 16 cohort studies identified several risk factors that are amenable to targeted 

interventions. One limitation of the current body of literature, however, is the inconsistency in 

the specific risk factors that have been assessed. Future studies should first focus on specific 

categories of risk factors, such as anthropometric measures (e.g., weight, BMI) or reproductiverelated factors (e.g., parity). Second, future studies should collect data on pertinent covariates 

and adjust for relevant confounders in multivariate analysis. Third, women should be recruited 

for longitudinal study at the time of diagnosis of gestational diabetes. Fourth, several studies 

included in this review were based on convenience sampling, which may have biased the results; 

random or purposeful sampling of participants would yield a more representative group of 

participants. 

Early identification of women with type 2 diabetes is paramount to achieving high quality of 

care and the ability to avoid diabetic complications due to delays in diagnosis. Future studies 

should focus on comparisons of the FBG and the standard 75-gm OGTT in postpartum women. 

Such comparisons would provide relevant data on the ability to screen women with a simple, 

time-efficient test, as compared to the burdensome OGTT. Studies should be conducted in 

diverse populations so that there is confidence that the findings are generalizable to other 

populations. The conduct of these studies in certain sub-groups (e.g., women with a family 

history of type 2 diabetes or prior gestational diabetes) is also warranted. Finally, studies of the 

reproducibility of test results will be critical to the development of broadly acceptable clinical 

guidelines for testing. 
88 

Implications 

The results of this systematic review have important implications for clinical practice and 

public health policy. Clinicians and policymakers should be aware that the available data, while 

limited, do not suggest that there are adverse maternal or neonatal outcomes associated with the 

use of oral diabetic agents (i.e., glyburide), insulin lispro, or various insulin regimens. The 

efficacy of insulin analogs or glyburide in achieving maternal glucose targets or preventing 

episodes of maternal or neonatal hypoglycemia remains unclear. Several measures of maternal 

and neonatal morbidity, such as perineal tears, operative vaginal delivery, have not been 

evaluated, and several measures have only been evaluated in one or two studies. Also, it is 

unclear what glucose thresholds should be used to initiate insulin, insulin analogues, or glyburide 

in patients on diet alone. 

Clinicians should also be aware that there is currently insufficient evidence to develop clear 

guidelines for labor induction or elective cesarean delivery in women with gestational diabetes. 

The conduct of well-designed clinical trials or observational studies may provide insight into 

evidenced-based management. 

For public health policymakers, our conclusion is that measures of obesity and antepartum 

glucose values are the most consistent and substantiated risk factors for type 2 diabetes in 

women with gestational diabetes. With findings from the Diabetes Prevention Trial106

highlighting the effect of lifestyle modifications on the primary prevention of type 2 diabetes in 

high-risk populations, our review suggests that the effectiveness of these interventions should be 

tested in women with a prior history of gestational diabetes. 

Finally, we conclude that there are insufficient data to recommend alternative tests to the 75-

gm OGTT for the detection of type 2 diabetes in women with gestational diabetes. Public health 

policymakers should work with health care researchers and national organizations (e.g., the 

ACOG and ADA) to further evaluate the effectiveness and timeliness of postpartum screening 

for type 2 diabetes in women with gestational diabetes. Further investigation can provide the data 

needed to develop broadly acceptable postpartum screening guidelines. 
89 

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List of Abbreviations 

ACOG American College of Obstetricians and Gynecologists

ADA American Diabetes Association 

AHRQ Agency for Healthcare Research and Quality

BMI Body mass index 

CC Concurrent control group 

CD Cesarean delivery 

CENTRAL Central Register of Controlled Trials 

CI Confidence interval 

CINAHL Cumulative Index to Nursing and Allied Health Literature 

CPD Cephalopelvic disproportion 

CRP C-reactive protein 

dL Deciliter 

EFW Estimated fetal weight 

EPC Evidence-based Practice Center

FBG Fasting blood glucose 

FN False negative 

FP False positive 

gm Grams 

GAD Glutamic acid decarboxylase 

GCT Glucose challenge test 

Gestational 

diabetes 

Gestational diabetes mellitus 

HAPO Hyperglycemia and Adverse Pregnancy Outcome 

HDL High-density lipoprotein 

hr Hour 

IA-2 Insulinoma antigen-2 

IGT Impaired glucose tolerance 

IU International units 

kg Kilograms 

KQ Key Question 

LDL Low-density lipoprotein 

LGA Large for gestational age 

L/S ratio Lecithin-to-sphingomyelin 

MeSH Medical subject headings 

mg milligrams 

MiG Metformin in Gestational Diabetes 

MOOSE Meta-analysis of Observational Studies in Epidemiology 

NDDG National Diabetes Data Group 

NICU Neonatal intensive care unit admissions 

NPH Neutral Protamine Hagedom 

OGTT Oral glucose tolerance test 

OR Odds ratio 
96 

PCOS Polycystic ovarian syndrome 

PDF Portable document format 

PPG Postprandial glucose 

RCT Randomized controlled trials 

RDS Respiratory distress syndrome 

RH Relative hazard 

RR Relative risk 

SD Standard deviation 

SE Standard error 

SGA Small for gestational age 

STARD Standards for Reporting of Diagnostic Accuracy 

STROBE Standards for Reporting of Observational Studies 

TN True negative 

TP True positive 

Type 2 diabetes Type 2 diabetes mellitus 

US Ultrasound 

WHO World Health Organization 
A-1 

Appendix A: Technical Experts and Peer Reviewers 

Donald R. Coustan, M.D. 

Chace/Joukowsky Professor and Chair 

Department of Obstetrics and Gynecology 

Warren Alpert Medical School of Brown 

University 

Chair of Obstetrics and Gynecology 

Women and Infants Hospital of Rhode 

Island 

Providence, RI 

Richard Hellman, M.D. 

Clinical Professor of Medicine 

University of Missouri – Kansas City School 

of Medicine 

Kansas City, MO 

Jean M. Lawrence, Sc.D., M.P.H. 

Research Scientist II/Epidemiologist 

Research and Evaluation 

Kaiser Permanente Southern California 

Pasadena, CA 

Troy Flint Porter, M.D. 

University of Utah School of Medicine and 

Intermountain Health Care 

Salt Lake City, UT 

Samuel F. Posner, Ph.D. 

Centers for Disease Control and Prevention 

Atlanta, GA 

E. Albert Reece, M.D., Ph.D., M.B.A. 

Dean and Vice President for Medical Affairs 

University of Maryland School of Medicine 

Baltimore, MD 

Caroline Signore, M.D., M.P.H. 

Medical Officer, Obstetrics 

Program Scientist, PASS Network 

Pregnancy and Perinatology Branch 

National Institute of Child Health and 

Human Development 

Bethesda, MD 
B-1 

Appendix B: Hand Searched Journals 

All Journals Hand Searched 

August 2006 – January 2007 

Acta Obstetricia et Gynecologica Scandinavica 

American Journal of Obstetrics and Gynecology 

American Journal of Perinatology 

The Australian and New Zealand Journal of Obstetrics and Gynaecology 

BJOG: An international journal of obstetrics and gynecology 

Diabetic Medicine 

Diabetes 

Diabetes Care 

Diabetes Research and Clinical Practice 

European Journal of Obstetrics & Gynecology and Reproductive Biology 

International Journal of Gynecology & Obstetrics 

Obstetrics & Gynecology 
C-1 

Appendix C: Detailed Electronic Database Search 

Strategies 

MEDLINE Strategy 

Terms Returns 

(Diabetes, gestational[mh] OR gestational diabet*[tiab] OR diabetes in 

pregnancy[tiab] OR (diabet*[tiab] AND gestation*[tiab])) AND (((Insulin[mh] 

OR Insulin[tiab]) OR (sulfonylurea compounds[mh] OR hypoglycemics[tiab] 

OR hypoglycemic agents[tiab] OR Glyburide[tiab] OR Glipizide[tiab] OR 

glimepiride[tiab]) OR (Biguanides[mh] OR biguanide*[tiab] OR 

Metformin[tiab]) OR (Pregnancy[mh] OR Pregnan*[tiab] OR Pregnancy 

complications[mh] OR treatment outcome[mh] OR treatment outcome*[tiab]) 

OR (labor, induced[mh] OR Induced labor[tiab] OR Induction of labor[tiab] OR 

Obstetric Labor[mh] OR Cesarean section[mh] OR cesarean*[tiab] OR Csection[tiab] OR Abdominal deliver*[tiab]) OR (Diabetes Mellitus, Type 2[mh] 

OR (Diabet*[tiab] AND type 2[tiab]) OR (Diabet*[tiab] AND type II[tiab])))) 

AND eng[la] NOT (animals[mh]NOT humans[mh]) 

5628 

EMBASE Strategy 

((((((('pregnancy diabetes mellitus'/exp) OR ('gestational diabetes')) OR 

(('pregnancy'/exp) AND ('non insulin dependent diabetes mellitus'/exp))) OR 

(('type 2 diabetes' OR 'type ii diabetes' OR 'diabetes mellitus') AND (pregnant 

OR pregnancy))) AND (((('antidiabetic agent'/exp) OR (hypoglycemic) OR 

('hypoglycemic agent')) OR (insulin)) OR (('risk factor') OR ('treatment 

outcome'/exp) OR ('treatment outcome') OR ('pregnancy outcome'/exp) OR 

('pregnancy outcome') OR (benefit) OR ('adverse event') OR (comorbidity)) OR 

(('labor'/exp) OR ('labor induction'/exp) OR ('induced labor') OR ('cesarean 

section')) OR ('reproducibility'/exp)))) AND [english]/lim AND [humans]/lim) 

NOT [review]/lim 

5306 
C-2 

The Cochrane Central Register of Controlled Trials (CENTRAL) 

#1 MeSH descriptor Diabetes, Gestational explode all trees 

#2 (gestational diabetes) or (gestational diabetes):ti or (gestational 

diabetes):ab or (gestational diabetes):kw 

#3 (#1 OR #2) 

#4 MeSH descriptor Diabetes Mellitus, Type 2 explode all trees 

#5 (diabetes) or (diabetes):ti or (diabetes):ab or (diabetes):kw 

#6 (#4 OR #5) 

#7 MeSH descriptor Labor, Induced explode all trees 

#8 (labor) or (labor):ti or (labor):ab or (labor):kw 

#9 (Induc*) or (Induc*):ti or (Induc*):ab or (Induc*):kw 

#10 (#8 AND #9) 

#11 (#7 OR #10) 

#12 MeSH descriptor Cesarean Section explode all trees 

#13 (cesarean*) or (cesarean*):ti or (cesarean*):ab or (cesarean*):kw 

#14 (caesarean*) or (caesarean*):ti or (caesarean*):kw or (caesarean*):ab 

#15 (#14 AND NOT #13) 

#16 (#13 OR #14) 

#17 MeSH descriptor Insulin explode all trees 

#18 (insulin) or (insulin):ti or (insulin):kw or (insulin):ab 

#19 MeSH descriptor Sulfonylurea Compounds explode all trees 

#20 (glyburide) or (glyburide):ti or (glyburide):kw or (glyburide):ab 

#21 (glipizide) or (glipizide):ti or (glipizide):kw or (glipizide):ab 

#22 (glimepiride) or (glimepiride):ti or (glimepiride):kw or (glimepiride):ab 

#23 (#17 OR #18) 

#24 (#19 OR #20 OR #21 OR #22) 

#25 MeSH descriptor Metformin explode all trees 

#26 (Metformin) or (Metformin):ti or (Metformin):kw or (Metformin):ab 

#27 (#25 OR #26) 

#28 (#12 OR #16) 

#29 MeSH descriptor Pregnancy Complications explode all trees 

#30 MeSH descriptor Pregnancy explode all trees 

#31 (pregnan*) or (pregnan*):ti or (pregnan*):kw or (pregnan*):ab 

#32 MeSH descriptor Risk explode all trees 

#33 (risk*) or (risk*):ti or (risk*):kw or (risk*):ab 

#34 (#29 OR #30 OR #31) 

#35 (#32 OR #33) 

#36 (#23 OR #24 OR #27) 

#37 (#3 AND ( #11 OR #28 OR #36 OR #34 OR #35 )) 

225 
C-3 

Cumulative Index to Nursing and Applied Health Literature (CINAHL) 

((MH Diabetes Mellitus, Gestational) OR (MH Diabetes Mellitus, Non-InsulinDependent) OR (TX "gestational diabetes") OR ((TX "type 2 diabetes" OR TX 

"type II diabetes" OR (TX diabetes and TX ( "type II" OR "type 2" ))) AND TX 

Pregnancy) OR (TX Pregnancy and TX diabetes) OR (TX "diabetes in 

pregnancy")) AND (( MH "pregnancy outcomes" or MH "Pregnancy 

Complications" or MH comorbidity ) OR (TX ( Maternal OR neonatal OR 

pregnancy ) and TX ( "adverse event" OR benefit OR risk OR complication OR 

complications OR outcome OR outcomes ) )) OR ((MH insulin or MH 

hypoglycemic agents or MH sulfonylurea compounds ) OR (TX ( hypoglycemics 

OR "hypoglycemic agents" OR sulfonylurea OR metformin ) )) OR (TX ( 

“diagnostic test” OR “diagnostic tests” ) or MH ( “sensitivity and specificity” ) 

or MH “reproducibility of results” )) NOT ( review OR "meta-analysis" OR 

"meta analysis" OR metaanalysis ) and LA English 

2907 

 

 
D-1 

Appendix D: List of Excluded Studies 

1. National Diabetes Month. Reviewing the types 

of diabetes. Diabetes Self Manag 

2006;23(6):38, 40-2. 

Does not include original data

2. Anonymous. Gestational diabetes mellitus. 

Diabetes Care 2004;27 (Suppl 1):S88-90. 

Does not include original data

3. Anonymous. Gestational diabetes mellitus. 

Diabetes Care 2003;26 (Suppl 1):S103-5. 

Does not include original data

4. Anonymous. Pregnancy problems echo later in 

life. Harv Heart Lett 2002;13(4):7. 

Does not include original data

5. Anonymous. Gestational diabetes mellitus. 

Diabetes Care 2000;23 (Suppl 1):S77-9. 

Does not include original data

6. Anonymous. Induction of labour at term (versus 

expectant management) for macrosomia results 

in which one of the following? Decreased birth 

weight. Can Fam Physician 1998;44:1610, 

1619-20. 

Does not include original data

7. Anonymous. From the Centers for Disease 

Control and Prevention. Prenatal care, 

pregnancies complicated by diabetes. JAMA 

1993;269(15):1932. 

Does not apply to a key question 

8. Anonymous. Sulphonylureas in pregnancy. 

Lancet 1991;338(8776):1222. 

Does not include original data 

9. Anonymous. Diabetes in pregnancy. Baillieres 

Clin Obstet Gynaecol 1991;5(2):257-503. 

Other 

10. Anonymous. Diabetes in pregnancy. Clin Obstet 

Gynecol 1985;28(3):455-568. 

Does not include original data 

11. Anonymous. Insulin pump shows promise for 

pregnant women--but problems for children. 

Am Pharm 1986;NS26(4):9-10. 

Does not include a medication of interest for 

KQ1 

12. Anonymous. The lack of drug studies in 

pregnancy currently restricts treatment options 

to insulin for gestational diabetes. Drugs Ther. 

Perspect. 2004;20(6):17-20. 

Does not include original data 

13. Anonymous. Use of glibenclamide in 

gestational diabetes. Pharm. J. 

2000;265(7120):644. 

Does not include original data 

14. Anonymous. Diabetes and congenital 

abnormalities. Bandolier 2006;13(3):5. 

Does not apply to a key question 

15. Anonymous. Gestational diabetes mellitus. 

Canadian Journal of Diabetes 2003;27S99-105. 

Does not include original data 

16. Anonymous. Diet, exercise delay type 2 

diabetes. FDA Consumer 2001;35(5):10-11. 

Does not apply to a key question 

17. Anonymous. Glyburide vs insulin for 

gestational diabetes. Nurses' Drug Alert 

2000;24(12):91. 

Does not include original data 

18. Anonymous. Insulin for gestational diabetes. 

Emergency Medicine 1990;22(17):45. 

Does not include original data 

19. Anonymous. Reducing the risks in gestational 

diabetes. Emergency Medicine 1990;22(3):113. 

Does not include original data 

20. Abell D A, Beischer N A, Wood C. Routine 

testing for gestational diabetes, pregnancy 

hypoglycemia and fetal growth retardation, and 

results of treatment. J Perinat Med 

1976;4(4):197-212. 

Diagnosis of gestational diabetes not 

confirmed 

21. Aberg A E, Jonsson E K, Eskilsson I et al. 

Predictive factors of developing diabetes 

mellitus in women with gestational diabetes. 

Acta Obstet Gynecol Scand 2002;81(1):11-6. 

Does not evaluate risk factors for type 2 

diabetes 
D-2 

22. Adam P A, Schwartz R. Diagnosis and 

treatment: should oral hypoglycemic agents be 

used in pediatric and pregnant patients? 

Pediatrics 1968;42(5):819-823. 

Does not include original data 

23. Agarwal S, Gupta A N. Gestational diabetes. J 

Assoc Physicians India 1982;30(4):203-5. 

No appropriate comparison group for KQ1 

24. Agrawal R K, Lui K, Gupta J M. Neonatal 

hypoglycaemia in infants of diabetic mothers. J 

Paediatr Child Health 2000;36(4):354-6. 

Does not have a comparison of interest 

25. Akiel A S, Laajam M A, Moghraby S et al. 

Clinical experience with diabetic pregnancy in 

Riyadh: Analysis of 357 cases. Ann. Saudi 

Med. 1990;10(3):308-312. 

No appropriate comparison group for KQ1 

26. al-Najashi S S. Control of gestational diabetes. 

Int J Gynaecol Obstet 1995;49(2):131-5. 

Other 

27. Albareda M, Caballero A, Badell G et al. 

Diabetes and abnormal glucose tolerance in 

women with previous gestational diabetes. 

Diabetes Care 2003;26(4):1199-205. 

Does not evaluate risk factors for type 2 

diabetes 

28. Albareda M, Caballero A, Badell G et al. 

Metabolic syndrome at follow-up in women 

with and without gestational diabetes mellitus in 

index pregnancy. Metabolism 2005;54(8):1115-

21. 

No relevant risk factor for KQ3 

29. Albareda M, De Leiva A, Corcoy R. 

Reproducibility of diabetes mellitus diagnosis 

(WHO 1999 criteria) in women. Acta Diabetol. 

2004;41(1):14-17. 

Not evaluating people with gestational 

diabetes 

30. Aldridge V, Temple R. Improving outcomes in 

diabetic pregnancies -- a challenge for all. 

Diabetes Primary Care 2000;2(2):38-41. 

Other 

31. Ali Z, Alexis S D. Occurrence of diabetes 

mellitus after gestational diabetes mellitus in 

Trinidad. Diabetes Care 90;13(5):527-9. 

Does not evaluate risk factors for type 2 

diabetes 

32. Altman J-J, Brun J-M, Chanson P et al. 

Multicenter survey of diabetic pregnancy in 

France. Diabetes Care 91;14(11):994-1000. 

Does not apply to a key question 

33. Alur P, Kodiyanplakkal P, Del Rosario A et al. 

Epidemiology of infants of diabetic mothers in 

indigent Micronesian population-Guam 

experience. Pac Health Dialog 2002;9(2):219-

221. 

Diagnosis of gestational diabetes not 

confirmed 

34. Arnold J M, Bromham D R, Burke B J. 

Induction of labour in pregnant diabetics using 

vaginal prostaglandin E2 pessaries. J. Obstet. 

Gynaecol. 1982;3(2):75-78. 

Does not apply to a key question 

35. Athukorala C, Crowther C A, Willson K. 

Women with gestational diabetes mellitus in the 

ACHOIS trial: Risk factors for shoulder 

dystocia. Aust N Z J Obstet Gynaecol 

2007;47(1):37-41. 

Does not apply to a key question 

36. Banerjee S, Ghosh U S, Banerjee D. Effect of 

tight glycaemic control on fetal complications in 

diabetic pregnancies. J Assoc Physicians India 

2004;52:109-13. 

Does not apply to a key question 

37. Banerjee S, Ghosh U S, Banerjee D. 

Foetomaternal complications in pregnancies 

with diabetes mellitus: association with the 

amount of insulin requirement, mean terminal 

blood glucose and HbA1C levels. J Indian Med 

Assoc 2003;101(12):728, 730-2, 740. 

No appropriate comparison group for KQ1 

38. Banerjee T. Diabetes in pregnancy. J Indian 

Med Assoc 76;67(11):247-50. 

Does not include original data 

39. Barahona M J, Sucunza N, Garcia-Patterson A 

et al. Period of gestational diabetes mellitus 

diagnosis and maternal and fetal morbidity. 

Acta Obstet Gynecol Scand 2005;84(7):622-7. 

No appropriate comparison group for KQ1 

40. Barnett R V. Diabetes in pregnancy. The 

obstetrician's dilemma. Ala J Med Sci 

1972;9(3):282-8. 

Does not include original data 
D-3 

41. Bartha J L, Martinez-del-Fresno P, CominoDelgado R. Postpartum metabolism and 

autoantibody markers in women with 

gestational diabetes mellitus diagnosed in early 

pregnancy. Am J Obstet Gynecol 

2001;184(5):965-70. 

Does not report a relative measure 

42. Bassaw B, Ataullah I, Roopnarinesingh S et al. 

Diabetes in pregnancy. Int J Gynaecol Obstet 

1995;50(1):5-9. 

Does not apply to a key question 

43. Bastian J S. Diabetic control in pregnancy. Am 

J Obstet Gynecol 1988;158(3 Pt 1):677-678. 

Does not include original data 

44. Bates G W. Management of gestational 

diabetes. Postgrad Med 1974;55(6):55-8. 

Does not include original data. 

45. Beischer N A, Cookson T, Sheedy M et al. 

Norethisterone and gestational diabetes. Aust N 

Z J Obstet Gynaecol 1992;32(3):233-8. 

Diagnosis of gestational diabetes not 

confirmed 

46. Beischer N A, Wein P, Sheedy M T et al. 

Studies of postnatal diabetes mellitus in women 

who had gestational diabetes. Part 1. Estimation 

of the prevalence of unrecognized prepregnancy 

diabetes mellitus. Aust N Z J Obstet Gynaecol 

1997;37(4):412-9. 

No relevant risk factor for KQ3 

47. Beischer N A, Wein P, Sheedy M T et al. 

Prevalence of antibodies to glutamic acid 

decarboxylase in women who have had 

gestational diabetes. Am J Obstet Gynecol 

1995;173(5):1563-9. 

Diagnosis of gestational diabetes not 

confirmed 

48. Bellmann O. Therapy of gestational diabetes. 

Acta Endocrinol Suppl (Copenh) 1986;27750-5. 

Does not have a comparison of interest 

49. Ben Slama C, Nsiri B, Bouguerra R et al. 

Diabetic pregnancy in over 35 years old women. 

Ann Ist Super Sanita 1997;33(3):313-6. 

Does not apply to a key question 

50. Benito J A, Melchor J C, Cortazar A et al. 

Gestational diabetes: maternal profile and 

perinatal outcome according to the insulin 

therapy. Prog. Obstet. Ginecol. 1996;39(2):103-

108. 

Not written in English 

51. Benjamin E, Winters D, Mayfield J et al. 

Diabetes in pregnancy in Zuni Indian women. 

Prevalence and subsequent development of 

clinical diabetes after gestational diabetes. 

Diabetes Care 1993;16(9):1231-5. 

Other 

52. Berkowitz G S, Roman S H, Lapinski R H et al. 

Maternal characteristics, neonatal outcome, and 

the time of diagnosis of gestational diabetes. 

Am J Obstet Gynecol 1992;167(4 Pt 1):976-82. 

Does not apply to a key question 

53. Bernstein I M, Catalano P M. Examination of 

factors contributing to the risk of cesarean 

delivery in women with gestational diabetes. 

Obstet Gynecol 1994;83(3):462-5. 

No appropriate comparison group for KQ1 

54. Bevier W C, Jovanovic-Peterson L, Burns A et 

al. Blood pressure predicts insulin requirement 

and exogenous insulin is associated with 

increased blood pressure in women with 

gestational diabetes mellitus. Am J Perinatol 

1994;11(5):369-73. 

Does not have a comparison of interest 

55. Bhattacharyya A, Vice P A. Insulin lispro, 

pregnancy, and retinopathy. Diabetes Care 

1999;22(12):2101-2104. 

Not evaluating people with gestational 

diabetes 

56. Bhattacharyya A, Brown S, Hughes S et al. 

Insulin lispro and regular insulin in pregnancy. 

QJM 2001;94(5):255-60. 

Diagnosis of gestational diabetes not 

confirmed 

57. Blackwell S C, Hassan S S, Wolfe H W et al. 

Why are cesarean delivery rates so high in 

diabetic pregnancies? J Perinat Med 

2000;28(4):316-20. 

No appropriate comparison group for KQ1 

58. Bloomgarden Z T. Aspects of type 2 diabetes 

and related insulin-resistant states. Diabetes 

Care 2006;29(3):732-40. 

Does not include original data 
D-4 

59. Bo S, Monge L, Macchetta C et al. Prior 

gestational hyperglycemia: a long-term 

predictor of the metabolic syndrome. J 

Endocrinol Invest 2004;27(7):629-35. 

Not evaluating people with gestational 

diabetes 

60. Bochner C J, Medearis A L, Williams J et al. 

Early third-trimester ultrasound screening in 

gestational diabetes to determine the risk of 

macrosomia and labor dystocia at term. Am J 

Obstet Gynecol 1987;157(3):703-8. 

No appropriate comparison group for KQ1 

61. Bonomo M, Cetin I, Pisoni M P et al. Flexible 

treatment of gestational diabetes modulated on 

ultrasound evaluation of intrauterine growth: a 

controlled randomized clinical trial. Diabetes 

Metab 2004;30(3):237-44. 

Does not have a comparison of interest 

62. Bonomo M, Mion E, Greco P et al. Maternal 

glycometabolic optimization and pregnancy 

outcome in gestational diabetes mellitus. 

Diabetes Nutr. Metab. Clin. Exp. 1998;11(1):1-

7. 

Other 

63. Botta R M, Di Giovanni B M, Cammilleri F et 

al. Predictive factors for insulin treatment in 

women with diagnosis of gestational diabetes. 

Ann Ist Super Sanita 1997;33(3):403-6. 

Does not have a comparison of interest 

64. Bracero L A, Cassidy S, Byrne D W. Effect of 

gender on perinatal outcome in pregnancies 

complicated by diabetes. Gynecol. Obstet. 

Invest. 1996;41(1):10-14. 

Not evaluating people with gestational 

diabetes 

65. Brown F M, Wyckoff J, Rowan J A et al. 

Metformin in pregnancy: its time has not yet 

come. Diabetes Care 2006;29(2):485-6. 

Does not include original data 

66. Brown Z A, Mills J L, Metzger B E et al. Early 

sonographic evaluation for fetal growth delay 

and congenital malformations in pregnancies 

complicated by insulin-requiring diabetes. 

Diabetes Care 1992;15(5):613-619. 

Does not apply to a key question 

67. Brudenell J M. Delivering the baby of the 

diabetic mother. J R Soc Med 1978;71(3):207-

211. 

No appropriate comparison group for KQ1 

68. Buchanan T A. Birth defects in diabetic 

pregnancies: where do we go from here? Eur J 

Endocrinol 1996;134(4):395-7. 

Does not include original data 

69. Buchanan T A, Kjos S L. Diabetes and 

pregnancy. Curr Ther Endocrinol Metab 

1994;5278-83. 

Does not include original data 

70. Buchanan T A, Kjos S L, Montoro M N et al. 

Use of fetal ultrasound to select metabolic 

therapy for pregnancies complicated by mild 

gestational diabetes. Diabetes Care 

1994;17(4):275-83. 

Diagnosis of gestational diabetes not 

confirmed 

71. Buchanan T A, Xiang A, Kjos S L et al. 

Gestational diabetes: Antepartum characteristics 

predict postpartum glucose intolerance and type 

2 diabetes in Latino women. Diabetes 

1998;47(8):1302-1310. 

Other 

72. Burkart W, Hanker J P, Schneider H P G. 

Complications and fetal outcome in diabetic 

pregnancy. Intensified conventional versus 

insulin pump therapy. Gynecol. Obstet. Invest. 

1988;26(2):104-112. 

Not evaluating people with gestational 

diabetes 

73. Byrne M M, Sturis J, O'Meara N M et al. 

Insulin secretion in insulin-resistant women 

with a history of gestational diabetes. 

Metabolism 1995;44(8):1067-73. 

Other 

74. Camm J. Babies at risk from mothers' diabetes. 

RCM Midwives 2005;8(11):442. 

Does not include original data 

75. Carpenter M W, Coustan D R, Widness J A et 

al. Postpartum testing for antecedent gestational 

diabetes. Am J Obstet Gynecol 

1988;159(5):1128-31. 

Other 
D-5 

76. Carr D B, Utzschneider K M, Hull R L et al. 

Gestational diabetes mellitus increases the risk 

of cardiovascular disease in women with a 

family history of type 2 diabetes. Diabetes Care 

2006;29(9):2078-83. 

Other 

77. Carrington E R. Diabetes in pregnancy. Clin 

Obstet Gynecol 1973;16(1):28-46. 

Does not include original data 

78. Caruso A, Lanzone A, Bianchi V et al. 

Continuous subcutaneous insulin infusion 

(CSII) in pregnant diabetic patients. Prenat 

Diagn 1987;7(1):41-50. 

Other 

79. Cassano F. The treatment of diabetics and 

prediabetics in pregnancy. Folia Endocrinol 

1966;19(1):1-6. 

Not evaluating people with gestational 

diabetes 

80. Catalano P M, Bernstein I M, Wolfe R R et al. 

Subclinical abnormalities of glucose 

metabolism in subjects with previous 

gestational diabetes. Am J Obstet Gynecol 

1986;155(6):1255-62. 

Other 

81. Catalano P M, Vargo K M, Bernstein I M et al. 

Incidence and risk factors associated with 

abnormal postpartum glucose tolerance in 

women with gestational diabetes. Am J Obstet 

Gynecol 1991;165(4 Pt 1):914-9. 

Other. 

82. Cheung N W, Oats J J, McIntyre H D. 

Australian carbohydrate intolerance study in 

pregnant women: implications for the 

management of gestational diabetes. Aust N Z J 

Obstet Gynaecol 2005;45(6):484-5. 

Does not include original data 

83. Chin R K. Hypertensive disorders of pregnancy 

and gestational diabetes mellitus in mature 

gravidae. Br J Clin Pract 1990;44(12):560-1. 

Does not apply to a key question 

84. Chollet MB, Pettitt DJ. Treatment of gestational 

diabetes mellitus. Clinical Diabetes 

2006;24(1):35-36. 

No appropriate comparison group for KQ1 

85. Chung J H, Voss K J, Caughey A B et al. Role 

of patient education level in predicting 

macrosomia among women with gestational 

diabetes mellitus. J Perinatol 2006;26(6):328-

32. 

Diagnosis of gestational diabetes not 

confirmed 

86. Cocilovo G, Tomasi F, Guerra S et al. Risk 

factors associated with persistence of glucose 

intolerance one year after gestational diabetes. 

Diabete Metab 1990;16(3):187-91. 

Other 

87. Coetzee E J, Jackson W P. Diabetes newly 

diagnosed during pregnancy: A 4-year study at 

Groote Schuur Hospital. S Afr Med J 

1979;56(12):467-75. 

Diagnosis of gestational diabetes not 

confirmed 

88. Cohen A M, Schenker J G. The effect of insulin 

treatment on fetal mortality and congenital 

malformations in diabetic pregnant women. Adv 

Exp Med Biol 1972;27(-):377-381. 

No appropriate comparison group for KQ1 

89. Cole H S, Bilder J H, Camerini-Davalos R A et 

al. Glucose tolerance, insulin and growth 

hormone in infants of gestational diabetic 

mothers. Pediatrics 1970;45(3):394-403. 

Does not apply to a key question 

90. Collins V R, Dowse G K, Zimmet P Z. 

Evidence against association between parity and 

NIDDM from five population groups. Diabetes 

Care 1991;14(11):975-81. 

Not evaluating people with gestational 

diabetes 

91. Comtois R, Seguin M C, Aris-Jilwan N et al. 

Comparison of obese and non-obese patients 

with gestational diabetes. Int J Obes Relat 

Metab Disord 1993;17(10):605-8. 

Does not apply to a key question 

92. Corcoy R, Garcia-Patterson A, Albareda M et 

al. Poor performance of American Diabetes 

Association criteria in women with gestational 

diabetes. Diabetes Care 2000;23(3):430-1. 

Does not include original data 

93. Coustan D R. Maternal insulin to lower the risk 

of fetal macrosomia in diabetic pregnancy. Clin. 

Obstet. Gynecol. 1991;34(2):288-295. 

Does not include original data 
D-6 

94. Coustan D R, Carpenter M W. Detection and 

treatment of gestational diabetes. Clin Obstet 

Gynecol 1985;28(3):507-15. 

Does not include original data 

95. Coustan D R, Imarah J. Prophylactic insulin 

treatment of gestational diabetes reduces the 

incidence of macrosomia, operative delivery, 

and birth trauma. Am J Obstet Gynecol 

1984;150(7):836-42. 

Does not have a comparison of interest 

96. Coustan D R, Lewis S B. Insulin therapy for 

gestational diabetes. Obstet Gynecol 

1978;51(3):306-10. 

Does not have a comparison of interest 

97. Coustan D R, Carpenter M W, O'Sullivan P S et 

al. Gestational diabetes: predictors of 

subsequent disordered glucose metabolism. Am 

J Obstet Gynecol 1993;168(4):1139-44; 

discussion 1144-5. 

Does not evaluate risk factors for type 2 

diabetes 

98. Coustan D R, Reece E A, Sherwin R S. A 

randomized clinical trial of the insulin pump vs 

intensive conventional therapy in diabetic 

pregnancies. J. Am. Med. Assoc. 

1986;255(5):631-636. 

Not evaluating people with gestational 

diabetes 

99. Crowther C A, Hiller J E, Moss J R et al. Effect 

of treatment of gestational diabetes mellitus on 

pregnancy outcomes. N Engl J Med 

2005;352(24):2477-86. 

No appropriate comparison group for KQ1 

100. Cuasay L C, Lee E S, Orlander P P et al. 

Prevalence and determinants of type 2 diabetes 

among Filipino-Americans in the Houston, 

Texas metropolitan statistical area. Diabetes 

Care 2001;24(12):2054-8. 

Does not include original data 

101. Cundy T, Ducker L, Wrathall K et al. 

Agreement between old and new diagnostic 

criteria in postpartum testing of women with 

gestational diabetes. Diabetes Care 

1998;21(9):1579-80. 

Does not include original data 

102. Cundy T, Gamble G, Manuel A et al. 

Determinants of birth-weight in women with 

established and gestational diabetes. Aust N Z J 

Obstet Gynaecol 1993;33(3):249-54. 

Does not apply to a key question 

103. Cypryk K, Sobczak M, Pertynska-Marczewska 

M et al. Pregnancy complications and perinatal 

outcome in diabetic women treated with 

Humalog (insulin lispro) or regular human 

insulin during pregnancy. Med. Sci. Monit. 

2004;10(2):PI29-PI32. 

Not evaluating people with gestational 

diabetes 

104. Czeszynska M B, Ronin-Walknowska E. 

Maternal glycemic control, cord blood insulin 

and erythropoietin levels in relation to 

indications for Cesarean section in diabetic 

pregnancy. Prenat. Neonatal Med. 

2000;5(4):236-242. 

Not evaluating people with gestational 

diabetes 

105. Dalfra M G, Lapolla A, Masin M et al. 

Antepartum and early postpartum predictors of 

type 2 diabetes development in women with 

gestational diabetes mellitus. Diabetes Metab 

2001;27(6):675-80. 

Does not report a relative measure 

106. Damm P. Gestational diabetes mellitus and 

subsequent development of overt diabetes 

mellitus. Dan Med Bull 1998;45(5):495-509. 

Does not include original data 

107. Damm P, Kuhl C, Hornnes P et al. A 

longitudinal study of plasma insulin and 

glucagon in women with previous gestational 

diabetes. Diabetes Care 1995;18(5):654-65. 

Diagnosis of gestational diabetes not 

confirmed 

108. Dandolu V. Increasis in the rate of shoulder 

dystocia. J Matern Fetal Neonatal Med 

2006;19(5):315, author reply 315-6. 

Does not include original data. 

109. Dandona P, Besterman H S, Freedman D B. 

Continuous subcutaneous infusion of insulin 

(CSII) during pregnancy and fetal size. Pract. 

Diabetes 1986;3(1):33-35. 

Not evaluating people with gestational 

diabetes 
D-7 

110. Dandrow R V, O'Sullivan J B. Obstetric hazards 

of gestational diabetes. Am J Obstet Gynecol 

1966;96(8):1144-7. 

Does not apply to a key question 

111. Davis C L, Gutt M, Llabre M M et al. History 

of gestational diabetes, insulin resistance and 

coronary risk. J Diabetes Complications 

1999;13(4):216-23. 

Other 

112. De Muylder X. Perinatal complications of 

gestational diabetes: the influence of the timing 

of the diagnosis. Eur J Obstet Gynecol Reprod 

Biol 1984;18(1-2):35-42. 

Does not have a comparison of interest 

113. De Veciana M, Major CA, Morgan MA et al. 

Postprandial vs preprandial blood glucose 

monitoring in women with gestational diabetes 

mellitus requiring insulin therapy. New England 

Journal of Medicine 1995;333:1237-1241. 

No appropriate comparison group for KQ1 

114. Delaney J J, Ptacek J. Three decades of 

experience with diabetic pregnancies. Am J 

Obstet Gynecol 1970;106(4):550-556. 

No appropriate comparison group for KQ1 

115. Delpapa E H, Mueller-Heubach E. Pregnancy 

outcome following ultrasound diagnosis of 

macrosomia. Obstet Gynecol 1991;78(3 Pt 

1):340-3. 

Not evaluating people with gestational 

diabetes 

116. Di Cianni G, Benzi L, Bottone P et al. Neonatal 

outcome and obstetric complications in women 

with gestational diabetes: effects of maternal 

body mass index. Int J Obes Relat Metab Disord 

1996;20(5):445-9. 

Does not apply to a key question 

117. Di Rado A. Insulating against resistance: recent 

insights into the risk factors predisposing people 

to type 2 diabetes are leading researchers to new 

prevention and treatment strategies. USC Health 

2001;9(1):10-13. 

Does not include original data 

118. Diamond M P, Salyer S L, Boehm F H et al. 

Congenital anomalies in offspring of insulindependent diabetic mothers. Diabetes Educ 

1986;12(3):272-276. 

Not evaluating people with gestational 

diabetes 

119. Dixon G. Management of diabetes in 

pregnancy. Midwife Health Visit 

1974;10(10):304-7, 310-2. 

Does not apply to a key question 

120. Dolger H, Bookman J J, Nechemias C. The 

Management Of Diabetes In Pregnancy. J Mt 

Sinai Hosp N Y 1963;30:479-90. 

Does not include a medication of interest for 

KQ1 

121. Dong Z G, Beischer N A, Wein P et al. Value of 

early glucose tolerance testing in women who 

had gestational diabetes in their previous 

pregnancy. Aust N Z J Obstet Gynaecol 

1993;33(4):350-7. 

Diagnosis of gestational diabetes not 

confirmed 

122. Dooley S L, Metzger B E, Cho N H. Gestational 

diabetes mellitus. Influence of race on disease 

prevalence and perinatal outcome in a U.S. 

population. Diabetes 1991;40(Suppl 2):25-9. 

Does not apply to a key question 

123. Dorner T, Rathmanner T, Lechleitner M et al. 

Public health aspects of diabetes mellitus--

epidemiology, prevention strategies, policy 

implications: the first Austrian diabetes report. 

Wien Klin Wochenschr 2006;118(17-18):513-9. 

Does not include original data 

124. Dornhorst A. A comparison of glyburide and 

insulin in women with gestational diabetes 

mellitus. Diabet Med 2001;Suppl 3:12-4. 

Does not include original data 

125. Dornhorst A, Frost G. The potential for dietary 

intervention postpartum in women with 

gestational diabetes. Diabetes Care 

1997;20(11):1635-7. 

Does not apply to a key question 

126. Dornhorst A, Rossi M. Risk and prevention of 

type 2 diabetes in women with gestational 

diabetes. Diabetes Care 1998;21 (Suppl 2):B43-

9. 

Does not include original data 

127. Dornhorst A, Bailey P C, Anyaoku V et al. 

Abnormalities of glucose tolerance following 

gestational diabetes. Q J Med 

1990;77(284):1219-28. 

Diagnosis of gestational diabetes not 

confirmed 
D-8 

128. Drexel H, Bichler A, Sailer S et al. Prevention 

of perinatal morbidity by tight metabolic control 

in gestational diabetes mellitus. Diabetes Care 

1988;11(10):761-8. 

Does not have a comparison of interest 

129. Driscoll J J, Gillespie L. Obstetrical 

Considerations In Diabetes In Pregnancy. Med 

Clin North Am 1965;49:1025-34. 

Does not include original data 

130. Dunne F. Gestational diabetes. Diabet Med 

2004;21 (Suppl 3):6-8. 

Does not include original data 

131. Durnwald C, Landon M B. Glyburide: the new 

alternative for treating gestational diabetes? Am 

J Obstet Gynecol 2005;193(1):1-2. 

Does not include original data 

132. Dutta R, Kulenthran A, Sivanesaratnam V et al. 

Management of pregnancy complicated by 

diabetes mellitus: experience at the University 

Hospital, Kuala Lumpur. Asia Oceania J Obstet 

Gynaecol 1988;14(3):307-311. 

Other 

133. Ecker J L, Greenberg J A, Norwitz E R et al. 

Birth weight as a predictor of brachial plexus 

injury. Obstet Gynecol 1997;89(5 Pt 1):643-7. 

Not evaluating people with gestational 

diabetes 

134. Ecker J L, Mascola M A, Riley L E. Gestational 

diabetes. N Engl J Med 2000;342(12):896-7. 

Does not include original data 

135. Efendic S, Hanson U, Persson B et al. Glucose 

tolerance, insulin release, and insulin sensitivity 

in normal-weight women with previous 

gestational diabetes mellitus. Diabetes 

1987;36(4):413-9. 

Other 

136. Egeland G M, Skjaerven R, Irgens L M. Birth 

characteristics of women who develop 

gestational diabetes: population based study. 

BMJ 2000;321(7260):546-7. 

Does not apply to a key question 

137. Ehrenberg H M, Durnwald C P, Catalano P et 

al. The influence of obesity and diabetes on the 

risk of cesarean delivery. Am J Obstet Gynecol 

2004;191(3):969-74. 

Not evaluating people with gestational 

diabetes 

138. Ehrenberg H M, Mercer B M, Catalano P M. 

The influence of obesity and diabetes on the 

prevalence of macrosomia. Am J Obstet 

Gynecol 2004;191(3):964-8. 

Does not have a comparison of interest 

139. el-Shafei A M, Bashmi Y A, Beischer N A et al. 

Incidence and severity of gestational diabetes in 

Bahrain and Australia. Aust N Z J Obstet 

Gynaecol 1989;29(3 Pt 1):204-8. 

Diagnosis of gestational diabetes not 

confirmed 

140. Elliott J P, Garite T J, Freeman R K. Ultrasonic 

prediction of fetal macrosomia in diabetic 

patients. Obstetrics and Gynecology: Obstet. 

Gynecol. 1982;60(2):159-162. 

Not evaluating people with gestational 

diabetes 

141. Elliott P. A review of the significance of 

gestational diabetes. Aust N Z J Obstet 

Gynaecol 1978;18(1):21-7. 

Does not apply to a key question 

142. Fallucca F, Di Mario U, Gargiulo P et al. 

Humoral immunity in diabetic pregnancy: 

interrelationships with maternal/neonatal 

complications and maternal metabolic control. 

Diabete Metab 1985;11(6):387-95. 

Diagnosis of gestational diabetes not 

confirmed 

143. Fan Z T, Yang H X, Gao X L et al. Pregnancy 

outcome in gestational diabetes. Int J Gynaecol 

Obstet 2006;94(1):12-6. 

Does not have a comparison of interest 

144. Farrag O A. Prospective study of 3 metabolic 

regimens in pregnant diabetics. Aust N Z J 

Obstet Gynaecol 1987;27(1):6-9. 

Not evaluating people with gestational 

diabetes 

145. Farrell J, Forrest J M, Storey G N et al. 

Gestational diabetes--infant malformations and 

subsequent maternal glucose tolerance. Aust N 

Z J Obstet Gynaecol 1986;26(1):11-6. 

No appropriate comparison group for KQ1 

146. Farrell T, Fraser R, Chan K. Ultrasonic fetal 

weight estimation in women with pregnancy 

complicated by diabetes. Acta Obstet Gynecol 

Scand 2004;83(11):1065-6. 

Not evaluating people with gestational 

diabetes 
D-9 

147. Feinstein U, Sheiner E, Levy A et al. Risk 

factors for arrest of descent during the second 

stage of labor. Int J Gynaecol Obstet 

2002;77(1):7-14. 

Does not have a comparison of interest 

148. Feldberg D, Dicker D, Samuel N et al. 

Intrapartum management of insulin-dependent 

diabetes mellitus (IDDM) gestants. A 

comparative study of constant intravenous 

insulin infusion and continuous subcutaneous 

insulin infusion pump (CSIIP). Acta Obstet. 

Gynecol. Scand. 1988;67(4):333-338. 

Not evaluating people with gestational 

diabetes 

149. Fines Verlee, Moore Thomas, Castle Shannon. 

A comparison of glyburide and insulin 

treatment in gestational diabetes mellitus on 

infant birth weight and adiposity: SMFM 

abstracts. American Journal of Obstetrics and 

Gynecology 2003;189(6, Supplement 1):S108. 

Does not include original data 

150. Fisher P M, Sutherland H W, Bewsher P D. The 

insulin response to glucose infusion in 

gestational diabetes. Diabetologia 

1980;19(1):10-4. 

Does not apply to a key question 

151. Fitz-Patrick D. Autoimmunity in "type 2" and 

gestational diabetes mellitus. Endocr Pract 

2001;7(5):407-8. 

Does not apply to a key question 

152. Forbes S, Moonan M, Robinson S et al. 

Impaired circulating glucagon-like peptide-1 

response to oral glucose in women with 

previous gestational diabetes. Clin Endocrinol 

(Oxf) 2005;62(1):51-5. 

Does not evaluate a relevant maternal or 

neonatal outcome 

153. Foster-Powell K A, Cheung N W. Recurrence 

of gestational diabetes. Aust N Z J Obstet 

Gynaecol 1998;38(4):384-7. 

Does not evaluate a relevant maternal or 

neonatal outcome 

154. Fraser R. Diabetic control in pregnancy and 

intrauterine growth of the fetus. Br J Obstet 

Gynaecol 1995;102(4):275-7. 

Does not include original data 

155. Fraser R. Diabetes in pregnancy. Arch Dis 

Child Fetal Neonatal Ed 1994;71(3):F224-30. 

Does not include original data 

156. Fraser R. Gestational diabetes: After the 

ACHOIS trial. Diabetic Med. 2006;23(SUPPL. 

1):8-11. 

Does not include original data 

157. Freilich T H. Management of the pregnant 

woman with diabetes. J Am Osteopath Assoc 

1970;69(12):1221-1224. 

Case report or case series of less than 50 

cases 

158. Friedlander A H, Chaudhuri G, Altman L. A 

past medical history of gestational diabetes: its 

medical significance and its dental implications. 

Oral Surg Oral Med Oral Pathol Oral Radiol 

Endod 2007;103(2):157-63. 

Does not include original data 

159. Friedman J E, Ishizuka T, Shao J et al. Impaired 

glucose transport and insulin receptor tyrosine 

phosphorylation in skeletal muscle from obese 

women with gestational diabetes. Diabetes 

99;48(9):1807-14. 

Does not evaluate a relevant maternal or 

neonatal outcome 

160. Gabbe SG, Graves CR. Management of diabetes 

mellitus complicating pregnancy. Obstetrics & 

Gynecology 2003;102(4):857-868. 

Does not include original data 

161. Gaillard T R, Schuster D P, Bossetti B M et al. 

Do sociodemographics and economic status 

predict risks for type II diabetes in African 

Americans? Diabetes Educ 1997;23(3):294-300. 

Not evaluating people with gestational 

diabetes 

162. Gamson K, Chia S, Jovanovic L. The safety and 

efficacy of insulin analogs in pregnancy. J. 

Matern.-Fetal Neonatal Med. 2004;15(1):26-34. 

Does not include original data 

163. Garcia-Patterson A, Martin E, Ubeda J et al. 

Evaluation of light exercise in the treatment of 

gestational diabetes. Diabetes Care 

2001;24(11):2006-7. 

Does not apply to a key question 
D-10 

164. Gasic S, Winzer C h, Bayerle-Eder M et al. 

Impaired cardiac autonomic function in women 

with prior gestational diabetes mellitus. Eur J 

Clin Invest 2007;37(1):42-7. 

Does not evaluate a relevant maternal or 

neonatal outcome. 

165. Gillmer M D, Persson B. Metabolism during 

normal and diabetic pregnancy and its effect on 

neonatal outcome. Ciba Found Symp 

1978;(63):93-126. 

No appropriate comparison group for KQ1 

166. Gillmer M D, Maresh M, Beard R W et al. Low 

energy diets in the treatment of gestational 

diabetes. Acta Endocrinol Suppl (Copenh) 

1986;277:44-9. 

Diagnosis of gestational diabetes not 

confirmed 

167. Goetzl L, Wilkins I. Glyburide compared to 

insulin for the treatment of gestational diabetes 

mellitus: a cost analysis (Provisional record). 

Journal of Perinatology 2002;22(5):403-406. 

Does not evaluate a relevant maternal or 

neonatal outcome 

168. Gojnic M, Pervulov M, Petkovic S et al. 

Acceleration of fetal maturation by oxytocinproduced uterine contraction in pregnancies 

complicated with gestational diabetes mellitus: 

a preliminary report. J Matern Fetal Neonatal 

Med 2004;16(2):111-4. 

Case report or case series of less than 50 

cases 

169. Goldberg J D, Franklin B, Lasser D et al. 

Gestational diabetes: impact of home glucose 

monitoring on neonatal birth weight. Am J 

Obstet Gynecol 1986;154(3):546-50. 

Does not include a medication of interest for 

KQ1 

170. Goldkrand J W, Lin J Y. Large for gestational 

age: dilemma of the infant of the diabetic 

mother. J Perinatol 1987;7(4):282-7. 

Not evaluating people with gestational 

diabetes 

171. Goldman M, Kitzmiller J L, Abrams B et al. 

Obstetric complications with GDM. Effects of 

maternal weight. Diabetes 1991;40 (Suppl 

2):79-82. 

No appropriate comparison group for KQ1 

172. Gonen R, Bader D, Ajami M. Effects of a policy 

of elective cesarean delivery in cases of 

suspected fetal macrosomia on the incidence of 

brachial plexus injury and the rate of cesarean 

delivery. Am J Obstet Gynecol 

2000;183(5):1296-300. 

Not evaluating people with gestational 

diabetes 

173. Gonzalez JL. Management of diabetes in 

pregnancy. Clinical Obstetrics & Gynecology 

2002;45(1):165-171. 

Does not include original data 

174. Gonzalez S, Mlinarevich N, MichalskiRimington A N et al. The Latina gestational 

diabetes mellitus pilot study: Baseline data. 

Hisp. Healthc. Int. 2005;3(1):21-26. 

Does not apply to a key question 

175. Grandis A S, Morris M A, Litton J C. 

Gestational diabetes: maternal response to diet 

and insulin therapy as reflected by glycosylated 

hemoglobin concentration. Am J Obstet 

Gynecol 1987;157(5):1118-21. 

Does not have a comparison of interest 

176. Grasso S, Roversi G D. Oversized infant of 

diabetic mother: its cause and prevention. J 

Perinat Med 1987;15(1):73-82. 

Does not apply to a key question 

177. Grasso S, Roversi G D. Oversized infants of 

diabetic mothers: Cause and prevention. J. 

Perinat. Med. 1987;15(1):73-82. 

Does not include a medication of interest for 

KQ1 

178. Greene M F. Oral hypoglycemic drugs for 

gestational diabetes. N Engl J Med 

2000;343(16):1178-9. 

Does not include original data 

179. Greene M F, Solomon C G. Gestational diabetes 

mellitus -- time to treat. N Engl J Med 

2005;352(24):2544-6. 

Does not include original data 

180. Gruendhammer M, Brezinka C, Lechleitner M. 

The number of abnormal plasma glucose values 

in the oral glucose tolerance test and the fetomaternal outcome of pregnancy. Eur J Obstet 

Gynecol Reprod Biol 2003;108(2):131-6. 

No appropriate comparison group for KQ1 
D-11 

181. Gyves M T, Rodman H M, Little A B et al. A 

modern approach to management of pregnant 

diabetics: a two-year analysis of perinatal 

outcomes. Am J Obstet Gynecol 

1977;128(6):606-16. 

Does not apply to a key question 

182. Gyves M T, Schulman P K, Merkatz I R. 

Results of individualized intervention in 

gestational diabetes. Diabetes Care 

1980;3(3):495-6. 

Does not apply to a key question 

183. Hadden D R, Alexander A, McCance D R et al. 

Obstetric and diabetic care for pregnancy in 

diabetic women: 10 Years outcome analysis, 

1985-1995. Diabetic Med. 2001;18(7):546-553. 

Does not include original data 

184. Hamada T, Yoshimatsu K, Ooshima T et al. The 

influence of age on glucose tolerance during 

pregnancy. Kurume Med J 1985;32(4):279-283. 

Not evaluating people with gestational 

diabetes 

185. Hanley A J G, Harris S B, Zinman B. 

Application of the revised American Diabetes 

Association criteria for the diagnosis of diabetes 

in a Canadian native population [4]. Diabetes 

Care: Diabetes Care 1998;21(5):870-871. 

Does not include original data 

186. Hanson U, Persson B, Stangenberg M. Factors 

influencing neonatal morbidity in diabetic 

pregnancy. Diabetes Res. 1986;3(2):71-76. 

Not evaluating people with gestational 

diabetes 

187. Hanson U, Persson B, Hartling S G et al. 

Increased molar proinsulin-to-insulin ratio in 

women with previous gestational diabetes does 

not predict later impairment of glucose 

tolerance. Diabetes Care 1996;19(1):17-20. 

Other 

188. Harnett M, Datta S. Diabetes in pregnancy. 

Seminars in Anesthesia, Perioperative Medicine 

& Pain 2000;19(3):188-195. 

Does not include original data 

189. Harris J L. Diabetes mellitus in pregnancy. 

West J Med 1992;156(6):647-8. 

Does not include original data 

190. Hawthorne G, Irgens LM, Lie RT. Outcome of 

pregnancy in diabetic women in northeast 

England and in Norway, 1994-7. BMJ: British 

Medical Journal 2000-;321(7263):730-731. 

Not evaluating people with gestational 

diabetes 

191. Hedderson M M, Ferrara A, Sacks D A. 

Gestational diabetes mellitus and lesser degrees 

of pregnancy hyperglycemia: association with 

increased risk of spontaneous preterm birth. 

Obstet Gynecol 2003;102(4):850-6. 

Does not apply to a key question 

192. Hellmuth E, Damm P, Molsted-Pedersen L. 

Oral hypoglycaemic agents in 118 diabetic 

pregnancies. Diabet Med 2000;17(7):507-11. 

Diagnosis of gestational diabetes not 

confirmed 

193. Henry O A, Beischer N A. Long-term 

implications of gestational diabetes for the 

mother. Baillieres Clin Obstet Gynaecol 

1991;5(2):461-83. 

Does not report a relative measure 

194. Henry O A, Beischer N A, Sheedy M T et al. 

Gestational diabetes and follow-up among 

immigrant Vietnam-born women. Aust N Z J 

Obstet Gynaecol 1993;33(2):109-14. 

Diagnosis of gestational diabetes not 

confirmed 

195. Herbison P, Wilson D. Intensified versus 

conventional management of gestational 

diabetes. Am J Obstet Gynecol 

1995;172(5):1642-3. 

Does not include original data 

196. Herbison P, Wilson D. Implications of 

gestational diabetes for the future health of the 

mother. Br J Obstet Gynaecol 1995;102(5):427-

8. 

Does not include original data 

197. Higham R. Caesarean section: an analysis of 

200 cases performed in a district hospital. Med J 

Aust 1967;2(11):505-506. 

Not evaluating people with gestational 

diabetes 

198. Hod M, Shafrir E. Oral hypoglycemic agents as 

an alternative therapy for gestational diabetes. 

ISR. J. MED. SCI. 1995;31(10):640-643. 

Does not include original data 
D-12 

199. Hod M, Bar J, Peled Y et al. Antepartum 

management protocol. Timing and mode of 

delivery in gestational diabetes. Diabetes Care 

1998;21 (Suppl 2):B113-7. 

Other 

200. Hod M, Merlob P, Friedman S et al. Gestational 

diabetes mellitus. A survey of perinatal 

complications in the 1980s. Diabetes 1991;40 

(Suppl 2):74-8. 

Does not have a comparison of interest 

201. Hod M, Rabinerson D, Kaplan B et al. Perinatal 

complications following gestational diabetes 

mellitus how 'sweet' is ill? Acta Obstet Gynecol 

Scand 1996;75(9):809-15. 

Does not have a comparison of interest 

202. Hoet J J. Effect of intervention in gestational 

diabetes. Diabetes Care 1980;3(3):497-8. 

Does not include original data 

203. Holt T A. Long term follow up of women who 

have had gestational diabetes. Br J Gen Pract 

1992;42(362):354-5. 

Does not include original data 

204. Homko C J, Sivan E, Nyirjesy P et al. The 

interrelationship between ethnicity and 

gestational diabetes in fetal macrosomia. 

Diabetes Care 1995;18(11):1442-5. 

No appropriate comparison group for KQ1 

205. Horger E O, 3rd Kellett W W, 3rd Williamson 

H O. Diabetes in pregnancy. A review of 143 

cases. Obstet Gynecol 1967;30(1):46-53. 

Does not apply to a key question 

206. Horrigan T J. Physicians who induce labor for 

fetal macrosomia do not reduce cesarean 

delivery rates. J Perinatol 2001;21(2):93-6. 

Not evaluating people with gestational 

diabetes 

207. Hoshi J, Nishida H, Takahashi N et al. Perinatal 

morbidity of infants of diabetic mothers. Acta 

Paediatr. Jpn. Overs. Ed. 1991;33(2):159-165. 

Not evaluating people with gestational 

diabetes 

208. Hu F B, Manson J E, Stampfer M J et al. Diet, 

lifestyle, and the risk of type 2 diabetes mellitus 

in women. N Engl J Med 2001;345(11):790-7. 

Not evaluating people with gestational 

diabetes 

209. Huddle K R, Myer I G, Diamond T H et al. 

Diabetes in pregnancy. The use of home blood 

glucose monitoring and intensive monitoring to 

ensure favourable perinatal outcome. S Afr Med 

J 1987;71(7):429-31. 

Does not apply to a key question 

210. Huddleston J F. Diagnosis and management of 

diabetes in pregnancy. J Med Assoc State Ala 

1980;50(1):31-3, 37. 

Does not include original data 

211. Hunger-Dathe W, Mosebach N, Samann A et al. 

Prevalence of impaired glucose tolerance 6 

years after gestational diabetes. Exp Clin 

Endocrinol Diabetes 2006;114(1):11-7. 

Diagnosis of gestational diabetes not 

confirmed 

212. Hunger-Dathe W, Volk K, Braun A et al. 

Perinatal morbidity in women with undiagnosed 

gestational diabetes in northern thuringia in 

Germany. Exp Clin Endocrinol Diabetes 

2005;113(3):160-6. 

Does not apply to a key question 

213. Hunter D J. Gestational diabetes. Aust N Z J 

Obstet Gynaecol 1987;27(2):170-1. 

Does not include original data 

214. Ismajovich B, Mashiach S, Zukut H et al. The 

effects of insulin of fetal development in 

"gestational diabetes". Adv Exp Med Biol 

1972;27:383-9. 

Does not apply to a key question 

215. Isseh N, Takrouri M S. Metabolic management 

of diabetes during labor and delivery. Middle 

East J Anesthesiol 1995;13(2):175-180. 

Does not include original data 

216. Jackson R F. Diabetes in pregnancy. J Indiana 

State Med Assoc 1965;58(11):1228-34. 

Case report or case series of less than 50 

cases 

217. Jacobson J D, Cousins L. A population-based 

study of maternal and perinatal outcome in 

patients with gestational diabetes. Am J Obstet 

Gynecol 1989;161(4):981-6. 

Does not apply to a key question 

218. James W H. Gestational diabetes, birth weight, 

sex ratio, and cesarian section. Diabetes Care 

2001;24(11):2018-9. 

Does not apply to a key question 
D-13 

219. Jardim O, Sobral E, Branco E C et al. Delivery 

in diabetic pregnancy. Ann Ist Super Sanita 

1997;33(3):329-332. 

Does not apply to a key question 

220. Jarvela I Y, Juutinen J, Koskela P et al. 

Gestational diabetes identifies women at risk for 

permanent type 1 and type 2 diabetes in fertile 

age: predictive role of autoantibodies. Diabetes 

Care 2006;29(3):607-12. 

Does not report a relative measure 

221. Jawad F, Irshaduddin PK. Prevalence of 

gestational diabetes and pregnancy outcome in 

Pakistan. Eastern Mediterranean Health Journal 

1996;2(2):268-273. 

Does not apply to a key question 

222. Jensen D M, Sorensen B, Feilberg-Jorgensen N 

et al. Maternal and perinatal outcomes in 143 

Danish women with gestational diabetes 

mellitus and 143 controls with a similar risk 

profile. Diabet Med 2000;17(4):281-6. 

Does not have a comparison of interest 

223. Johns K, Olynik C, Mase R et al. Gestational 

diabetes mellitus outcome in 394 patients. J 

Obstet Gynaecol Can 2006;28(2):122-7. 

No appropriate comparison group for KQ1 

224. Johnstone F D, Nasrat A A, Prescott R J. The 

effect of established and gestational diabetes on 

pregnancy outcome. Br J Obstet Gynaecol 

1990;97(11):1009-15. 

Does not have a comparison of interest 

225. Joseph S E. Macrosomia and poor glycaemic 

control in diabetic pregnancy. Diabet Med 

1996;13(12):1072. 

Does not include original data 

226. Jovanovic-Peterson L, Peterson C M. Dietary 

manipulation as a primary treatment strategy for 

pregnancies complicated by diabetes. J. Am. 

Coll. Nutr. 1990;9(4):320-325. 

Does not apply to a key question 

227. Jovanovic-Peterson L, Peterson C M. Turning 

point in the management of pregnancies 

complicated by diabetes: Normoglycemia with 

self blood glucose monitoring of diet and 

insulin dosing. Asaio Trans. 1990;36(4):799-

804. 

Case report or case series of less than 50 

cases 

228. Jovanovic-Peterson L, Bevier W, Peterson C M. 

The Santa Barbara County Health Care Services 

program: birth weight change concomitant with 

screening for and treatment of glucoseintolerance of pregnancy: a potential costeffective intervention? Am J Perinatol 

1997;14(4):221-8. 

Not evaluating people with gestational 

diabetes 

229. Kadiki O A, Reddy M R, Sahli M A et al. 

Outcome of pregnant diabetic patients in 

Benghazi (Libya) from 1984 to 1991. Diabetes 

Res Clin Pract 1993;21(1):39-42. 

Not evaluating people with gestational 

diabetes 

230. Kale S D, Yajnik C S, Kulkarni S R et al. High 

risk of diabetes and metabolic syndrome in 

Indian women with gestational diabetes 

mellitus. Diabet Med 2004;21(11):1257-8. 

Diagnosis of gestational diabetes not 

confirmed 

231. Karlsson K, Kjellmer I. The outcome of diabetic 

pregnancies in relation to the mother's blood 

sugar level. Am J Obstet Gynecol 

1972;112(2):213-220. 

No appropriate comparison group for KQ1 

232. Kaufmann R C, Schleyhahn F T, Huffman D G 

et al. Gestational diabetes diagnostic criteria: 

long-term maternal follow-up. Am J Obstet 

Gynecol 1995;172(2 Pt 1):621-5. 

Does not report a relative measure. 

233. Kelly S. The use of a sliding scale insulin 

regime during the intrapartum period for women 

diagnosed with gestational diabetes. Does it 

prevent neonatal hypoglycaemia? N2N: 

Nurse2Nurse 2003;3(8):50-52. 

Other 

234. Kemball M L, McIver C, Milner R D et al. 

Neonatal hypoglycaemia in infants of diabetic 

mothers given sulphonylurea drugs in 

pregnancy. Arch Dis Child 1970;45(243):696-

701. 

Case report or case series of less than 50 

cases 
D-14 

235. Kerenyi Z, Tabak A G, Stella P et al. 

Association between socioeconomic factors and 

the metabolic syndrome in women with prior 

gestational diabetes mellitus. Diabetes Care 

2000;23(9):1444-5. 

Does not include original data 

236. Keshavarz M, Cheung N W, Babaee G R et al. 

Gestational diabetes in Iran: incidence, risk 

factors and pregnancy outcomes. Diabetes Res 

Clin Pract 2005;69(3):279-86. 

Does not apply to a key question 

237. Khan K S, Hashmi F A, Rizvi J H. Are nondiabetic women with abnormal glucose 

screening test at increased risk of pre-eclampsia, 

macrosomia and caesarian birth? J Pak Med 

Assoc 1995;45(7):176-9. 

Does not apply to a key question 

238. Khonjandi M, Tsai M, Tyson J E. Gestational 

diabetes: the dilemma of delivery. Obstet 

Gynecol 1974;43(1):1-6. 

Does not apply to a key question 

239. Kinalski M, Sledziewski A, Telejko B et al. 

Post-partum evaluation of amylin in lean 

patients with gestational diabetes mellitus. Acta 

Diabetol 2004;41(1):1-4. 

Does not apply to a key question 

240. King K C, Adam P A, Clemente G A et al. 

Infants of diabetic mothers: attenuated glucose 

uptake without hyperinsulinemia during 

continuous glucose infusion. Pediatrics 

1969;44(3):381-392. 

Does not include a medication of interest for 

KQ1 

241. Kirby R S. Diabetes and congenital 

malformations. Paediatr Perinat Epidemiol 

1996;10(4):469-76. 

Does not include original data 

242. Kivnick S G, Fachnie J D, Lee C Y. Current 

management of pregnancy in the diabetic: a 

team approach. Henry Ford Hosp Med J 

1983;31(2):84-90. 

Does not include original data 

243. Kjos S L, Berkowitz K, Xiang A. Independent 

predictors of cesarean delivery in women with 

diabetes. J Matern Fetal Neonatal Med 

2004;15(1):61-67. 

Not evaluating people with gestational 

diabetes 

244. Kjos S L, Henry O, Lee R M et al. The effect of 

lactation on glucose and lipid metabolism in 

women with recent gestational diabetes. Obstet 

Gynecol 1993;82(3):451-5. 

Does not report a relative measure 

245. Kjos S L, Leung A, Henry O A et al. 

Antepartum surveillance in diabetic 

pregnancies: predictors of fetal distress in labor. 

Am J Obstet Gynecol 1995;173(5):1532-9. 

Does not have a comparison of interest 

246. Kjos S L, Schaefer-Graf U, Sardesi S et al. A 

randomized controlled trial using glycemic plus 

fetal ultrasound parameters versus glycemic 

parameters to determine insulin therapy in 

gestational diabetes with fasting hyperglycemia. 

Diabetes Care 2001;24(11):1904-10. 

Does not have a comparison of interest 

247. Kjos S L, Shoupe D, Douyan S et al. Effect of 

low-dose oral contraceptives on carbohydrate 

and lipid metabolism in women with recent 

gestational diabetes: results of a controlled, 

randomized, prospective study. Am J Obstet 

Gynecol 1990;163(6 Pt 1):1822-7. 

Does not report a relative measure 

248. Knopp R H, Magee M S, Raisys V et al. 

Metabolic effects of hypocaloric diets in 

management of gestational diabetes. Diabetes 

1991;40 (Suppl 2):165-71. 

Does not have a comparison of interest 

249. Knopp R H, Magee M S, Raisys V et al. 

Hypocaloric diets and ketogenesis in the 

management of obese gestational diabetic 

women. J. AM. COLL. NUTR. 1991;10(6):649-

667. 

Does not include original data 

250. Ko G T, Chan J C, Cockram C S. Change of 

glycaemic status in Chinese subjects with 

impaired fasting glycaemia. Diabet Med 

2001;18(9):745-8. 

Not evaluating people with gestational 

diabetes 

251. Ko G T, Chan J C, Tsang L W et al. Glucose 

intolerance and other cardiovascular risk factors 

in chinese women with a history of gestational 

diabetes mellitus. Aust N Z J Obstet Gynaecol 

1999;39(4):478-83. 

Diagnosis of gestational diabetes not 

confirmed 
D-15 

252. Ko G T, Chan J C, Tsang L W et al. Outcomes 

of screening for diabetes in high-risk Hong 

Kong Chinese subjects. Diabetes Care 

2000;23(9):1290-4. 

Not evaluating people with gestational 

diabetes 

253. Ko G T, Chan J C, Yeung V T et al. Combined 

use of a fasting plasma glucose concentration 

and HbA1c or fructosamine predicts the 

likelihood of having diabetes in high-risk 

subjects. Diabetes Care 1998;21(8):1221-5. 

Not evaluating people with gestational 

diabetes 

254. Kodama Y, Sameshima H, Ikenoue T. Regional 

population-based study on pregnancy outcomes 

in women with diabetes mellitus in Japan. J. 

Obstet. Gynaecol. Res. 2007;33(1):45-48. 

No appropriate comparison group for KQ1 

255. Koivunen R M, Juutinen J, Vauhkonen I et al. 

Metabolic and steroidogenic alterations related 

to increased frequency of polycystic ovaries in 

women with a history of gestational diabetes. J 

Clin Endocrinol Metab 2001;86(6):2591-9. 

No relevant risk factor for KQ3 

256. Koren G. Glyburide is safe for gestational 

diabetes mellitus. Can. Pharm. J. 

2005;138(6):67+74. 

Does not include original data 

257. Kousta E, Cela E, Lawrence N et al. The 

prevalence of polycystic ovaries in women with 

a history of gestational diabetes. Clin 

Endocrinol (Oxf) 2000;53(4):501-7. 

Other 

258. Kousta E, Efstathiadou Z, Lawrence N J et al. 

The impact of ethnicity on glucose regulation 

and the metabolic syndrome following 

gestational diabetes. Diabetologia 

2006;49(1):36-40. 

Other 

259. Kousta E, Lawrence N J, Godsland I F et al. 

Insulin resistance and beta-cell dysfunction in 

normoglycaemic European women with a 

history of gestational diabetes. Clin Endocrinol 

(Oxf) 2003;59(3):289-97. 

Does not evaluate a relevant maternal or 

neonatal outcome 

260. Kraus P A. Re: Walsh E. Re: Gestational 

Diabetes. What happens postpartum? Aust N Z 

J Obstet Gynaecol 2004;44(6):589. 

Does not include original data 

261. Kremer C J, Duff P. Glyburide for the treatment 

of gestational diabetes. Am J Obstet Gynecol 

2004;190(5):1438-9. 

Other 

262. Kripke C. Intensive management of gestational 

diabetes. Am Fam Physician 2004;70(5):866. 

Does not include original data 

263. Krishna U, Panjabi J, Purandare V N. Some 

criteria for induction of labour in diabetes, 

toxemia of pregnancy and Rh immunization. J 

Postgrad Med 1972;18(1):21-26. 

Other 

264. Kuhl C, Moller-Jensen B, Saurbrey N et al. 

Intensified insulin treatment in diabetic 

pregnancy. Diabetes Educ 1984;10:60-63. 

Not evaluating people with gestational 

diabetes 

265. Kung A W, Ma J T, Wong V C et al. Glucose 

and lipid metabolism with triphasic oral 

contraceptives in women with history of 

gestational diabetes. Contraception 

1987;35(3):257-69. 

Other 

266. Laird J, McFarland K F. Fasting blood glucose 

levels and initiation of insulin therapy in 

gestational diabetes. Endocr Pract 

1996;2(5):330-2. 

Does not include original data 

267. Lam K S, Li D F, Lauder I J et al. Prediction of 

persistent carbohydrate intolerance in patients 

with gestational diabetes. Diabetes Res Clin 

Pract 1991;12(3):181-6. 

Other 

268. Landon M B, Gabbe S G. Antepartum fetal 

surveillance in gestational diabetes mellitus. 

Diabetes 1985;34 (Suppl 2)50-4. 

Diagnosis of gestational diabetes not 

confirmed. 

269. Landon M B, Sonek J, Foy P et al. Sonographic 

measurement of fetal humeral soft tissue 

thickness in pregnancy complicated by GDM. 

Diabetes 1991;40 (Suppl 2):66-70. 

Does not apply to a key question 
D-16 

270. Langer O. Management of gestational diabetes: 

Pharmacologic treatment options and glycemic 

control. Endocrinol. Metab. Clin. North Am. 

2006;35(1):53-78. 

Does not include original data 

271. Langer O, Maulik D. Developing evidencebased medicine for managing diabetes in 

pregnancy. J Matern Fetal Neonatal Med 

2002;11(4):217. 

Does not include original data 

272. Langer O, Mazze R. The relationship between 

large-for-gestational-age infants and glycemic 

control in women with gestational diabetes. Am 

J Obstet Gynecol 88;159(6):1478-83. 

Does not have a comparison of interest 

273. Langer O, Berkus M D, Huff R W et al. 

Shoulder dystocia: should the fetus weighing 

greater than or equal to 4000 grams be delivered 

by cesarean section? Am J Obstet Gynecol 

1991;165(4 Pt 1):831-7. 

Not evaluating people with gestational 

diabetes 

274. Langer O, Berkus M, Brustman L et al. 

Rationale for insulin management in gestational 

diabetes mellitus. Diabetes 1991;40 (Suppl 

2):186-90. 

Does not have a comparison of interest 

275. Langer O, Conway D L, Berkus M D. 

Glyburide was as safe and effective as insulin in 

gestational diabetes. Evid.-Based Med. 

2001;6(3):79. 

Does not include original data 

276. Langer O, Levy J, Brustman L et al. Glycemic 

control in gestational diabetes mellitus--how 

tight is tight enough: small for gestational age 

versus large for gestational age? Am J Obstet 

Gynecol 1989;161(3):646-53. 

No appropriate comparison group for KQ1 

277. Langer O, Rodriguez D A, Xenakis E M et al. 

Intensified versus conventional management of 

gestational diabetes. Am J Obstet Gynecol 

1994;170(4):1036-46; discussion 1046-7. 

Does not have a comparison of interest 

278. Langer O, Yogev Y, Most O et al. Gestational 

diabetes: the consequences of not treating. Am J 

Obstet Gynecol 2005;192(4):989-97. 

Does not apply to a key question 

279. Langer O, Yogev Y, Xenakis E M et al. 

Overweight and obese in gestational diabetes: 

the impact on pregnancy outcome. Am J Obstet 

Gynecol 2005;192(6):1768-76. 

Does not have a comparison of interest 

280. Lao T T, Ho L F. Does maternal glucose 

intolerance affect the length of gestation in 

singleton pregnancies? J Soc Gynecol Investig 

2003;10(6):366-71. 

Does not apply to a key question 

281. Lauenborg J, Hansen T, Jensen D M et al. 

Increasing incidence of diabetes after 

gestational diabetes: a long-term follow-up in a 

Danish population. Diabetes Care 

2004;27(5):1194-9. 

Diagnosis of gestational diabetes not 

confirmed 

282. Lauenborg J, Mathiesen E, Hansen T et al. The 

prevalence of the metabolic syndrome in a 

danish population of women with previous 

gestational diabetes mellitus is three-fold higher 

than in the general population. J Clin 

Endocrinol Metab 2005;90(7):4004-10. 

Does not evaluate a relevant maternal or 

neonatal outcome 

283. Leeman L, Leeman R. A Native American 

community with a 7% cesarean delivery rate: 

does case mix, ethnicity, or labor management 

explain the low rate? Ann Fam Med 

2003;1(1):36-43. 

Does not apply to a key question 

284. Leikin E, Jenkins J H, Graves W L. 

Prophylactic insulin in gestational diabetes. 

Obstet Gynecol 1987;70(4):587-92. 

Does not have a comparison of interest 

285. Lencioni C, Volpe L, Miccoli R et al. Early 

impairment of beta-cell function and insulin 

sensitivity characterizes normotolerant 

Caucasian women with previous gestational 

diabetes. Nutr Metab Cardiovasc Dis 

2006;16(7):485-93. 

Does not evaluate risk factors for type 2 

diabetes 

286. Leveno K J, Fortunato S J, Raskin P et al. 

Continuous subcutaneous insulin infusion 

during pregnancy. Diabetes Res. Clin. Pract. 

1988;4(4):257-268. 

Does not have a comparison of interest 
D-17 

287. Levy A L, Gonzalez J L, Rappaport V J et al. 

Effect of labor induction on cesarean section 

rates in diabetic pregnancies. J. Reprod. Med. 

Obstet. Gynecol. 2002;47(11):931-932. 

No appropriate comparison group for KQ1 

288. Li D F, Wong V C, O'Hoy K M et al. Is 

treatment needed for mild impairment of 

glucose tolerance in pregnancy? A randomized 

controlled trial. Br J Obstet Gynaecol 

1987;94(9):851-4. 

Does not apply to a key question 

289. Lin C C, River J, River P et al. Good diabetic 

control early in pregnancy and favorable fetal 

outcome. Obstet Gynecol 1986;67(1):51-6. 

Not evaluating people with gestational 

diabetes 

290. Lin C H, Wen S F, Wu Y H et al. The 

postpartum metabolic outcome of women with 

previous gestational diabetes mellitus. Chang 

Gung Med J 2005;28(11):794-800. 

Does not evaluate risk factors for type 2 

diabetes 

291. Liner R. Induction of labor in patients with 

diabetes mellitus. Am J Obstet Gynecol 

1982;143(7):850-851. 

Does not include original data 

292. Linne Y, Barkeling B, Rossner S. Natural 

course of gestational diabetes mellitus: long 

term follow up of women in the SPAWN study. 

BJOG 2002;109(11):1227-31. 

Does not report a relative measure 

293. Lucarini N, Bottini F G, Borgiani P et al. 

Genetic and non genetic factors in the outcome 

of diabetic pregnancy. J Perinat Med 

1994;22(5):379-85. 

Does not apply to a key question 

294. Mangione RA, Torre MS, DeLuca A et al. 

Neonatal complications associated with 

maternal diabetes. Neonatal Network 

1983;2(3):36-41. 

Does not include original data 

295. Mannucci E, Bardini G, Ognibene A et al. 

Screening for diabetes in obese patients using 

the new diagnostic criteria. Diabetes Care 

1998;21(3):468-9. 

Not evaluating people with gestational 

diabetes 

296. Manolakis P G. APhA drug treatment protocols: 

management of gestational diabetes mellitus 

and impaired glucose tolerance during 

pregnancy. APhA Diabetes Mellitus Panel. J 

Am Pharm Assoc (Wash) 1998;38(3):307-16. 

Does not include original data 

297. Maresh M, Beard R W, Bray C S et al. Factors 

predisposing to and outcome of gestational 

diabetes. Obstet Gynecol 1989;74(3 Pt 1):342-6. 

Does not have a comparison of interest 

298. Maresh M, Gillmer M D, Beard R W et al. The 

effect of diet and insulin on metabolic profiles 

of women with gestational diabetes mellitus. 

Diabetes 1985;34 Suppl 2:88-93. 

Does not have a comparison of interest 

299. Mashini I S, Fadel H E, Nelson G H et al. 

Indications for and timing of delivery in 

diabetic pregnancies. Am. J. Obstet. Gynecol. 

1985;153(7):759-766. 

Does not evaluate a relevant maternal or 

neonatal outcome 

300. Mathieu C. Diabetes and pregnancy: beyond 

glucose? Diabetologia 2005;48(9):1714-5. 

Does not include original data 

301. Mauricio D, Corcoy R M, Codina M et al. Islet 

cell antibodies identify a subset of gestational 

diabetic women with higher risk of developing 

diabetes mellitus shortly after pregnancy. 

Diabetes Nutr. Metab. Clin. Exp. 

1992;5(4):237-241. 

Other 

302. Mawhinney H, Hadden D R, Middleton D et al. 

HLA antigens in asymptomatic diabetes. A 10-

year follow-up study of potential diabetes in 

pregnancy and gestational diabetes. Ulster Med 

J 1979;48(2):166-72. 

Does not report a relative measure 

303. McAuliffe F M, Foley M, Firth R et al. 

Outcome of diabetic pregnancy with 

spontaneous labour after 38 weeks. Ir. J. Med. 

Sci. 1999;168(3):160-163. 

Not evaluating people with gestational 

diabetes 

304. McElduff A, Hitchman R. Fasting plasma 

glucose values alone miss most abnormalities of 

glucose tolerance in the postpartum. Diabet 

Med 2004;21(6):648; author reply 648-9. 

Does not include original data 
D-18 

305. McFarland K F. Management of diabetes in 

pregnancy. J Fla Med Assoc 1985;72(3):170-5. 

Does not include original data 

306. McGuire V, Rauh M J, Mueller B A et al. The 

risk of diabetes in a subsequent pregnancy 

associated with prior history of gestational 

diabetes or macrosomic infant. Paediatr Perinat 

Epidemiol 1996;10(1):64-72. 

Other 

307. McLellan J A, Barrow B A, Levy J C et al. 

Prevalence of diabetes mellitus and impaired 

glucose tolerance in parents of women with 

gestational diabetes. Diabetologia 

1995;38(6):693-8. 

Does not apply to a key question 

308. McManus R M, Cunningham I, Watson A et al. 

Beta-cell function and visceral fat in lactating 

women with a history of gestational diabetes. 

Metabolism 2001;50(6):715-9. 

Does not apply to a key question 

309. Mello G, Parretti E, Mecacci F et al. 

Anthropometric features in infants of mothers 

with gestational diabetes: relationship with 

treatment modalities. Biol Neonate 

1997;72(1):22-7. 

Does not have a comparison of interest 

310. Mestman J H. Insulin resistance syndrome and 

gestational diabetes. Endocr Pract 2003;9 

(Suppl 2):90-2. 

Does not include original data 

311. Mestman J H, Anderson G V, Guadalupe V. 

Follow-up study of 360 subjects with abnormal 

carbohydrate metabolism during pregnancy. 

Obstet Gynecol 1972;39(3):421-5. 

Other 

312. Metzger B E, Coustan D R. Summary and 

recommendations of the Fourth International 

Workshop-Conference on Gestational Diabetes 

Mellitus. The Organizing Committee. Diabetes 

Care 98;21 (Suppl 2):B161-7. 

Does not include original data 

313. Metzger B E, Bybee D E, Freinkel N et al. 

Gestational diabetes mellitus. Correlations 

between the phenotypic and genotypic 

characteristics of the mother and abnormal 

glucose tolerance during the first year 

postpartum. Diabetes 1985;34 (Suppl 2):111-5. 

Other 

314. Miller J M, Brown H L, Pastorek J G et al. Fetal 

overgrowth. Diabetic versus nondiabetic. J 

Ultrasound Med 1988;7(10):577-9. 

Does not apply to a key question 

315. Mimouni F, Miodovnik M, Rosenn B et al. 

Birth trauma in insulin-dependent diabetic 

pregnancies. Am J Perinatol 1992;9(3):205-8. 

Not evaluating people with gestational 

diabetes 

316. Mimouni F, Miodovnik M, Siddiqi T A et al. 

Perinatal asphyxia in infants of insulindependent diabetic mothers. J. PEDIATR. 

1988;113(2):345-353. 

Not evaluating people with gestational 

diabetes 

317. Mirghani O A, Saeed O K. A simplified 

management of diabetic pregnant woman. Saudi 

Med J 2000;21(4):335-339. 

Does not apply to a key question 

318. Moggi G, Teti G, De Luca et al. Prevention and 

treatment of carbohydrate metabolism 

abnormalities during pregnancy. J. Foetal Med. 

1985;5(1-2):26-35. 

Does not include a medication of interest for 

KQ1 

319. Mohamed N, Dooley J. Gestational diabetes and 

subsequent development of NIDDM in 

aboriginal women of northwestern Ontario. Int J 

Circumpolar Health 1998;57 (Suppl 1):355-8. 

Does not apply to a key question 

320. Mokgokong E T. Management of diabetes 

mellitus during pregnancy by maintaining 

normal blood glucose levels. S. Afr. Med. J. 

83;64(26):1011-1013. 

Not evaluating people with gestational 

diabetes 

321. Molsted-Pedersen L, Skouby S O, Damm P. 

Preconception counseling and contraception 

after gestational diabetes. Diabetes 1991;40 

(Suppl 2):147-50. 

Diagnosis of gestational diabetes not 

confirmed 
D-19 

322. Moore Lisa, Briery Christian, Martin Rick et al. 

Metformin (M) vs. insulin (I) in A2 diabetics; A 

randomized clinical trial: 25th Annual Meeting 

of the Society for Maternal-Fetal Medicine, 

February 7-12, 2005 Reno Hilton, Reno, 

Nevada. American Journal of Obstetrics and 

Gynecology 2004;191(Supplement 1):S8. 

Does not include original data 

323. Moore M P. Diabetes and pregnancy. Improving 

perinatal outcome. Curr. Ther. 1987;28(9):85-

96. 

Does not include original data 

324. Moses R G. The medical management of 

gestational diabetes in Australia within a solo 

private practice. Diabet Med 1994;11(6):597-

600. 

Does not apply to a key question 

325. Moses R G, Griffiths R D. Can a diagnosis of 

gestational diabetes be an advantage to the 

outcome of pregnancy? J Soc Gynecol Investig 

1995;2(3):523-5. 

Does not apply to a key question 

326. Moses R G, Knights S J, Lucas E M et al. 

Gestational diabetes: is a higher cesarean 

section rate inevitable? Diabetes Care 

2000;23(1):15-7. 

No appropriate comparison group for KQ1 

327. Moses R G, Lucas E M, Knights S. Gestational 

diabetes mellitus. At what time should the 

postprandial glucose level be monitored? Aust 

N Z J Obstet Gynaecol 1999;39(4):457-60. 

Does not apply to a key question 

328. Moss J M. Treatment of pregnant diabetics with 

oral hypoglycemic drugs. South Med J 

1966;59(6):695-697. 

Case report or case series of less than 50 

cases 

329. Murphy J, Peters J, Morris P. Conservative 

management of pregnancy in diabetic women. 

BR. MED. J. 1984;288(6425):1203-1205. 

Not evaluating people with gestational 

diabetes 

330. Naeye R L. The outcome of diabetic 

pregnancies: a prospective study. Ciba Found 

Symp 1978;(63):227-241. 

Not evaluating people with gestational 

diabetes 

331. Nagy G. Management of gestational diabetes. 

Zentralbl Gynakol 1993;115(4):147-53. 

Diagnosis of gestational diabetes not 

confirmed 

332. Nagy G. Late complications of gestational 

diabetes--maternal effects. Zentralbl Gynakol 

1993;115(10):450-3. 

Does not apply to a key question 

333. Nasrat H A, Salleh M, Ardawi M et al. Outcome 

of pregnancy in diabetic mothers. Int J 

Gynaecol Obstet 1993;43(1):29-34. 

Does not have a comparison of interest 

334. Nasrat H, Fageeh W, Abalkhail B et al. 

Determinants of pregnancy outcome in patients 

with gestational diabetes. Int J Gynaecol Obstet 

1996;53(2):117-23. 

Does not apply to a key question 

335. Naylor C D, Sermer M, Chen E et al. Cesarean 

delivery in relation to birth weight and 

gestational glucose tolerance: pathophysiology 

or practice style? Toronto Trihospital 

Gestational Diabetes Investigators. JAMA 

1996;275(15):1165-70. 

No appropriate comparison group for KQ1 

336. Naylor C D, Sermer M, Chen E et al. Cesarean 

delivery in relation to birth weight and 

gestational glucose tolerance: Pathophysiology 

or practice style?. J. Am. Med. Assoc. 

1996;275(15):1165-1170. 

Other 

337. Neiger R. Fetal macrosomia in the diabetic 

patient. Clin. Obstet. Gynecol. 1992;35(1):138-

150. 

Does not include original data 

338. Nestler J E. Reproductive endocrinology. Curr. 

Opin. Endocrinol. Diabetes 2002;9(6):443. 

Does not include original data 

339. Ng C S, Lim L S, Chng K P et al. Combined 

team management of diabetes mellitus in 

pregnancy. Ann Acad Med Singapore 

1985;14(2):297-302. 

Diagnosis of gestational diabetes not 

confirmed 
D-20 

340. Nord E, Hanson U, Persson B. A simplified 

model for management of women with 

gestational diabetes at the primary care level. 

Diabetes Res 1991;17(4):175-9. 

Does not include a medication of interest for 

KQ1 

341. Nordlander E, Hanson U, Stangenberg M et al. 

Twenty-four hour excretion of urinary Cpeptide in gestational diabetic women before 

and after treatment with diet of diet and insulin. 

Diabetes Res. 1989;10(1):25-30. 

Does not apply to a key question 

342. Notelovitz M. Gestational diabetes in general 

practice. S Afr Med J 1974;48(10):417-20. 

Does not include original data 

343. Notelovitz M. Sulphonylurea therapy in the 

treatment of the pregnant diabetic. S Afr Med J 

1971;45(9):226-229. 

Case report or case series of less than 50 

cases 

344. Noussitou P, Monbaron D, Vial Y et al. 

Gestational diabetes mellitus and the risk of 

metabolic syndrome: a population-based study 

in Lausanne, Switzerland. Diabetes Metab 

2005;31(4 Pt 1):361-9. 

Does not evaluate risk factors for type 2 

diabetes 

345. O'Neill E. Gestational diabetes. Bol Asoc Med 

P R 1965;57(10):508-15. 

Does not apply to a key question 

346. O'Sullivan J B, Charles D, Mahan C M et al. 

Gestational diabetes and perinatal mortality rate. 

Am J Obstet Gynecol 1973;116(7):901-4. 

Does not apply to a key question 

347. O'Sullivan J B, Gellis S S, Dandrow R V et al. 

The potential diabetic and her treatment in 

pregnancy. Obstet Gynecol 1966;27(5):683-

689. 

No appropriate comparison group for KQ1 

348. Oakley N W, Beard R W, Turner R C. Effect of 

sustained maternal hyperglycaemia on the fetus 

in normal and diabetic pregnancies. Br Med J 

1972;1(798):466-469. 

No appropriate comparison group for KQ1 

349. Oats J N, Beischer N A. The persistence of 

abnormal glucose tolerance after delivery. 

Obstet Gynecol 1990;75(3 Pt 1):397-401. 

Diagnosis of gestational diabetes not 

confirmed 

350. Ogata ES. Diabetes-related problems of the 

newborn. Perinatology Neonatology 

1984;8(1):48-53. 

Does not include original data 

351. Olofsson P, Ingemarsson I, Solum T. Fetal 

distress during labour in diabetic pregnancy. 

BR. J. Obstet. Gynaecol. 1986;93(10):1067-

1071. 

Not evaluating people with gestational 

diabetes 

352. Orskou J, Kesmodel U, Henriksen T B et al. An 

increasing proportion of infants weigh more 

than 4000 grams at birth. Acta Obstet Gynecol 

Scand 2001;80(10):931-6. 

Not evaluating people with gestational 

diabetes 

353. Ort T, Voss M, Lichtmacher A et al. 

Pharmacogenomic assessment of treatment 

options in gestational diabetes. 

Pharmacogenomics J 2005;5(6):338-45. 

Diagnosis of gestational diabetes not 

confirmed 

354. Osei K, Gaillard T R, Schuster D P. History of 

gestational diabetes leads to distinct metabolic 

alterations in nondiabetic African-American 

women with a parental history of type 2 

diabetes. Diabetes Care 1998;21(8):1250-7. 

Other 

355. Oztekin O. Screening for gestational diabetes 

mellitus. Acta Obstet Gynecol Scand 

2006;85(6):762; author reply 763. 

Does not include original data 

356. Paisey R B, Hartog M, Savage P. A high-fibre 

diet in gestational diabetes--wheat fibre, 

leguminous fibre or both? Hum Nutr Appl Nutr 

1987;41(2):146-9. 

Case report or case series of less than 50 

cases 
D-21 

357. Pallardo L F, Herranz L, Martin-Vaquero P et 

al. Impaired fasting glucose and impaired 

glucose tolerance in women with prior 

gestational diabetes are associated with a 

different cardiovascular profile. Diabetes Care 

2003;26(8):2318-22. 

Does not report a relative measure 

358. Pedersen J, Molsted-Pedersen L M. Congenital 

malformations: the possible role of diabetes care 

outside pregnancy. Ciba Found Symp 

1978;(63):265-271. 

Does not apply to a key question 

359. Peel J. Diabetes In Pregnancy. Foetal 

Macrosomia And Increased Perinatal Mortality. 

Proc R Soc Med 1963;56:1009-11. 

Does not include original data 

360. Perry A. Gestational diabetes. J Midwifery 

Womens Health 2006;51(2):135-6. 

Does not include original data 

361. Perry RC, Dixon D. Gestational diabetes 

mellitus. Physician Assistant 1999;23(5):14. 

Does not include original data 

362. Persson B, Stangenberg M, Hansson U et al. 

Gestational diabetes mellitus (GDM): 

comparative evaluation of two treatment 

regimens, diet vs insulin and diet. Diabetes 

1985;34(Suppl 2):101-105. 

Not evaluating people with gestational 

diabetes 

363. Persson B, Hanson U, Hartling S G et al. 

Follow-up of women with previous GDM. 

Insulin, C-peptide, and proinsulin responses to 

oral glucose load. Diabetes 1991;40 (Suppl 

2):136-41. 

Does not evaluate risk factors for type 2 

diabetes 

364. Persson B, Stangenberg M, Hansson U et al. 

Gestational diabetes mellitus (GDM). 

Comparative evaluation of two treatment 

regimens, diet versus insulin and diet. Diabetes 

85;34 (Suppl 2):101-5. 

Not evaluating people with gestational 

diabetes 

365. Pettitt D J, Ospina P, Kolaczynski J W et al. 

Comparison of an insulin analog, insulin aspart, 

and regular human insulin with no insulin in 

gestational diabetes mellitus. Diabetes Care 

2003;26(1):183-6. 

Other 

366. Philipson E H, Kalhan S C, Edelberg S C et al. 

Maternal obesity as a risk factor in gestational 

diabetes. Am J Perinatol 1985;2(4):268-70. 

Does not apply to a key question 

367. Philipson E H, Kalhan S C, Rosen M G et al. 

Gestational diabetes mellitus. Is further 

improvement necessary? Diabetes 1985;34 

(Suppl 2):55-60. 

Does not have a comparison of interest 

368. Piacquadio K, Hollingsworth D R, Murphy H. 

Effects of in-utero exposure to oral 

hypoglycaemic drugs. Lancet 

1991;338(8771):866-9. 

Not evaluating people with gestational 

diabetes 

369. Pimenta W P, Calderon I M, Cruz N S et al. 

Subclinical abnormalities of glucose 

metabolism in Brazilian women with a history 

of gestational diabetes mellitus. Acta Obstet 

Gynecol Scand 2004;83(12):1152-8. 

Does not evaluate risk factors for type 2 

diabetes 

370. Piscitelli J, Eden R D, Jelovsek F R et al. 

Family history of diabetes mellitus and oral 

glucose tolerance testing criteria. Acta Obstet. 

Gynecol. Scand. 1987;66(6):489-492. 

Does not apply to a key question 

371. Plehwe W E, Shearman R P, Turtle J R. 

Management of pregnancy complicated by 

diabetes: experience with 232 patients in a 4-

year period. Aust N Z J Obstet Gynaecol 

1984;24(3):167-73. 

Not evaluating people with gestational 

diabetes 

372. Pullen F, Thompson T, Drubra U. A nurse-led 

clinic for women with IGT following 

gestational diabetes. Impaired glucose tolerance 

[corrected] [published erratum appears in J 

Diabetes Nurs 1998 Sep-Oct; 2(5): 138]. 

Journal of Diabetes Nursing 98;2(4):115-118. 

Does not apply to a key question 

373. Pullen F, Grenfell A. The diagnosis of 

gestational diabetes in a multiethnic population: 

Which diagnostic criteria should be used with 

respect to maternal outcome? Pract. Diabetes 

Int. 2002;19(9):279-282. 

Other 
D-22 

374. Rajab K E, Mehdi S. Pregnancy outcome 

among gestational diabetics with blood glucose 

levels between 7.7 and 8.3 mmol/l. Int J 

Gynaecol Obstet 1998;63(1):59-61. 

Does not apply to a key question 

375. Ramos-Arroyo M A, Rodriguez-Pinilla E, 

Cordero J F. Maternal diabetes: the risk for 

specific birth defects. Eur J Epidemiol 

1992;8(4):503-8. 

Does not evaluate a relevant maternal or 

neonatal outcome 

376. Ranade A Y, Merchant R H, Bajaj R T et al. 

Infants of diabetic mothers--an analysis of 50 

cases. Indian Pediatr 1989;26(4):366-370. 

No appropriate comparison group for KQ1 

377. Rand L, Caughey A B. Comparison of 

glyburide and insulin for the management of 

gestational diabetes in a large managed care 

organization. Am J Obstet Gynecol 

2006;195(2):628-9; author reply 629-30. 

Does not include original data 

378. Rasmussen M J, Firth R, Foley M et al. The 

timing of delivery in diabetic pregnancy: A 10-

Year review. Aust. New Zealand J. Obstet. 

Gynaecol. 1992;32(4):313-317. 

Not evaluating people with gestational 

diabetes 

379. Ravina A. Insulin-dependent diabetes of 

pregnancy treated with the combination of 

sulfonylurea and insulin. Isr J Med Sci 

1995;31(10):623-5. 

Case report or case series of less than 50 

cases 

380. Ray J G, Vermeulen M J, Shapiro J L et al. 

Maternal and neonatal outcomes in 

pregestational and gestational diabetes mellitus, 

and the influence of maternal obesity and 

weight gain: the DEPOSIT study. Diabetes 

Endocrine Pregnancy Outcome Study in 

Toronto. QJM 2001;94(7):347-56. 

Does not apply to a key question 

381. Raychaudhuri K, Maresh M J. Glycemic control 

throughout pregnancy and fetal growth in 

insulin-dependent diabetes. Obstet Gynecol 

2000;95(2):190-4. 

Not evaluating people with gestational 

diabetes 

382. Reader D, Splett P, Gunderson EP et al. Impact 

of gestational diabetes mellitus nutrition 

practice guidelines implemented by registered 

dietitians on pregnancy outcomes. Journal of the 

American Dietetic Association. 

2006;106(9):1426-33. 

No appropriate comparison group for KQ1 

383. Remsberg K E, McKeown R E, McFarland K F 

et al. Diabetes in pregnancy and cesarean 

delivery. Diabetes Care 1999;22(9):1561-7. 

Does not apply to a key question 

384. Retnakaran R, Hanley A J, Raif N et al. 

Reduced adiponectin concentration in women 

with gestational diabetes: a potential factor in 

progression to type 2 diabetes. Diabetes Care 

2004;27(3):799-800. 

Does not apply to a key question 

385. Ricart W, Bach C, Fernandez-Real J M et al. 

Major fetal complications in optimised 

progestational diabetes mellitus. Diabetologia 

2000;43(8):1077-8. 

Not evaluating people with gestational 

diabetes 

386. Roach V, Rogers M. The incidence of perinatal 

mortality associated with hyperglycaemia in 

pregnancy. Aust N Z J Obstet Gynaecol 

1997;37(2):250-1. 

Does not include original data 

387. Roberts A B, Baker J R, James A G et al. 

Fructosamine in the management of gestational 

diabetes. Am J Obstet Gynecol 1988;159(1):66-

71. 

Does not apply to a key question 

388. Romon M, Nuttens M C, Vambergue A et al. 

Higher carbohydrate intake is associated with 

decreased incidence of newborn macrosomia in 

women with gestational diabetes. J Am Diet 

Assoc 2001;101(8):897-902. 

Does not apply to a key question. 

389. Roncaglia N, Bellini P, Arreghini A et al. 

Gestational diabetes mellitus: intensive versus 

mild treatment. Clin Exp Obstet Gynecol 

1999;26(2):95-7. 

Does not apply to a key question 
D-23 

390. Roseman J M, Go R C, Perkins L L et al. 

Gestational diabetes mellitus among AfricanAmerican women. Diabetes Metab Rev 

1991;7(2):93-104. 

Does not apply to a key question 

391. Ross G. Gestational diabetes. Aust Fam 

Physician 2006;35(6):392-6. 

Does not include original data 

392. Ruder K. Family ties. Diabetes during 

pregnancy carries a lifelong risk of type 2 for 

mother and child. Diabetes Forecast 

2006;59(12):54-6, 58. 

Does not include original data 

393. Russell M A, Phipps M G, Olson C L et al. 

Rates of postpartum glucose testing after 

gestational diabetes mellitus. Obstet Gynecol 

2006;108(6):1456-62. 

Does not apply to a key question 

394. Rutten G E H M, Boomsma L J. Detection of 

type 2 diabetes mellitus in general practice: Do 

the patients' dossiers provide clues? Pract. 

Diabetes Int. 2000;17(5):152-154. 

Not evaluating people with gestational 

diabetes 

395. Ryan E A, Imes S, Liu D et al. Defects in 

insulin secretion and action in women with a 

history of gestational diabetes. Diabetes 

1995;44(5):506-12. 

Other 

396. Saade G. Gestational diabetes mellitus: a pill or 

a shot? Obstet Gynecol 2005;105(3):456-7. 

Does not include original data 

397. Salzberger M, Sharon A, Liban E. Significance 

of the oral glucose tolerance test performed on 

the third day after delivery for the diagnosis of 

diabetes in pregnancy. Isr J Med Sci 

1975;11(6):629-31. 

Does not apply to a key question 

398. Sameshima H, Ikenoue T, Kawahara S et al. 

Effects of longitudinal maternal glucose control 

of infants of diabetic mothers. Acta Obstet. 

Gynaecol. Jpn. 1991;43(7):779-782. 

Does not include a medication of interest for 

KQ1 

399. Sameshima H, Kamitomo M, Kajiya S et al. 

Early glycemic control reduces large-forgestational-age infants in 250 Japanese 

gestational diabetes pregnancies. Am J Perinatol 

2000;17(7):371-6. 

Does not apply to a key question 

400. Schaefer-Graf U M, Buchanan T A, Xiang A H 

et al. Clinical predictors for a high risk for the 

development of diabetes mellitus in the early 

puerperium in women with recent gestational 

diabetes mellitus. Am. J. Obstet. Gynecol. 

2002;186(4):751-756. 

Other 

401. Schaefer-Graf U M, Buchanan T A, Xiang A et 

al. Patterns of congenital anomalies and 

relationship to initial maternal fasting glucose 

levels in pregnancies complicated by type 2 and 

gestational diabetes. Am J Obstet Gynecol 

2000;182(2):313-20. 

Not evaluating people with gestational 

diabetes 

402. Schaefer-Graf UM, Kjos SL, Fauzan OH et al. 

A randomized trial evaluating a predominately 

fetal growth-based strategy to guide 

management of gestational diabetes in 

Caucasian women. Diabetes Care 

2004;27(2):297-302. 

Other 

403. Scherbaum W A, Lankisch M R, Pawlowski B 

et al. Insulin Lispro in pregnancy - 

Retrospective analysis of 33 cases and matched 

controls. Exp. Clin. Endocrinol. Diabetes 

2002;110(1):6-9. 

Not evaluating people with gestational 

diabetes 

404. Schranz A G, Savona-Ventura C. Long-term 

significance of gestational carbohydrate 

intolerance: a longitudinal study. Exp Clin 

Endocrinol Diabetes 2002;110(5):219-22Not 

evaluating people with gestational diabetes 

405. Schwartz R, Teramo K A. Pregnancy outcome, 

Diabetes Control and Complications Trial, and 

intensive glycemic control. Am J Obstet 

Gynecol 1998;178(2):416-7. 

Does not include original data 

406. Schwarz R H, Fields G A, Kyle G C. Timing of 

delivery in the pregnant diabetic patient. Obstet 

Gynecol 1969;34(6):787-791. 

No appropriate comparison group for KQ1 
D-24 

407. Scupholme A, Kamons A S. Validating change 

in risk criteria for a birth center: gestational 

diabetes. J Nurse Midwifery 1988;33(3):129-33. 

Does not apply to a key question. 

408. Seely E W. Does treatment of gestational 

diabetes mellitus affect pregnancy outcome?. 

Nat Clin Pract Endocrinol Metab 2006;2(2):72-

3. 

Does not include original data 

409. Semchyshyn S. A new approach to the 

treatment of diabetic pregnant women. Am J 

Obstet Gynecol 1981;139(8):975-979. 

Case report or case series of less than 50 

cases 

410. Sendag F, Terek M C, Itil I M et al. Maternal 

and perinatal outcomes in women with 

gestational diabetes mellitus as compared to 

nondiabetic controls. J Reprod Med 

2001;46(12):1057-62. 

Does not have a comparison of interest 

411. Senior B. Neonatal hypoglycemia. N Engl J 

Med 1973;289(15):790-793. 

Does not include original data 

412. Serirat S, Deerochanawong C, 

Sunthornthepvarakul T et al. Gestational 

diabetes mellitus. J Med Assoc Thai 

92;75(6):315-9. 

Does not apply to a key question 

413. Serr D M, Ismajovitch B, Mashiach S et al. 

Effect of insulin on perinatal mortality in 

gestational diabetes. Isr J Med Sci 

1972;8(6):789. 

Does not apply to a key question 

414. Shanmugasundaram L. Outcome of type I and 

type II diabetic pregnancy in Asian women. 

BJOG 2006;113(4):495-6; author reply 496. 

Does not include original data 

415. Shea M A, Garrison D L, Tom S K. Diabetes in 

pregnancy. Am J Obstet Gynecol 

1971;111(6):801-3. 

Does not apply to a key question 

416. Shearman R P. Diabetes in pregnancy. Med J 

Aust 1987;146(4):181-2. 

Does not include original data 

417. Shushan A, Ezra Y, Samueloff A. Early 

treatment of gestational diabetes reduces the 

rate of fetal macrosomia. Am J Perinatol 

1997;14(5):253-6. 

Does not apply to a key question 

418. Silver H J. Nutritional management of diabetes 

in pregnancy. J Am Diet Assoc 

1993;93(12):1381-2. 

Does not include original data 

419. Simhayoff N, Sheiner E, Levy A et al. To 

induce or not to induce labor: a macrosomic 

dilemma. Gynecol Obstet Invest 

2004;58(3):121-5. 

Not evaluating people with gestational 

diabetes 

420. Simmons D. Gestational diabetes mellitus: 

growing consensus on management but not 

diagnosis. N Z Med J 1999;112(1082):45-6. 

Does not include original data 

421. Simmons D, Robertson S. Influence of maternal 

insulin treatment on the infants of women with 

gestational diabetes. Diabet Med 

1997;14(9):762-5. 

Does not have a comparison of interest 

422. Simmons D, Flack J R, McIntyre H D. Auditing 

diabetes in pregnancy care in New Zealand. N Z 

Med J 2006;119(1230):U1897. 

Does not include original data 

423. Simmons D, Thompson C F, Conroy C et al. 

Use of insulin pumps in pregnancies 

complicated by type 2 diabetes and gestational 

diabetes in a multiethnic community. Diabetes 

Care 2001;24(12):2078-82. 

Not evaluating people with gestational 

diabetes 

424. Simpson R W, Kast S J. Management of 

gestational diabetes with a conservative insulin 

protocol. Med J Aust 2000;172(11):537-40. 

Does not apply to a key question 

425. Sinha B, Dunne F. A postpartum screening 

strategy following gestational diabetes. Diabetes 

Primary Care 2001;3(2):44-46. 

Other 
D-25 

426. Sinha B, Brydon P, Taylor R S et al. Maternal 

ante-natal parameters as predictors of persistent 

postnatal glucose intolerance: a comparative 

study between Afro-Caribbeans, Asians and 

Caucasians. Diabet Med 2003;20(5):382-6. 

Does not apply to a key question 

427. Skouby S O, Andersen O, Kuhl C. Oral 

contraceptives and insulin receptor binding in 

normal women and those with previous 

gestational diabetes. Am J Obstet Gynecol 

1986;155(4):802-7. 

Does not evaluate a relevant maternal or 

neonatal outcome 

428. Skouby S O, Kuhl C, Hornnes P J et al. 

Prolactin and glucose tolerance in normal and 

gestational diabetic pregnancy. Obstet Gynecol 

1986;67(1):17-20. 

Not evaluating people with gestational 

diabetes 

429. Skyler J S, O'Sullivan M J, Robertson E G. 

Blood glucose control during pregnancy. 

Diabetes Care 1980;3(1):69-76. 

Not evaluating people with gestational 

diabetes 

430. Slawson D. Do certain forms of contraception 

given to women with gestational diabetes 

mellitus increase their risk of developing type 2 

diabetes? Evidence-Based Practice 

1998;1(11):9-10, insert 2p. 

Other 

431. Smith S G, Scragg W H. Gestational diabetes. 

Obstet Gynecol 1968;31(2):228-39. 

Does not apply to a key question 

432. Spellacy W N. Shoulder dystocia risks. Am J 

Obstet Gynecol 1999;180(4):1047. 

Does not include original data 

433. Sperling M A, Menon R K. Infant of the 

diabetic mother. Curr Ther Endocrinol Metab 

1994;5:372-6. 

Does not include original data 

434. Stage E, Ronneby H, Damm P. Lifestyle change 

after gestational diabetes. Diabetes Res Clin 

Pract 2004;63(1):67-72. 

No relevant risk factor for KQ3 

435. Stallone L A, Ziel H K. Management of 

gestational diabetes. Am J Obstet Gynecol 

1974;119(8):1091-4. 

Does not apply to a key question 

436. Stangenberg M, Agarwal N, Rahman F et al. 

Frequency of HLA genes and islet cell 

antibodies (ICA) and result of postpartum oral 

glucose tolerance tests (OGTT) in Saudi 

Arabian women with abnormal OGTT during 

pregnancy. Diabetes Res 1990;14(1):9-13. 

Does not evaluate risk factors for type 2 

diabetes 

437. Stangenberg M, Persson B, Lunell N O et al. 

Effect of treatment with insulin or diet on 

intermediary metabolites in pregnant women 

with chemical diabetes in the third trimester of 

pregnancy. Acta Diabetol Lat 1984;21(1):55-61. 

Does not have a comparison of interest 

438. Steel J M, Campbell I W, Hellmuth E et al. Oral 

hypoglycaemic agents in 188 diabetic 

pregnancies. Diabetic Med. 2001;18(7):604-

605. 

Does not include original data 

439. Stephenson M J. Gestational diabetes mellitus. 

Can Fam Physician 1993;39:745-53. 

Does not include original data 

440. Stoffel M, Bell K L, Blackburn C L et al. 

Identification of glucokinase mutations in 

subjects with gestational diabetes mellitus. 

Diabetes 1993;42(6):937-40. 

Does not evaluate a relevant maternal or 

neonatal outcome 

441. Stowers J M, Sutherland H W, Kerridge D F. 

Long-range implications for the mother. The 

Aberdeen experience. Diabetes 1985;34 (Suppl 

2):106-10. 

Diagnosis of gestational diabetes not 

confirmed 

442. Strehlow S L, Mestman J H. Prevention of 

T2DM in women with a previous history of 

GDM. Curr. Diabetes Rep. 2005;5(4):272-277. 

Does not include original data 

443. Sugiyama Y, Kozuka Y, Tamura H. The studies 

of pregnant women with diabetes mellitus or 

gestational diabetes. Acta Obstet Gynaecol Jpn 

1974;21(3):127-34. 

Does not apply to a key question 
D-26 

444. Sun Y, Wang J H, Qi X Y. The 1:3 matched 

case-control study of genetic mutations of 

gestational diabetes mellitus. Chin Med Sci J 

2005;20(2):141. 

No relevant risk factor for KQ3 

445. Sunehag A, Berne C, Lindmark G et al. 

Gestational diabetes-perinatal outcome with a 

policy of liberal and intensive insulin therapy. 

Ups J Med Sci 1991;96(3):185-98. 

Does not have a comparison of interest 

446. Svare J A, Hansen B B, Molsted-Pedersen L. 

Perinatal complications in women with 

gestational diabetes mellitus. Acta Obstet 

Gynecol Scand 2001;80(10):899-904. 

No appropriate comparison group for KQ1 

447. Svare J A, Hansen B B, Molsted-Pedersen L. 

Perinatal complications in women with 

gestational diabetes mellitus: Significance of a 

diagnosis early in pregnancy. Acta Obstet. 

Gynecol. Scand. 2001;80(10):899-904. 

Other 

448. Szilagyi A, Szabo I. Improvement of perinatal 

outcome in diabetic pregnant women. Early 

Pregnancy 2001;5(1):55-6. 

Does not include original data. 

449. Tan Y Y, Yeo S H, Liauw P C. Is postnatal oral 

glucose tolerance testing necessary in all 

women with gestational diabetes. Singapore 

Med J 1996;37(4):384-8. 

Does not apply to a key question 

450. Tanir H M, Sener T, Gurer H et al. A ten-year 

gestational diabetes mellitus cohort at a 

university clinic of the mid-Anatolian region of 

Turkey. Clin Exp Obstet Gynecol 

2005;32(4):241-4. 

Does not apply to a key question 

451. Taricco E, Radaelli T, Nobile de et al. Foetal 

and placental weights in relation to maternal 

characteristics in gestational diabetes. Placenta 

2003;24(4):343-7. 

Does not apply to a key question 

452. Tee C S, Wang K W, Tho C K et al. 

Management and outcome of gestational 

diabetes in Alexandra Hospital, Singapore. Ann 

Acad Med Singapore 1990;19(4):459-62.

No appropriate comparison group for KQ1 

453. Thatcher R. A review of 806 caesarean 

operations performed at the Queen Victoria 

Maternity Hospital, Adelaide, in the years 1965-

1969. Med J Aust 1970;2(5):231-232. 

Not evaluating people with gestational 

diabetes 

454. Thompson D M, Dansereau J, Creed M et al. 

Tight glucose control results in normal perinatal 

outcome in 150 patients with gestational 

diabetes. Obstet Gynecol 1994;83(3):362-6. 

Does not have a comparison of interest 

455. Todros T, Meriggi E, Catella G et al. Growth of 

fetuses of diabetic mothers. J. Clin. Ultrasound 

1989;17(5):333-337. 

Does not apply to a key question 

456. Toescu V, Nuttall S L, Kendall M J et al. 

Women with gestational diabetes should be 

targeted to reduce cardiovascular risk. BMJ 

2002;325(7370):966. 

Does not include original data 

457. Tuffnell D, West J, Walkinshaw S. Time to 

screen for, and treat, gestational diabetes. BJOG 

2006;113(1):3-4. 

Does not include original data 

458. Tura A, Mari A, Winzer C et al. Impaired betacell function in lean normotolerant former 

gestational diabetic women. Eur J Clin Invest 

2006;36(1):22-8. 

Does not evaluate a relevant maternal or 

neonatal outcome 

459. Usher R H, Allen A C, McLean F H. Risk of 

respiratory distress syndrome related to 

gestational age, route of delivery, and maternal 

diabetes. Am J Obstet Gynecol 

1971;111(6):826-832. 

Other 

460. Van Assche F A. Fetal consequences of 

maternal diabetes. Verh K Acad Geneeskd Belg 

1987;49(6):445-60. 

Does not apply to a key question 

461. van der, Linden S J, Mastboom J L. Insulin 

treatment of latent and potential diabetics during 

pregnancy. J Obstet Gynaecol Br Commonw 

1971;78(10):924-926. 

No appropriate comparison group for KQ1 
D-27 

462. Van Howe R S, Storms M R. Hypoglycemia in 

infants of diabetic mothers: experience in a rural 

hospital. Am J Perinatol 2006;23(2):105-10. 

Not evaluating people with gestational 

diabetes 

463. Van Wootten W, Turner R E. Macrosomia in 

neonates of mothers with gestational diabetes is 

associated with body mass index and previous 

gestational diabetes. J Am Diet Assoc 

2002;102(2):241-3. 

Does not apply to a key question 

464. Vaughan N J. Treatment of diabetes in 

pregnancy. Br Med J (Clin Res Ed) 

1987;294(6571):558-60. 

Does not include original data 

465. Verma A, Boney C M, Tucker R et al. Insulin 

resistance syndrome in women with prior 

history of gestational diabetes mellitus. J Clin 

Endocrinol Metab 2002;87(7):3227-35. 

Other 

466. Vitoratos N, Salamalekis E, Loghis S et al. 

Changes of glucose tolerance after delivery in 

women with gestational diabetes. Clin Exp 

Obstet Gynecol 2000;27(3-4):212-4. 

Does not apply to a key question 

467. Vohr B R, McGarvey S T, Coll C G. Effects of 

maternal gestational diabetes and adiposity on 

neonatal adiposity and blood pressure. Diabetes 

Care 1995;18(4):467-75. 

Does not have a comparison of interest 

468. Walsh E. Re: Gestational diabetes. What 

happens post-partum? Aust N Z J Obstet 

Gynaecol 2004;44(3):277-8. 

Does not include original data 

469. Walters B N. Re: Australian carbohydrate 

intolerance study in pregnant women: 

implications for the management of gestational 

diabetes. Aust N Z J Obstet Gynaecol 

2006;46(5):463-4; author reply 464. 

Does not include original data 

470. Ward W K, Johnston C L, Beard J C et al. 

Abnormalities of islet B-cell function, insulin 

action, and fat distribution in women with 

histories of gestational diabetes: relationship to 

obesity. J Clin Endocrinol Metab 

1985;61(6):1039-45. 

Other 

471. Watson D, Rowan J, Neale L et al. Admissions 

to neonatal intensive care unit following 

pregnancies complicated by gestational or type 

2 diabetes. Aust N Z J Obstet Gynaecol 

2003;43(6):429-32. 

Does not apply to a key question 

472. Weaver S P. New research gestational diabetes 

indicates risk later in life. Fam Med 

2004;36(3):159-60. 

Does not include original data 

473. Wechter D J, Kaufmann R C, Amankwah K S et 

al. Prevention of neonatal macrosomia in 

gestational diabetes by the use of intensive 

dietary therapy and home glucose monitoring. 

Am J Perinatol 1991;8(2):131-4. 

Does not apply to a key question 

474. Weeks J W, Major C A, de Veciana M et al. 

Gestational diabetes: does the presence of risk 

factors influence perinatal outcome? Am J 

Obstet Gynecol 1994;171(4):1003-7. 

Does not apply to a key question 

475. Weeks J W, Pitman T, Spinnato J A et al. Fetal 

macrosomia: does antenatal prediction affect 

delivery route and birth outcome? Am J Obstet 

Gynecol 1995;173(4):1215-9. 

Not evaluating people with gestational 

diabetes 

476. Wein P, Beischer N A, Sheedy M T. Studies of 

postnatal diabetes mellitus in women who had 

gestational diabetes. Part 2. Prevalence and 

predictors of diabetes mellitus after delivery. 

Aust N Z J Obstet Gynaecol 1997;37(4):420-3. 

Diagnosis of gestational diabetes not 

confirmed 

477. Wein P, Beischer N, Harris C et al. A trial of 

simple versus intensified dietary modification 

for prevention of progression to diabetes 

mellitus in women with impaired glucose 

tolerance. Aust N Z J Obstet Gynaecol 

1999;39(2):162-6. 

Diagnosis of gestational diabetes not 

confirmed 

478. Weiss P A. Prophylactic insulin in gestational 

diabetes. Obstet Gynecol 1988;71(6 Pt 1):951-2. 

Does not include original data 
D-28 

479. Weiss P A, Hofmann H M, Kainer F et al. Fetal 

outcome in gestational diabetes with elevated 

amniotic fluid insulin levels. Dietary versus 

insulin treatment. Diabetes Res Clin Pract 

1988;5(1):1-7. 

Diagnosis of gestational diabetes not 

confirmed 

480. Weng J, Ekelund M, Lehto M et al. Screening 

for MODY mutations, GAD antibodies, and 

type 1 diabetes--associated HLA genotypes in 

women with gestational diabetes mellitus. 

Diabetes Care 2002;25(1):68-71. 

Does not apply to a key question 

481. Wheeler F C, Gollmar C W, Deeb L C. Diabetes 

and pregnancy in South Carolina: prevalence, 

perinatal mortality, and neonatal morbidity in 

1978. Diabetes Care 1982;5(6):561-5. 

Not evaluating people with gestational 

diabetes 

482. Wijeyaratne C N, Waduge R, Arandara D et al. 

Metabolic and polycystic ovary syndromes in 

indigenous South Asian women with previous 

gestational diabetes mellitus. BJOG 

2006;113(10):1182-7. 

Does not evaluate a relevant maternal or 

neonatal outcome 

483. Williger V M. Fetal outcome in the diabetic 

pregnancy. Am J Obstet Gynecol 

1966;94(1):57-61. 

Not evaluating people with gestational 

diabetes 

484. Winzer C, Wagner O, Festa A et al. Plasma 

adiponectin, insulin sensitivity, and subclinical 

inflammation in women with prior gestational 

diabetes mellitus. Diabetes Care 

2004;27(7):1721-7. 

Does not apply to a key question 

485. Xiang A H, Wang C, Peters R K et al. 

Coordinate changes in plasma glucose and 

pancreatic beta-cell function in Latino women at 

high risk for type 2 diabetes. Diabetes 

2006;55(4):1074-9. 

Does not report a relative measure 

486. Yan J S, Chang Y K, Yin C S. Elective cesarean 

section for macrosomia? Zhonghua Yi Xue Za 

Zhi (Taipei) 1994;53(3):141-5. 

Does not apply to a key question 

487. Yang X, Hsu-Hage B H, Dong L et al. 

Postpartum glucose intolerance in Chinese 

women with gestational diabetes. Diabet Med 

2003;20(8):687-9. 

Does not include original data 

488. Yogev Y, Ben-Haroush A, Chen R et al. Active 

induction management of labor for diabetic 

pregnancies at term; mode of delivery and fetal 

outcome--a single center experience. Eur J 

Obstet Gynecol Reprod Biol 2004;114(2):166-

70. 

Not evaluating people with gestational 

diabetes 

489. Yorav S, Homburg R, Zakut H. Fetal 

macrosomia. Clinical factors and implications. 

J. Foetal Med. 1987;7(1-2):40-43. 

Not evaluating people with gestational 

diabetes 

490. Yue D K, Molyneaux L M, Ross G P et al. Why 

does ethnicity affect prevalence of gestational 

diabetes? The underwater volcano theory. 

Diabet Med 1996;13(8):748-52. 

Does not apply to a key question 

491. Yun S, Kabeer N H, Zhu B P et al. Modifiable 

risk factors for developing diabetes among 

women with previous gestational diabetes. Prev 

Chronic Dis 2007;4(1):A07. 

Not evaluating people with gestational 

diabetes 

492. Zarowitz H, Moltz A. Management of diabetes 

in pregnancy. Obstet Gynecol 1966;27(6):820-

6. 

Does not apply to a key question 

493. Zelop C M, Shipp T D, Repke J T et al. 

Outcomes of trial of labor following previous 

cesarean delivery among women with fetuses 

weighing >4000 g. Am J Obstet Gynecol 

2001;185(4):903-5. 

Not evaluating people with gestational 

diabetes 

494. Zhu L, Nakabayashi M, Takeda Y. Statistical 

analysis of perinatal outcomes in pregnancy 

complicated with diabetes mellitus. J Obstet 

Gynaecol Res 1997;23(6):555-63. 

Not evaluating people with gestational 

diabetes 
D-29 

495. Zonenberg A, Telejko B, Topolska J et al. 

Factors predisposing to disturbed carbohydrate 

tolerance in patients with previous gestational 

diabetes mellitus. Diabetol. Dosw. Klin. 

2006;6(3):143-150. 

Does not have a comparison of interest 

496. Zoupas Ch, Mastrantonakis E, Diakakis I. The 

importance of insulin administration in 

gestational diabetics. Acta Endocrinol. Suppl. 

1984;107(265):26-28. 

Does not have a comparison of interest 
Previewing Only: You cannot submit data from this form

Previewing at Level 34 

Reviewer Comments ( Add a Comment ) 

Refid: 1, Geremia, C. and Cianfarani, S., Insulin Sensitivity in Children Born Small for Gestational Age (SGA), Rev Diabet Stud, 1

(2), 2004, p.58-65 

State: Excluded, Level: 2

Save to finish later Submit Data

KQ4 Quality Form

Labor and Postpartum Management of Gestational Diabetes Mellitus

Please complete this form if study applies to KQ4

Yes No

1. Was the reference test stated? Clear

2. Did the authors report the test used to determine GDM in the study sample? Clear

3. What was the study design? 

Retrospective (data collection planned after completion of tests)

Prospective (data collection planned prior to testing)

4. How was the study population sampled? 

Random

Consecutive

Convenience

Other type of sample

Not stated

Yes No Not reported

5. ---SEE Q16-17 BELOW.--- Clear

6. Were positive and negative tests verified equally? Clear

7. Were the methods for calculating or comparing measures of diagnostic accuracy reported? Clear

8. Were estimates of test reproducibility done? Clear

9. What types of reproducibility were assessed? 

Test-retest

Other (specify:)

10. What was the lost to followup? 

<10%

10-20%

>20%

Not reported

Clear Selection

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Total 130. 131. 132. 

N=

133. If the study reports only the sensitivity/specificity, please list it below. 

%Sensitivity

%SpecificityPositive predictive valueNegative predictive value

134. 

Specify Subgroup

 Reference test + (Diagnosis of test) Reference test - (Diagnosis of test) Total

Comparison test + 135. 136. 137. 

Comparison test - 138. 139. 140. 

Total 141. 142. 143. 

N=

144. If the study reports only the sensitivity/specificity, please list it below. 

%Sensitivity

%SpecificityPositive predictive valueNegative predictive value

145. Comments:Enlarge Shrink

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SRS Form https://www.clinical-analytics.com/d2d/ul1/review.asp?mode=previewMode&articleid=1&level=32 
Total 108. 109. 110. 

N=

111. If the study reports only the sensitivity/specificity, please list it below. 

%Sensitivity

%SpecificityPositive predictive valueNegative predictive value

112. 

Specify Subgroup

 Reference test + (Diagnosis of test) Reference test - (Diagnosis of test) Total

Comparison test + 113. 114. 115. 

Comparison test - 116. 117. 118. 

Total 119. 120. 121. 

N=

122. If the study reports only the sensitivity/specificity, please list it below. 

%Sensitivity

%SpecificityPositive predictive valueNegative predictive value

123. 

Specify Subgroup

 Reference test + (Diagnosis of test) Reference test - (Diagnosis of test) Total

Comparison test + 124. 125. 126. 

Comparison test - 127. 128. 129. 

SRS Form https://www.clinical-analytics.com/d2d/ul1/review.asp?mode=previewMode&articleid=1&level=32 
Comparison test - 83. 84. 85. 

Total 86. 87. 88. 

N=

89. If the study reports only the sensitivity/specificity, please list it below. 

%Sensitivity

%SpecificityPositive predictive valueNegative predictive value

90. 

Specify Subgroup

 Reference test + (Diagnosis of test) Reference test - (Diagnosis of test) Total

Comparison test + 91. 92. 93. 

Comparison test - 94. 95. 96. 

Total 97. 98. 99. 

N=

100. If the study reports only the sensitivity/specificity, please list it below. 

%Sensitivity

%SpecificityPositive predictive valueNegative predictive value

101. 

Specify Subgroup

 Reference test + (Diagnosis of test) Reference test - (Diagnosis of test) Total

Comparison test + 102. 103. 104. 

Comparison test - 105. 106. 107. 

SRS Form https://www.clinical-analytics.com/d2d/ul1/review.asp?mode=previewMode&articleid=1&level=32 
Racial groups

Age groupsHistory of prior GDMFamily history of DMWeightBMIOther (specify):

Please complete the tables below for calculation of sensitivity and specificity for each subgro

cells where data has been provided in the article.)

68. 

Specify Subgroup

 Reference test + (Diagnosis of test) Reference test - (Diagnosis of test) Total

Comparison test + 69. 70. 71. 

Comparison test - 72. 73. 74. 

Total 75. 76. 77. 

N=

78. If the study reports only the sensitivity/specificity, please list it below. 

%Sensitivity

%SpecificityPositive predictive valueNegative predictive value

79. 

Specify Subgroup

 Reference test + (Diagnosis of test) Reference test - (Diagnosis of test) Total

Comparison test + 80. 81. 82. 

SRS Form https://www.clinical-analytics.com/d2d/ul1/review.asp?mode=previewMode&articleid=1&level=32 
Please complete the table below for calculation of sensitivity, specificity, positive predictive value and diagnostic odds ratio for subsequent testing of th

 Reference test + (Diagnosis of test) Reference test - (Diagnosis of test) Total

Subsequent comparison test + 44. 45. 46. 

Subsequent comparison test - 47. 48. 49. 

Total 50. 51. 52. 

N=

If the study reports only the sensitivity/specificity, please list it below. Report AUC and likelihood ratio only if no other data are provided.

 %53.

Standard deviation

Standard error95% CI

Clear Selection

 Sensitivity 54. 55. 

Specificity 56. 57. 

 Positive predictive value 58. 59. 

Negative predictive value 60. 61. 

AUC 62. 63. 

Likelihood ratio 64. 65. 

66. Does the study of the comparison test provide information on the test’s performance in different subgroups (i.e., race/ethnicity, age groups)? 

Yes

No (end of form - hit submit)

Clear Selection67. If yes, check all that apply 

SRS Form https://www.clinical-anal

ytics.com/d2d/ul1/review.as

p?mode=

previewMode&articleid=1&level=32 
95% CI

Clear Selection

 Sensitivity 25. 26. 

Specificity 27. 28. 

 Positive predictive value 29. 30. 

Negative predictive value 31. 32. 

AUC 33. 34. 

Likelihood ratio 35. 36. 

37. Did the comparison test occur at more than one time subsequent to initial testing? 

Yes

No (skip to Q66)

Clear SelectionIf yes, what was the time interval from delivery to subsequent testing with the comparison test? 

38. 

Mean

MedianOther (specify:)

Clear Selection

39. 

Standard deviation

Standard errorRange

Clear Selection

Reference test 40. 41. 

Subsequent comparison test 42. 43. 

SRS Form https://www.clinical-analytics.com/d2d/ul1/review.asp?mode=previewMode&articleid=1&level=32 
Clear Selection

If yes, what was the mean (or median) time interval from delivery to each test? 

 8. 

Mean

MedianOther (specify:)

Clear Selection

9. 

Standard deviation

Standard errorRange

Clear Selection

Reference test 10. 11. 

Comparison test 12. 13. 

14. Sample size: 

Number eligible for postpartum testing

Number in study sampleNumber lost to follow-up% lost to follow-up

Please complete the table below for calculation of sensitivity, specificity, positive predictive value and diagnostic odds ratio for the comparison test. (Odata has been provided in the article.)

 Reference test + (Diagnosis of test) Reference test - (Diagnosis of test) Total

Comparison test + 15. 16. 17. 

Comparison test - 18. 19. 20. 

Total 21. 22. 23. 

N=

If the study reports only the sensitivity/specificity, please list it below. Report AUC and likelihood ratio only if no other data are provided.

 %24.

Standard deviation

Standard error

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Previewing Only: You cannot submit data from this form

Previewing at Level 32 

Reviewer Comments ( Add a Comment ) 

Refid: 1, Geremia, C. and Cianfarani, S., Insulin Sensitivity in Children Born Small for Gestational Age (SGA), Rev Diabet Stud, 1(2), 2004, p.58-65

State: Excluded, Level: 2

Save to finish later Submit Data

KQ4 Data Abstraction Form

Labor and Postpartum Management of Gestational Diabetes Mellitus

Please complete this form if study applies to KQ4

Please complete one form for each comparison test.

Reference test (to determine incidence of diabetes) (Please select the test used and enter the threshold values at each time point).

1. Reference test used: 

75g OGTT

100g OGTTFasting plasma glucoseOther test used (specify:)

2. Threshold values: 

Fasting

1 hour2 hour3 hour

3. Units for the threshold values: 

mg/dL

mmol/L

Clear Selection

Comparison Test, if comparison test used: (Please select the test used and enter the threshold values at each time point).

4. Comparison test used: 

75g OGTT

100g OGTTFasting plasma glucoseOther test used (specify:)

5. Threshold values: 

Fasting

1 hour2 hour3 hour

6. Units for the threshold values: 

mg/dL

mmol/L

Clear Selection

7. Does the article report the time interval(s) from delivery to testing? 

Yes

No

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Form took 0.109375 seconds to render

Not reported

9. Do the authors report how missing data was handled in the analysis? 

Yes

No

Clear Selection

10. Comments: 

Enlarge Shrink 

Save to finish later Submit Data

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Previewing at Level 31 

Reviewer Comments ( Add a Comment ) 

Refid: 1, Geremia, C. and Cianfarani, S., Insulin Sensitivity in Children Born Small for Gestational Age (SGA), Rev Diabet Stud, 1

(2), 2004, p.58-65 

State: Excluded, Level: 2

Save to finish later Submit Data

KQ3 Quality Form

Labor and Postpartum Management of Gestational Diabetes Mellitus

Please complete this form for studies that apply to KQ3.

Yes No

1. Are pre-specified hypotheses stated? Clear

2. Are inclusion and exclusion criteria reported? Clear

3. How was the study population sampled? 

Consecutive

Random

Convenience

Other type of sample

Not stated

Yes No

4. Were power or sample size calculations used? Clear

5. Does the article state how the outcome was defined? Clear

6. What was the loss to follow-up? 

<10%

10-20%

>20%

Not reported

7. Did the study report comparisons of those who followed up vs. those who did not on any characteristics? 

Yes

No

Clear Selection

8. What was the percent of missing data? 

<10%

10-20%

>20%

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57. Q6

58. Q1159. Q1660. Q2161. Q2662. Q3163. Q3664. Q4165. Q4666. Q51

Save to finish later Submit Data

SRS Form 

https://www.clinical-analytics.com/d2d/ul1/review.asp?mode=previewMode&articleid=1&level=30 
model

Reported in 

fully adjusted model

Unadjusted

Categorical 

(describe how this was defined, using a semicolon (;) to separate categories)

Enlarge Shrink

S99p

36. 

Please Select

37. 

Included in 

fully adjusted model

Reported in 

fully adjusted model

Unadjusted

38. 

Continuous

Categorical 

(describe how this was defined, using a semicolon (;) to separate categories)

39. Enter measure of association for each group, using a semicolon (;) to separate each group's results. Indicate reference group with "ref." Enlarge Shrink

4geg

S

99p

41. 

Please Select

42. 

Included in 

fully adjusted model

Reported in 

fully adjusted model

Unadjusted

43. 

Continuous

Categorical 

(describe how this was defined, using a semicolon (;) to separate categories)

44. Enter measure of association for each group, using a semicolon (;) to separate each group's results. Indicate reference group with "ref." Enlarge Shrink

4geg

S

99p

46. 

Please Select

47. 

Included in 

fully adjusted model

Reported in 

fully adjusted model

Unadjusted

48. 

Continuous

Categorical 

(describe how this was defined, using a semicolon (;) to separate categories)

49. Enter measure of association for each group, using a semicolon (;) to separate each group's results. Indicate reference group with "ref." Enlarge Shrink

5geg

S

99p

51. 

Please Select

52. 

Included in 

fully adjusted model

Reported in 

fully adjusted model

Unadjusted

53. 

Continuous

Categorical 

(describe how this was defined, using a semicolon (;) to separate categories)

54. Enter measure of association for each group, using a semicolon (;) to separate each group's results. Indicate reference group with "ref." Enlarge Shrink

5geg

S

99p

56. Comments: Enlarge ShrinkWhat is the unit for the risk factor mentioned in each question?

weeks years dollars mg/dL mmol/L kg pounds centimeters millimeters kg/m2 % Other (specify)

SRS Form 

https://www.clinical-analytics.com/d2d/ul1/review.asp?mode=previewMode&articleid=1&level=30 
6. 

Please Select

7. 

Included in 

fully adjusted model

Reported in 

fully adjusted model

Unadjusted

8. 

Continuous

Categorical 

(describe how this was defined, using a semicolon (;) to separate categories)

9. Enter measure of association for each group, using a semicolon (;) to separate each group's results. Indicate reference group with "ref." Enlarge Shrink

1geg

S

99p

11. 

Please Select

12. 

Included in 

fully adjusted model

Reported in 

fully adjusted model

Unadjusted

13. 

Continuous

Categorical 

(describe how this was defined, using a semicolon (;) to separate categories)

14. Enter measure of association for each group, using a semicolon (;) to separate each group's results. Indicate reference group with "ref." Enlarge Shrink

1geg

S

99p

16. 

Please Select

17. 

Included in 

fully adjusted model

Reported in 

fully adjusted model

Unadjusted

18. 

Continuous

Categorical 

(describe how this was defined, using a semicolon (;) to separate categories)

19. Enter measure of association for each group, using a semicolon (;) to separate each group's results. Indicate reference group with "ref." Enlarge Shrink

2geg

S

99p

21. 

Please Select

22. 

Included in 

fully adjusted model

Reported in 

fully adjusted model

Unadjusted

23. 

Continuous

Categorical 

(describe how this was defined, using a semicolon (;) to separate categories)

24. Enter measure of association for each group, using a semicolon (;) to separate each group's results. Indicate reference group with "ref." Enlarge Shrink

2geg

S

99p

26. 

Please Select

27. 

Included in 

fully adjusted model

Reported in 

fully adjusted model

Unadjusted

28. 

Continuous

Categorical 

(describe how this was defined, using a semicolon (;) to separate categories)

29. Enter measure of association for each group, using a semicolon (;) to separate each group's results. Indicate reference group with "ref." Enlarge Shrink

3geg

S

99p

31. 

Please Select

32. 

Included in 

fully adjusted 

33. 

Continuous

34. Enter measure of association for each group, using a semicolon (;) to separate each group's results. Indicate reference group with "ref." 

3geg

SRS Form 

https://www.clinical-analytics.com/d2d/ul1/review.asp?mode=previewMode&articleid=1&level=30 
Previewing Only: You cannot submit data from this form

Previewing at Level 30 

Reviewer Comments ( Add a Comment ) 

Refid: 1, Geremia, C. and Cianfarani, S., Insulin Sensitivity in Children Born Small for Gestational Age (SGA), Rev Diabet Stud, 1(2), 2004, p.58-65 

State: Excluded, Level: 2

Save to finish later Submit Data

KQ3 Data Abstraction Form

Labor and Postpartum Management of Gestational Diabetes Mellitus

Please complete this form for studies that apply to KQ3.

Please complete a separate form for each outcome reported by the study.1. List the measures that were used to define type 2 diabetes. (Check all that apply. Where applicable, enter the threshold used and specify if mg/dL or mmol/L.) 

Fasting blood sugar > 

Random blood sugar >Abnormal 75g OGTTHemoglobin Alc > Self reportTaking diabetes medicationsOther (specify:)

2. N of the analysis: 3. What was the time interval between delivery and time of follow-up testing? Enlarge ShrinkIndicate variables that were included and reported in fully adjusted model or unadjusted. For each risk factor included in the most fully adjusted model, indicate if it was analyzed as a catego

describe how the variable was defined, and provide the measure of association and measures of variability. Note: For categorical variables, separate the different categories using a semicolon 

Please select risk factor. Check all that 

apply for each variable.

Please briefly describe how the variable was defined.

4. Measure of Association 

RR

RHORRDIncidenceOther (specify:)

Clear Selection

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Consecutive

Random

Convenience

Other type of sample

Not stated

Yes No

9. Were power or sample size calculations used? Clear

10. Does the article state how the outcome was defined? Clear

11. What was the loss to follow-up? 

<10%

10-20%

>20%

Not reported

12. Do the authors report how loss to follow-up was handled in the analysis? 

Yes

No

Not applicable (i.e., no loss to follow-up)

Clear Selection

13. What was the percent of missing data? 

<10%

10-20%

>20%

Not reported

14. Do the authors report how missing data was handled in the analysis? 

Yes

No

Not applicable (i.e., no missing data)

Clear Selection

15. Comments: 

Enlarge Shrink 

Save to finish later Submit Data

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Previewing Only: You cannot submit data from this form

Previewing at Level 29 

Refid: 1, Geremia, C. and Cianfarani, S., Insulin Sensitivity in Children Born Small for Gestational Age (SGA), Rev Diabet Stud, 1

(2), 2004, p.58-65 

State: Excluded, Level: 2

Save to finish later Submit Data

KQ2 Quality Form

Labor and Postpartum Management of Gestational Diabetes Mellitus

Please complete this form for studies that apply to KQ2.

If the study was an RCT, answer Q1-5. Otherwise, skip to Q6.

1. Was the study described as randomized (this includes the use of words such as randomly, random, and randomization)? 

Yes (1)

No (0)

Not Reported/Can’t Tell (0)

Clear Selection

2. If yes to q1, was the randomization scheme described AND appropriate? 

Yes: (1) appropriate randomization is if each study participant is allowed to have the same chance of receiving each intervention 

and the investigators could not predict which treatment was next.

No: (-1) randomization described AND inappropriate (e.g. methods of allocation using date of birth, date of admission, hospital

numbers, or alteration should not be regarded as appropriate)

No: (0) randomization methods not described

Clear Selection

3. Was the study described as double blind? 

Yes (1)

No (0)

Not Reported/Can’t Tell (0)

Clear Selection

4. If yes to Q3, was the method of double blinding described AND appropriate? 

Yes: (1) appropriate double blinding is if neither the person doing the assessments nor the study participant could identify the 

intervention being assessed OR if the use of active placebos, identical placebos or dummies is mentioned

No: (-1) the study was described as double blind AND inappropriate (e.g. comparison of tablet vs lifestyle with no double dummy

or fake tablet given to the lifestyle group)

No: (0) no description of double blinding available and unable to tell if appropriate or not.

Clear Selection

5. Was there a description of withdrawals and drop-outs? 

Yes: (1) the number and the reasons for withdrawals in each group must be stated or state that there were no withdrawals. If 

subjects were not included in the analysis, they must state the number and reasons for not including them in the analysis.

No (0)

Clear Selection

If study was an RCT, skip Q6-14. For all other study designs, answer Q6-14.

Yes No

6. Are pre-specified hypotheses stated? Clear

7. Are inclusion and exclusion criteria reported? Clear

8. How was the study population sampled? 

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SRS Form https://www.clinical-analytics.com/d2d/ul1/review.asp?mode=previewMode&articleid=1&level=28 
Group 

1

30. 31. 32. 

lower limit

upper limit

33. 

Group 2

35. 36. 37. 

lower limit

upper limit

38. 

Group 3

40. 41. 42. 

lower limit

upper limit

43. 

Group 4

45. 46. 47. 

lower limit

upper limit

48. 

Other statistics 

50. Other measure

(specify:)

51. Other measure

(specify:)

52. Other measure

(specify:)

Group 1 53. 54. 55. Group 2 56. 57. 58. Group 3 59. 60. 61. Group 4 62. 63. 64. 

65. Comments: 

SRS Form https://www.clinical-analytics.com/d2d/ul1/review.asp?mode=previewMode&articleid=1&level=28 
Mean

MedianOther 

(specify:)

Clear Selection

Standard 

error

Standard 

deviation

Other 

(specify:)

Clear Selection

95% Confidence intervalInterquartile range (IQR)

Clear Selection

Group 1

7. 8. 9. 

lower limit

upper limit

10. 

Group 2

12. 13. 14. 

lower limit

upper limit

15. 

Group 3

17. 18. 19. 

lower limit

upper limit

20. 

Group 4

22. 23. 24. 

lower limit

upper limit

25. 

Mean difference from placebo/other group (For measures of variability, please record the standard error when availabplease record either the 95% confidence interval or the standard deviation. Always record the p-value when available

27. Point estimate (select one:)

Mean

MedianOther 

(specify:)

Clear Selection

28. Measure of variability (select one:)

Standard 

error

Standard 

deviation

Other 

(specify:)

Clear Selection

29. (Select one:)

95% Confidence interval

Interquartile range (IQR)

Clear Selection

N 

SRS Form https://www.clinical-analytics.com/d2d/ul1/review.asp?mode=previewMode&articleid=1&level=28 
Previewing Only: You cannot submit data from this form

Previewing at Level 28 

Refid: 1, Geremia, C. and Cianfarani, S., Insulin Sensitivity in Children Born Small for Gestational Age (SGA), Rev Diabet Stud, 1(2), 2004, p.58-65

State: Excluded, Level: 2

Save to finish later Submit Data

KQ2 Outcomes Form 

Labor and Postpartum Management of Gestational Diabetes 

Please complete this form if:

Study applies to KQ2

Neonatal outcomes being reported is birth weight.

Mark outcome of interest and how defined or what units used. (Check only one outcome per form)

Neonatal outcome Definition and/or units used (check all that apply)

1. 

Birth weight

2. 

grams

Other (specify:)Not reported

3. Was this an intention-to-treat analysis? 

Yes

NoNot reportedNot applicable

Clear SelectionWeight outcomes should be recorded here. (Report results for the most adjusted model.)Final measures (For measures of variability, please record the standard error when available. If the standard error is confidence interval/interquartile range or the standard deviation. Always record the p-value when available.)

4. Point estimate (select one:) 5. Measure of variability (select one:) 6. (Select one:) N 

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Group 2 115. 116. 117. Group 3 118. 119. 120. Group 4 121. 122. 123. 

124. Comments: Enlarge Shrink

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SRS Form https://www.clinical-analytics.com/d2d/ul1/review.asp?mode=previewMode&articleid=1&level=21 
Relative 

risk

Relative 

hazard

Odds 

ratio

Risk 

difference

Other 

(specify:)

Clear Selection

reference group

Standard 

error

Standard 

deviation

Other 

(specify:)

Clear Selection

Group 1

89. 90. 91. 92. 

lower limit

upper limit

Group 2

94. 95. 96. 97. 

lower limit

upper limit

Group 3

99. 100. 101. 102. 

lower limit

upper limit

Group 4

104. 105. 106. 107. 

lower limit

upper limit

Other statistics 

109. Other measure

(specify:)

110. Other measure

(specify:)

111. Other measure

(specify:)

Group 1 112. 113. 114. 

SRS Form https://www.clinical-analytics.com/d2d/ul1/review.asp?mode=previewMode&articleid=1&level=21 
Measure of Association (For measures of variability, please record the standard error when available. If the standard 

record either the 95% confidence interval or the standard deviation. Always record the p-value when available.) 

65. Point estimate (select one:)

Relative 

risk

Relative 

hazard

Odds 

ratio

Risk 

difference

Other 

(specify:)

Clear Selection

Indicate reference group

66. Measure of variability (select one:)

Standard 

error

Standard 

deviation

Other 

(specify:)

Clear Selection

95% Confidence interva

Group 1

67. 68. 69. 70. 

lower limit

upper limit

Group 2

72. 73. 74. 75. 

lower limit

upper limit

Group 3

77. 78. 79. 80. 

lower limit

upper limit

Group 4

82. 83. 84. 85. 

lower limit

upper limit

Measure of Association (For measures of variability, please record the standard error when available. If the standard record either the 95% confidence interval or the standard deviation. Always record the p-value when available.)

87. Point estimate (select one:) Indicate 88. Measure of variability (select one:) 95% Confidence interva

SRS Form https://www.clinical-analytics.com/d2d/ul1/review.asp?mode=previewMode&articleid=1&level=21 
Specifiy other 

numerator value:

Group 4

45. 

List if different from initial N

Can't tellN has not 

changed

46. 

# with 1 or more events

% with 1 or more eventsSpecify other numerator type:Specifiy other numerator value:

47. 

Incidence Rate (For measures of variability, please record the standard error when available. If the standard error is either the 95% confidence interval or the standard deviation. Always record the p-value when available.)

 Point Estimate 48. Measure of variability (select one:)

Standard error

Standard deviationOther (specify:)

Clear Selection

95% Confidence interval 

Group 1 49. 50. 51. 

lower limit

upper limit

52

Group 2 53. 54. 55. 

lower limit

upper limit

56

Group 3 57. 58. 59. 

lower limit

upper limit

60

Group 4 61. 62. 63. 

lower limit

upper limit

64

SRS Form https://www.clinical-analytics.com/d2d/ul1/review.asp?mode=previewMode&articleid=1&level=21 
Not applicable

Clear SelectionAll outcomes except blood sugar and weight should be recorded here. (Report results for the most adjusted model.)

Number of people included in analysis for each group

Numerator 35. Denominator (if person-time use

Enter amount of time below and ind

Days

WeeksMonthsYearsPerson-yearsOther (specify:)Not applicable

Group 1

36. 

List if different from initial N

Can't tellN has not 

changed

37. 

# with 1 or more events

% with 1 or more eventsSpecify other numerator type:Specifiy other numerator value:

38. 

Group 2

39. 

List if different from initial N

Can't tellN has not 

changed

40. 

# with 1 or more events

% with 1 or more eventsSpecify other numerator type:Specifiy other numerator value:

41. 

Group 3

42. 

List if different from initial N

Can't tellN has not 

changed

43. 

# with 1 or more events

% with 1 or more eventsSpecify other numerator type:

44. 

SRS Form https://www.clinical-analytics.com/d2d/ul1/review.asp?mode=previewMode&articleid=1&level=21 
Anoxia or acidosis Clinical diagnosis (criteria not given)

Claims data/ICD-9Arterial blood gas from neonateCord blood gasOther (specify):Not reported

27. 

Congenital malformation (specify):

28. 

Clinical diagnosis (criteria not given)

Claims data/ICD-9Other (specify):Not reported

29. 

Respiratory distress syndrome

30. 

Clinical diagnosis (criteria not given)

Claims data/ICD-9Other (specify):Not reported

31. 

Admission to NICU

NA 

32. Mortality 

Fetal mortality

Perinatal/neonatal mortality

33. 

Death certificate

Clinical diagnosis Chart reviewOther (specify):

34. Was this an intention-to-treat analysis? 

Yes

NoNot reported

SRS Form https://www.clinical-analytics.com/d2d/ul1/review.asp?mode=previewMode&articleid=1&level=21 
Not reported

15. 

Macrosomia

16. 

Birth weight >

Other (specify):Not reported

17. 

Large for gestational age (LGA)

18. 

weight (grams) >

percentile weight >Other (specify:)Not reported

19. 

Small for gestational age (SGA)

20. 

weight (grams) <

percentile weight <Other (specify:)Not reported

21. 

Shoulder dystocia

22. 

Clinical diagnosis (criteria not given)

Claims data/ICD-9Other (specify):Not reported

23. Birth trauma 

Clavicle bone fracture

Humerus bone fractureOther bone fracture (specify:)Nerve palsyOther (specify:)

24. 

Clinical diagnosis (criteria not given)

Claims data/ICD-9Other (specify):Not reported

25. 26. 

SRS Form https://www.clinical-analytics.com/d2d/ul1/review.asp?mode=previewMode&articleid=1&level=21 
Postpartum infection Claims data/ICD-9

Other (specify):Not reported

5. Operative vaginal delivery 

Forceps use

Vacuum useOther (specify:)

6. 

Clinical diagnosis (criteria not given)

Claims data/ICD-9Other (specify):Not reported

7. Perineal tears 

3rd degree tears

4th degree tears

8. 

Clinical diagnosis (criteria not given)

Claims data/ICD-9Other (specify):Not reported

9. Cesarean delivery after failed attempt at vaginal delivery

Failed induction

Protracted laborCesarean deliveryOther (specify:)

10. TBD 

Clinical diagnosis (criteria not given)

Claims data/ICD-9Other (specify):Not reported

Neonatal outcome Definition and/or units used (check all that apply)

11. 

Neonatal hypoglycemia

12. 

fsg<

symptomsOther (specify):Not reported

13. 

Hyperbilirubinemia

14. 

Serum bilirubin > 

Other (specify):

SRS Form https://www.clinical-analytics.com/d2d/ul1/review.asp?mode=previewMode&articleid=1&level=21 
Previewing Only: You cannot submit data from this form

Previewing at Level 21 

Reviewer Comments ( Add a Comment ) 

Refid: 1, Geremia, C. and Cianfarani, S., Insulin Sensitivity in Children Born Small for Gestational Age (SGA), Rev Diabet Stud, 1(2), 2004, p.58-65

State: Excluded, Level: 2

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KQ2 Outcomes Form 

Labor and Postpartum Management of Gestational Diabetes Mellit

Please complete this form if:

Study applies to KQ2

Maternal outcome being reported in hemorrhage, infection, perineal laceration

delivery, or failed attempt at vaginal delivery

Neonatal outcome being reported is hypoglycemia, hyperbilirubinemia, macro

shoulder dystocia, birth trauma, anoxia or acidosis, congenital malformations, 

syndrome, admission to NICU, or mortality.

Mark outcome of interest and how defined or what units used. (Check only one outcome per form)

Maternal outcome Definition and/or units used (check all that apply)

1. Hemorrhage 

Postpartum hemorrhage

Other (specify:)

2. 

Clinical diagnosis (criteria not given)

Claims data/ICD-9Other (specify):Not reported

3. Infection 

Intrapartum infection

4. TBD 

Clinical diagnosis (criteria not given)

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Form took 0.1875 seconds to render

Glucose: specify glucose measure used (such as mean glucose during pregnancy) 

Duration of gestational diabetesDuration of treatment for gestational diabetesGestational ageOther (specify):Other (specify):Other (specify):Other (specify):Other (specify):

27. Comments: Enlarge Shrink

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SRS Form https://www.clinical-analytics.com/d2d/ul1/review.asp?mode=previewMode&articleid=1&level=20 
18. Spontaneous 

labor and vaginal delivery, %19. Spontaneous labor and cesarean delivery, N20. Spontaneous labor and cesarean delivery, %21. Induced labor and vaginal delivery, N22. Induced labor and vaginal delivery, %23. Induced labor and cesarean delivery, N24. Induced labor and cesarean delivery, %

25. If an observational study, were adjustments done? 

Yes

NoNot applicable

Clear Selection26. If yes, what confounders were adjusted for? (check all that apply) 

Maternal age

RaceParityFamily History of DiabetesPrior GDMDiagnosed with GDM prior to 24 weeksPre-pregnancy weightPre-pregnancy BMIGestational weight gainOther maternal disease confounders such as thyroid disease, placental abruption, placental previaMultiple gestationSteroid use during pregnancy

SRS Form https://www.clinical-analytics.com/d2d/ul1/review.asp?mode=previewMode&articleid=1&level=20 
LMP

1st trimester ultrasound2nd trimester ultrasoundOther

If intrauterine fetal weight or another measure of fetal size (e.g. abdominal circumference) was used to determine timing of delivery, what was the meaor median of measure provided, please give details (e.g. mean estimated intrauterine fetal weight for group 1). 

Group 1 Group 2 Group 3 Group 4

9. Grams

10. AC percentile11. Other (specify:)12. Mean13. Median14. Standard deviation

15. What was used to assess the patient's readiness for induction? 

Bishop's score

Fetal fibronectinOther (specify:)

16. What was the method for induction? 

Mechanical interventions

Misoprostil (saline infusion)Monitoring/conservative careOxytocinProstaglandin E2 gel Stripping of membranes Other (specify:)

What was the N and % of patients who ultimately had each outcome? 

Group 1 Group 2 Group 3 Group 4 

17. Spontaneous labor and vaginal delivery, N

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Previewing at Level 20 

Reviewer Comments ( Add a Comment ) 

Refid: 1, Geremia, C. and Cianfarani, S., Insulin Sensitivity in Children Born Small for Gestational Age (SGA), Rev Diabet Stud, 1(2), 2004, p.58-65

State: Excluded, Level: 2

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KQ2 Intervention Form

Labor and Postpartum Management of Gestational Diabetes Mellitus

Please complete this form for studies that apply to KQ2.

What was the initial planned management for each group? 

Group 1 Group 2 Group 3 

1. Spontaneous labor and vaginal delivery (also termed “expectant management”) (could include those augmented with Pitocin)

2. Induced labor and vaginal delivery3. “Elective” cesarean delivery (also termed “planned” cesarean delivery)4. Other (specify:)

If gestational age (weeks) was used to determine timing of delivery, what was the timing (i.e. gestational age) for each group? (Please write in the tim

Group 1 Group 2 Group 3 Group 4

5. Weeks

If the mean gestational age of delivery for a group is provided, please also include this information. 

Group 1 Group 2 Group 3 Group 4

6. Mean

7. Standard deviation

8. How was gestational age determined? 

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If study was an RCT, skip Q6-14. For all other study designs, answer Q6-14.

Yes No

7. Are pre-specified hypotheses stated? Clear

8. Are inclusion and exclusion criteria reported? Clear

9. How was the study population sampled? 

Consecutive

Random

Convenience

Other type of sample

Not stated

Yes No

10. Were power or sample size calculations used? Clear

11. Does the article state how the outcome was defined? Clear

12. What was the loss to follow-up? 

<10%

10-20%

>20%

Not reported

13. Do the authors report how loss to follow-up was handled in the analysis? 

Yes

No

Not applicable (i.e., no loss to follow-up)

Clear Selection

14. What was the percent of missing data? 

<10%

10-20%

>20%

Not reported

15. Do the authors report how missing data was handled in the analysis? 

Yes

No

Not applicable (i.e., no missing data)

Clear Selection

Save to finish later Submit Data

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Previewing at Level 19 

Reviewer Comments ( Add a Comment ) 

Refid: 1, Geremia, C. and Cianfarani, S., Insulin Sensitivity in Children Born Small for Gestational Age (SGA), Rev Diabet Stud, 1

(2), 2004, p.58-65 

State: Excluded, Level: 2

Save to finish later Submit Data

KQ1 Quality Form

Labor and Postpartum Management of Gestational Diabetes Mellitus

Please complete this form for studies that apply to KQ1.

1. Was the study described as randomized (this includes the use of words such as randomly, random, and randomization)? 

Yes (1)

No (0)

Not Reported/Can’t Tell (0)

Clear Selection

2. If yes to q1, was the randomization scheme described AND appropriate? 

Yes: (1) appropriate randomization is if each study participant is allowed to have the same chance of receiving each intervention 

and the investigators could not predict which treatment was next.

No: (-1) randomization described AND inappropriate (e.g. methods of allocation using date of birth, date of admission, hospital

numbers, or alteration should not be regarded as appropriate)

No: (0) randomization methods not described

Clear Selection

3. Was the study described as double blind? 

Yes (1)

No (0)

Not Reported/Can’t Tell (0)

Clear Selection

4. If yes to Q3, was the method of double blinding described AND appropriate? 

Yes: (1) appropriate double blinding is if neither the person doing the assessments nor the study participant could identify the 

intervention being assessed OR if the use of active placebos, identical placebos or dummies is mentioned

No: (-1) the study was described as double blind AND inappropriate (e.g. comparison of tablet vs lifestyle with no double dummy

or fake tablet given to the lifestyle group)

No: (0) no description of double blinding available and unable to tell if appropriate or not.

Clear Selection

5. Was there a description of withdrawals and drop-outs? 

Yes: (1) the number and the reasons for withdrawals in each group must be stated or state that there were no withdrawals. If 

subjects were not included in the analysis, they must state the number and reasons for not including them in the analysis.

No (0)

Clear Selection

6. Comments: 

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Group 2Group 3 109. 110. 111. Group 4 112. 113. 114. 

115. Comments: Enlarge Shrink

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SRS Form https://www.clinical-analytics.com/d2d/ul1/review.asp?mode=previewMode&articleid=1&level=17 
Mean difference from placebo/other group (For measures of variability, please record the standard error when availab

please record either the 95% confidence interval or the standard deviation. Always record the p-value when available

77. Point estimate (select one:)

Mean

MedianOther 

(specify:)

Clear Selection

78. Measure of variability (select one:)

Standard 

error

Standard 

deviation

Other 

(specify:)

Clear Selection

79. (Select one:)

95% Confidence interval

Interquartile range (IQR)

Clear Selection

N 

Group 1

80. 81. 82. 

lower limit

upper limit

83. 

Group 2

85. 86. 87. 

lower limit

upper limit

88. 

Group 3

90. 91. 92. 

lower limit

upper limit

93. 

Group 4

95. 96. 97. 

lower limit

upper limit

98. 

Other statistics 

100. Other measure

(specify:)

101. Other measure

(specify:)

102. Other measure

(specify:)

Group 1 103. 104. 105. 

106. 107. 108. 

SRS Form https://www.clinical-analytics.com/d2d/ul1/review.asp?mode=previewMode&articleid=1&level=17 
upper 

limit

Group 4

49. 50. 51. 

lower limit

upper limit

52. 

Mean difference from baseline (For measures of variability, please record the standard error when available. If the st

either the 95% confidence interval or the standard deviation. Always record the p-value when available.)

54. Point estimate (select one:)

Mean

MedianOther 

(specify:)

Clear Selection

55. Measure of variability (select one:)

Standard 

error

Standard 

deviation

Other 

(specify:)

Clear Selection

56. (Select one:)

95% Confidence interval

Interquartile range (IQR)

Clear Selection

N 

Group 1

57. 58. 59. 

lower limit

upper limit

60. 

Group 2

62. 63. 64. 

lower limit

upper limit

65. 

Group 3

67. 68. 69. 

lower limit

upper limit

70. 

Group 4

72. 73. 74. 

lower limit

upper limit

75. 

SRS Form https://www.clinical-analytics.com/d2d/ul1/review.asp?mode=previewMode&articleid=1&level=17 
Group 

2

16. 17. 18. 

lower limit

upper limit

19. 

Group 3

21. 22. 23. 

lower limit

upper limit

24. 

Group 4

26. 27. 28. 

lower limit

upper limit

29. 

Final measures (For measures of variability, please record the standard error when available. If the standard error is confidence interval or the standard deviation. Always record the p-value when available.)

31. Point estimate (select one:)

Mean

MedianOther 

(specify:)

Clear Selection

32. Measure of variability (select one:)

Standard 

error

Standard 

deviation

Other 

(specify:)

Clear Selection

33. (Select one:)

95% Confidence interval

Interquartile range (IQR)

Clear Selection

N 

Group 1

34. 35. 36. 

lower limit

upper limit

37. 

Group 2

39. 40. 41. 

lower limit

upper limit

42. 

Group 3

44. 45. 46. 

lower limit

47. 

SRS Form https://www.clinical-analytics.com/d2d/ul1/review.asp?mode=previewMode&articleid=1&level=17 
pounds

Other (specify:)Not reported

Neonatal outcome Definition and/or units used (check all that apply)

5. 

Birth weight

6. 

grams

Other (specify:)Not reported

7. Was this an intention-to-treat analysis? 

Yes

NoNot reportedNot applicable

Clear SelectionBlood sugar and weight outcomes should be recorded here. (Report results for the most adjusted model.)Baseline measures (For measures of variability, please record the standard error when available. If the standard erroconfidence interval or the standard deviation. Always record the p-value when available.)

8. Point estimate (select one:)

Mean

MedianOther 

(specify:)

Clear Selection

9. Measure of variability (select one:)

Standard 

error

Standard 

deviation

Other 

(specify:)

Clear Selection

10. (Select one:)

95% Confidence interval

Interquartile range (IQR)

Clear Selection

N 

Group 1

11. 12. 13. 

lower limit

upper limit

14. 

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Previewing at Level 17 

Reviewer Comments ( Add a Comment ) 

Refid: 1, Geremia, C. and Cianfarani, S., Insulin Sensitivity in Children Born Small for Gestational Age (SGA), Rev Diabet Stud, 1(2), 2004, p.58-65

State: Excluded, Level: 2

Save to finish later Submit Data

KQ1 Outcomes Form 

Labor and Postpartum Management of Gestational Diabetes 

Please complete this form if:

Study applies to KQ1

Maternal outcome being reported is glycemic control or mat

Neonatal outcomes being reported is birth weigh

Mark outcome of interest and how defined or what units used. (Check only one outcome per form)

Maternal outcome Definition and/or units used (check all that apply)

1. Glycemic control during treatment (choose one:) 

Fasting plasma glucose during pregnancy

Pre-prandial glucose during pregnancy1 hour postprandial glucose during pregnancy2 hour postprandial glucose during pregnancyCombined glucose during pregnancyOther (specify:)

Clear Selection

2. 

mmol/L

mg/dLOther (specify:)Not reported

3. 

Maternal weight

4. 

kg

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Group 2 84. 85. 86. Group 3 87. 88. 89. Group 4 90. 91. 92. 

93. Comments: Enlarge Shrink

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SRS Form https://www.clinical-analytics.com/d2d/ul1/review.asp?mode=previewMode&articleid=1&level=16 
56. Point estimate (select one:)

Relative 

risk

Relative 

hazard

Odds 

ratio

Risk 

difference

Other 

(specify:)

Clear Selection

Indicate reference group

57. Measure of variability (select one:)

Standard 

error

Standard 

deviation

Other 

(specify:)

Clear Selection

95% Confidence interva

Group 1

58. 59. 60. 61. 

lower limit

upper limit

Group 2

63. 64. 65. 66. 

lower limit

upper limit

Group 3

68. 69. 70. 71. 

lower limit

upper limit

Group 4

73. 74. 75. 76. 

lower limit

upper limit

Other statistics 

78. Other measure

(specify:)

79. Other measure

(specify:)

80. Other measure

(specify:)

Group 1 81. 82. 83. 

SRS Form https://www.clinical-analytics.com/d2d/ul1/review.asp?mode=previewMode&articleid=1&level=16 
Measure of Association (For measures of variability, please record the standard error when available. If the standard 

record either the 95% confidence interval or the standard deviation. Always record the p-value when available.)

34. Point estimate (select one:)

Relative 

risk

Relative 

hazard

Odds 

ratio

Risk 

difference

Other 

(specify:)

Clear Selection

Indicate reference group

35. Measure of variability (select one:)

Standard 

error

Standard 

deviation

Other 

(specify:)

Clear Selection

95% Confidence interva

Group 1

36. 37. 38. 39. 

lower limit

upper limit

Group 2

41. 42. 43. 44. 

lower limit

upper limit

Group 3

46. 47. 48. 49. 

lower limit

upper limit

Group 4

51. 52. 53. 54. 

lower limit

upper limit

Measure of Association (For measures of variability, please record the standard error when available. If the standard record either the 95% confidence interval or the standard deviation. Always record the p-value when available.)

SRS Form https://www.clinical-analytics.com/d2d/ul1/review.asp?mode=previewMode&articleid=1&level=16 
Specifiy other 

numerator value:

Group 4

14. 15. 

# with 1 or more events

% with 1 or more eventsMean # of eventsSpecify other numerator type:Specifiy other numerator value:

16. 

Incidence Rate (For measures of variability, please record the standard error when available. If the standard error is either the 95% confidence interval or the standard deviation. Always record the p-value when available.)

 Point Estimate 17. Measure of variability (select one:)

Standard error

Standard deviationOther (specify:)

Clear Selection

95% Confidence interval 

Group 1 18. 19. 20. 

lower limit

upper limit

21

Group 2 22. 23. 24. 

lower limit

upper limit

25

Group 3 26. 27. 28. 

lower limit

upper limit

29

Group 4 30. 31. 32. 

lower limit

upper limit

33

SRS Form https://www.clinical-analytics.com/d2d/ul1/review.asp?mode=previewMode&articleid=1&level=16 
Number of people included in 

analysis for each group

Numerator 4. Denominator (if person-time used or 

Enter amount of time below and indicat

Days

WeeksMonthsYearsPerson-yearsOther (specify:)

Group 1

5. 6. 

# with 1 or more events

% with 1 or more eventsMean # of eventsSpecify other numerator type:Specifiy other numerator value:

7. 

Group 2

8. 9. 

# with 1 or more events

% with 1 or more eventsMean # of eventsSpecify other numerator type:Specifiy other numerator value:

10. 

Group 3

11. 12. 

# with 1 or more events

% with 1 or more eventsMean # of eventsSpecify other numerator type:

13. 

SRS Form https://www.clinical-analytics.com/d2d/ul1/review.asp?mode=previewMode&articleid=1&level=16 
Previewing Only: You cannot submit data from this form

Previewing at Level 16 

Reviewer Comments ( Add a Comment ) 

Refid: 1, Geremia, C. and Cianfarani, S., Insulin Sensitivity in Children Born Small for Gestational Age (SGA), Rev Diabet Stud, 1(2), 2004, p.58-65

State: Excluded, Level: 2

Save to finish later Submit Data

KQ1 Outcomes Form 

Labor and Postpartum Management of Gestational Diabetes Mellit

Please complete this form if:

Study applies to KQ1

Maternal outcome being reported is hypoglycemia.

Mark outcome of interest and how defined or what units used. (Check only one outcome per form)

Maternal outcome Definition and/or units used (check all that apply)

1. 

Maternal hypoglycemia

2. 

fsg<

symptomsOther (specify):Not reported

3. Was this an intention-to-treat analysis? 

Yes

NoNot reportedNot applicable

Clear SelectionAll outcomes except blood sugar and weight should be recorded here. (Report results for the most adjusted model.)

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Form took 0.421875 seconds to render

Other statistics 

109. Other measure

(specify:)

110. Other measure

(specify:)

111. Other measure

(specify:)

Group 1 112. 113. 114. Group 2 115. 116. 117. Group 3 118. 119. 120. Group 4 121. 122. 123. 

124. Comments: Enlarge Shrink

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limit

Measure of Association (For measures of variability, please record the standard error when available. If the standard record either the 95% confidence interval or the standard deviation. Always record the p-value when available.)

87. Point estimate (select one:)

Relative 

risk

Relative 

hazard

Odds 

ratio

Risk 

difference

Other 

(specify:)

Clear Selection

Indicate reference group

88. Measure of variability (select one:)

Standard 

error

Standard 

deviation

Other 

(specify:)

Clear Selection

95% Confidence interva

Group 1

89. 90. 91. 92. 

lower limit

upper limit

Group 2

94. 95. 96. 97. 

lower limit

upper limit

Group 3

99. 100. 101. 102. 

lower limit

upper limit

Group 4

104. 105. 106. 107. 

lower limit

upper limit

SRS Form https://www.clinical-analytics.com/d2d/ul1/review.asp?mode=previewMode&articleid=1&level=7 
Group 4 61. 62. 63. 

lower limit

upper limit

64

Measure of Association (For measures of variability, please record the standard error when available. If the standard record either the 95% confidence interval or the standard deviation. Always record the p-value when available.)

65. Point estimate (select one:)

Relative 

risk

Relative 

hazard

Odds 

ratio

Risk 

difference

Other 

(specify:)

Clear Selection

Indicate reference group

66. Measure of variability (select one:)

Standard 

error

Standard 

deviation

Other 

(specify:)

Clear Selection

95% Confidence interva

Group 1

67. 68. 69. 70. 

lower limit

upper limit

Group 2

72. 73. 74. 75. 

lower limit

upper limit

Group 3

77. 78. 79. 80. 

lower limit

upper limit

Group 4

82. 83. 84. 85. 

lower limit

upper 

SRS Form https://www.clinical-analytics.com/d2d/ul1/review.asp?mode=previewMode&articleid=1&level=7 
from initial N

Can''t tellN has not 

changed

events% with 1 or more eventsSpecify other numerator type:Specifiy other numerator value:

Group 4

45. 

List if different from initial N

Can''t tellN has not 

changed

46. 

# with 1 or more events

% with 1 or more eventsSpecify other numerator type:Specifiy other numerator value:

47. 

Incidence Rate (For measures of variability, please record the standard error when available. If the standard error is either the 95% confidence interval or the standard deviation. Always record the p-value when available.)

 Point Estimate 48. Measure of variability (select one:)

Standard error

Standard deviationOther (specify:)

Clear Selection

95% Confidence interval 

Group 1 49. 50. 51. 

lower limit

upper limit

52

Group 2 53. 54. 55. 

lower limit

upper limit

56

Group 3 57. 58. 59. 

lower limit

upper limit

60

SRS Form https://www.clinical-analytics.com/d2d/ul1/review.asp?mode=previewMode&articleid=1&level=7 
Yes

NoNot reportedNot applicable

Clear SelectionAll outcomes except blood sugar and weight should be recorded here. (Report results for the most adjusted model.)

Number of people included in analysis for each group

Numerator 35. Denominator (if person-time use

Enter amount of time below and ind

Days

WeeksMonthsYearsPerson-yearsOther (specify:)Not applicable

Group 1

36. 

List if different from initial N

Can''t tellN has not 

changed

37. 

# with 1 or more events

% with 1 or more eventsSpecify other numerator type:Specifiy other numerator value:

38. 

Group 2

39. 

List if different from initial N

Can''t tellN has not 

changed

40. 

# with 1 or more events

% with 1 or more eventsSpecify other numerator type:Specifiy other numerator value:

41. 

Group 3

42. 

List if different 

43. 

# with 1 or more 

44. 

SRS Form https://www.clinical-analytics.com/d2d/ul1/review.asp?mode=previewMode&articleid=1&level=7 
Other bone fracture (specify:)

Nerve palsyOther (specify:)

Other (specify):Not reported

25. 

Anoxia or acidosis

26. 

Clinical diagnosis (criteria not given)

Claims data/ICD-9Arterial blood gas from neonateCord blood gasOther (specify):Not reported

27. 

Congenital malformation (specify):

28. 

Clinical diagnosis (criteria not given)

Claims data/ICD-9Other (specify):Not reported

29. 

Respiratory distress syndrome

30. 

Clinical diagnosis (criteria not given)

Claims data/ICD-9Other (specify):Not reported

31. 

Admission to NICU

 NA 

32. Mortality 

Fetal mortality

Perinatal/neonatal mortality

33. 

Death certificate

Clinical diagnosis Chart reviewOther (specify):

34. Was this an intention-to-treat analysis? 

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Not reported

13. 

Hyperbilirubinemia

14. 

Serum bilirubin > 

Other (specify):Not reported

15. 

Macrosomia

16. 

Birth weight >

Other (specify):Not reported

17. 

Large for gestational age (LGA)

18. 

weight (grams) >

percentile weight >Other (specify:)Not reported

19. 

Small for gestational age (SGA)

20. 

weight (grams) <

percentile weight <Other (specify:)Not reported

21. 

Shoulder dystocia

22. 

Clinical diagnosis (criteria not given)

Claims data/ICD-9Other (specify):Not reported

23. Birth trauma 

Clavicle bone fracture

Humerus bone fracture

24. 

Clinical diagnosis (criteria not given)

Claims data/ICD-9

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Other (specify):

Not reported

3. C-section 

Elective C-section

Emergency C-sectionTotal C-sectionsOther (specify:)

4. 

Clinical diagnosis (criteria not given)

Claims data/ICD-9Other (specify):Not reported

5. Hemorrhage 

Intrapartum hemorrhage

Postpartum hemorrhageOther (specify:)

6. 

Clinical diagnosis (criteria not given)

Claims data/ICD-9Other (specify):Not reported

7. Operative vaginal delivery 

Forceps use

Vacuum useOther (specify:)

8. 

Clinical diagnosis (criteria not given)

Claims data/ICD-9Other (specify):Not reported

9. Perineal tears 

3rd degree tears

4th degree tears

10. 

Clinical diagnosis (criteria not given)

Claims data/ICD-9Other (specify):Not reported

Neonatal outcome Definition and/or units used (check all that apply)

11. 

Neonatal hypoglycemia

12. 

fsg<

symptomsOther (specify):

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Refid: 1, Geremia, C. and Cianfarani, S., Insulin Sensitivity in Children Born Small for Gestational Age (SGA), Rev Diabet Stud, 1(2), 2004, p.58-65

State: Excluded, Level: 2

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KQ1 Outcomes Form 

Labor and Postpartum Management of Gestational Diabetes Mellit

Please complete this form if:

Study applies to KQ1

Maternal outcome being reported is pre-eclampsia, c-section, hemorrhage, operat

perineal tears

Neonatal outcome being reported is hypoglycemia, hyperbilirubinemia, macro

shoulder dystocia, birth trauma, anoxia or acidosis, congenital malformations, 

syndrome, admission to NICU, or mortality.

Mark outcome of interest and how defined or what units used. (Check only one outcome per form)

Maternal outcome Definition and/or units used (check all that apply)

1. 

Pre-eclampsia

2. 

Clinical diagnosis (criteria not given)

Claims data/ICD-9Blood pressure (specify systolic 

and/or diastolic):

 Systolic:  Diastolic: 

Proteinuria: 

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Yes

NoNot applicable

Clear Selection44. If yes, what confounders were adjusted for? (check all that apply) 

Maternal age

RaceParityFamily History of DiabetesPrior GDMDiagnosed with GDM prior to 24 weeksPre-pregnancy weightPre-pregnancy BMIGestational weight gainOther maternal disease confounders such as thyroid disease, placental abruption, placental previaMultiple gestationSteroid use during pregnancyGlucose: specify glucose measure used (such as mean glucose during pregnancy) Duration of gestational diabetesDuration of treatment for gestational diabetesOther (specify):Other (specify):Other (specify):Other (specify):Other (specify):

45. Please write in any additional comments regarding key question 1 

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If escalated, what were the mean and max dose of medication for each group (if applicable)? 

Group 1 Group 2 Group 3 Group 4

34. Mean 

35. Max

Group 1 Group 2 Group 3 

36. What were the target glucose values for each group? 

(Enter NR if not reported.)

37. What was the unit for the target glucose values in above question? 

mmol/l 

mg/dL other: specify

Clear Selection38. Are the target glucose values in Q36: 

Fasting glucose

1 hour postprandial glucose2 hour postprandial glucoseNot specified

Clear Selection(If assignment to treatment was non-randomized, answer:)

39. Were there different cut-points in glucose used for assigning subjects to each treatment group? 

Yes

NoNot applicable

Clear Selection

Group 1 Group 2 Group 3 

40. At what level of glucose was the decision made 

to add insulin, switch to insulin or add oral? 

For each group, report the number and/or percent of participants who added insulin to their regimen, switched their regimen to insulin or added oral to 

Group 1 Group 2 Group 3 Group 4 

41. Number

42. Percent

43. If an observational study, were adjustments done? 

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12. Insulin switched to oral

13. Insulin added to diet14. Insulin added to oral15. Oral added to diet16. Oral added to insulin17. Other (Specify): 

What were the starting dose, units, and number of times a day for each group (if applicable)? 

 Group 1 Group 2 Group 3 

Dose 18. 19. 20. 

Unit 22. 

mg

gramsIUUnits/kgOther 

(specify):

23. 

mg

gramsIUUnits/kgOther 

(specify):

24. 

mg

gramsIUUnits/kgOther 

(specify):

25. 

(spe

# times per day 

26. 27. 28. 

Was the dose of drug fixed or escalated for each group (if applicable)? 

Group 1 Group 2 Group 3 Group 4

30. Fixed 

31. Escalated 32. Not Specified 33. Other (Specify): 

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Refid: 1, Geremia, C. and Cianfarani, S., Insulin Sensitivity in Children Born Small for Gestational Age (SGA), Rev Diabet Stud, 1(2), 2004, p.58-65

State: Excluded, Level: 2

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KQ1 Intervention Form

Labor and Postpartum Management of Gestational Diabetes Mellit

Please complete this form for studies that apply to KQ1.

Select the intervention at baseline for each group. (Check all that apply) 

Group 1 Group 2 Group 3 

1. Diet 

2. NPH Insulin 3. Regular insulin 4. Lispro insulin5. Insulin pump6. Metformin7. Sulfonylurea8. Placebo9. Diet switched to oral (either metformin or sulfonylurea)10. Diet switched to insulin11. Oral switched to insulin

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Gestational age at test is not reported

For the test used, enter the mean or median glucose values of the results of the test.

Group 1 Group 2 Group 3 Group 4 Tota

50g

3 hour, 100g OGTT Fasting 

 1 hr 2 hr 3 hr

2 hour, 75g OGTT Fasting 

 1 hr 2 hr

Values are: 

Mean

MedianRangeOther measure (specify)Glucose values are not reported

77. Comments: Enlarge Shrink

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100g, O'Sullivan or NDDG (National 

Diabetes Data Group

105 mg/dL or5.8 mmol/L 

190 mg/dL or

10.6 mmol/L 

165 mg/

9.2 mmo

75g, WHO (World Health 

Organization)

126 mg/dL or7.0 mmol/L 

n/a 140 mg/

7.8 mmo

75g, ADA (American Diabetes 

Association)

95 mg/dL or5.3 mmol/L 

180 mg/dL or

10.0 mmol/L 

155 mg/

8.6 mmo

75g, CDA (Canadian Diabetes 

Association)

95 mg/dL or5.3 mmol/L 

190 mg/dL or

10.6 mmol/L 

160 mg/

8.9 mmo

Other 

test used (specify name of test here and enter threshold values for the appropriate times)

mg/dL

mmol/L

mg/dL

mmol/L

mg/dL

mmol/L

75g OGTT, threshold value not 

specified

n/a n/a n/a 

100g OGTT, threshold value not 

specified

n/a n/a n/a 

For the test used, enter the mean, median or range of gestational age when the test was conducted. 

66. Gestational age at test, mean, median or range in weeks 

50g

3 hour, 100g OGTT2 hour, 75g OGTTOther test

67. Values are: 

Mean

MedianRangeOther measure (specify)

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Group 1 Group 2 Group 3 Group 4 

39. Diet, n

40. Diet, %41. Oral hypoglycemics, n42. Oral hypoglycemics, %43. Insulin, n44. Insulin, %

Specify management method Group 1 Group 2 Group 3 

45. Other method of management, n

46. Other method of management, %47. Other method of management, n48. Other method of management, %49. Other method of management, n50. Other method of management, %

Other population characteristics(Only include other population characteristics that either are statistically significant or considered a confounder.)

Other Group 1 Group 2 Group 3 

51. Other (specify)

52. Other (specify)53. Other (specify)

OGTT

What was the threshold value for the OGTT? 

 Fasting 1 hour 2 ho

100g, Carpenter and Coustan criteria

95 mg/dL or5.3 mmol/L 

180 mg/dL or

10.0 mmol/L 

155 mg/

8.6 mmo

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Mean

MedianRangeOtherNot reported

Clear Selection

Group 1 Group 2 Group 3 Group 4 

24. Pre-pregnancy weight

25. First trimester weight26. Pregnancy weight gain27. Postpartum weight28. Pre-pregnancy BMI29. Pregnancy BMI at delivery30. Postpartum BMI

Previous pregnancies/live births

Group 1 Group 2 Group 3 

31. Number of previous pregnancies, mean (gravida)

32. Number of previous live births, mean (parity)

Specify parity category Group 1 Group 2 Group 3 

33. Other parity

34. Other parity35. Other parity36. Other parity

Gestational age at time of enrollment

Group 1 Group 2 Group 3 

37. Gestational age at time of enrollment, mean weeks

38. Gestational age at time of enrollment, range in weeks

Method of GDM management during pregnancy

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Age

Group 1 Group 2 Group 3 Group 4 

4. Mean age

5. Age range

Specify age category Group 1 Group 2 Group 3 

6. Other age

7. Other age8. Other age9. Other age

Race

Group 1 Group 2 Group 3 Group 4 

10. African American, n

11. African American, %12. Caucasian, n13. Caucasian, %14. Asian/Asian American, n15. Asian/Asian American, %16. Hispanic/Latino, n17. Hispanic/Latino, %

Specify race Group 1 Group 2 Group 3 

18. Other race, n

19. Other race, %20. Other race, n21. Other race, %

22. 

Race not reported

Weight/BMI

23. Weight/BMI values are: 

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Refid: 1, Geremia, C. and Cianfarani, S., Insulin Sensitivity in Children Born Small for Gestational Age (SGA), Rev Diabet Stud, 1(2), 2004, p.58-65

State: Excluded, Level: 2

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General Form - Part 2 

Labor and Postpartum Management of Gestational Diabetes 

Please complete this form for ALL included studies.

Please respond to the following questions for the ENTIRE study. 

Study Population Characteristics

1. Does the study include more than 1 group? 

Yes, specify number of groups

No ->FILL IN TOTAL COLUMN FOR Q4-Q39.

Clear SelectionPlease fill in the study population characteristics below. (Enter data only for relevant groups.) (You do NOT need to enter the standard deviatio"Total" column only if there are no study groups.) (For KQ4, include the data for the total sample under the total column.)

Group 1 Group 2 Group 3 

2. Please provide a one word name for each 

group indicated in question above. List groups in order of increasing dosage of the intervention, e.g. for KQ1, group 1= placebo (or control), group 2 = 0.7 U/Kg Insulin, group 3 = 2.5 mg glyburide, group 4 = 425mg metformin; e.g., for KQ2, expectant management = group 1.

3. N enrolled

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Early diagnosis of GDM (1st trimester)

Fasting plasma glucose at time of diagnosisTemporal pattern of hyperglycemia Method of glucose control Poor glycemic control Characteristics of delivery Preterm labor Macrosomia LGA SGA 

Pre-pregnancy weight Pregnancy weight gain High saturated fat diet Physical activity level Postpartum factorsPostpartum weight loss Postpartum weight retention Postpartum BMI Breastfeeding Contraceptive use Postpartum depression Psychological characteristics 

Insulin antibodies Anti-islet cell anti-GAD C-peptide Pro-insulin 

8. KEY QUESTION 4: What are the performance characteristics (sensitivity, specificity, and reproducibility) of tests for diagnosing diabetes when condpatients after pregnancy? Are there differences in the performance characteristics of the test results based on sub-group analysis? 

Applies to KQ 4

9. Reviewer comments: Enlarge Shrink10. Reviewer initials (only enter if sharing a user id). Enlarge Shrink11. Applies to KQ3, diabetes only AND: 

Reports relative measure

Does not report relative measure

Clear Selection12. Observational study that applies to KQ1 and: 

compares glyburide/glibenclamide to insulin

compares insulin to another insulinhas another relevant comparisondoes not have a comparison of interest

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Applies to KQ 2b: What is the evidence for vaginal labor induction at 40 weeks compared to labor induction at an earlier gestational age (<40 wee

pregnancy of gestational diabetes mellitus? i. labor induction at <40 weeks v labor induction at 40 weeks ii. labor induction at 40 weeks v spontaneous labor iii. labor induction at <40 weeks v spontaneous labor

Applies to KQ 2c: How is the estimated intrauterine fetal weight related to outcomes of management of GDM with medically indicated cesarean d

gestational age range) of labor induction?

Applies to KQ 2d: How is gestational age related to outcomes of management of GDM with medically indicated cesarean delivery or choice of tim

age range) of labor induction?

 Maternal Outcomes: · postpartum hemorrhage,  · intrapartum infection,  · postpartum infection,  · third or fourth degree lacerations or any other perineal laceration and episiotomy,  · operative vaginal delivery  · cesarean delivery after failed attempt at vaginal delivery (e.g., failed induction, protracted labor) 

 Neonatal Outcomes:  · macrosomia,  · LGA or SGA,  · respiratory distress syndrome,  · birth weight,  · shoulder dsytocia,  · birth trauma,  · nerve palsy and fracture,  · anoxia or acidosis,  · hypoglycemia, and hyperbilirubinemia, · neonatal intensive care admissions,  · congenital malformations,  · mortality 

6. KEY QUESTION 3: What risk factors are associated with short-term and long-term development of 1) impaired glucose tolerance, and/or 2) type 2 d

pregnancy with GDM? (choose all that apply) Note: If the study DOES NOT use an accepted diagnostic method (FBS > 125 mg/dl; 75g OGTT, 2-hour glusose > 200 mg/dl; random glucose > 200 m

diabetes mellitus; current use of an antidiabetic medication) for type 2 diabetes mellitus it is not eligible for Q3

(Note: exclude if evaluates risk factors for only impaired glucose tolerance)

Applies to KQ3 for type 2 diabetes mellitus only or has a separate analysis for type 2 diabetes mellitus only

Applies to KQ3 for impaired glucose tolerance and type 2 diabetes combined

7. For studies that apply to KQ3, was a multivariate analysis reported? 

Multivariate analysis reported

Multivariate analysis not reported

Clear Selection

Risk Factors for KQ3

Demographics Age Race Income/Eductation/SES Pregnancy Characteristics 

Cumulative pregnancy-related factorsParity # of prior GDM pregnancies # prior macrosomic infants Maternal lifestyle 

Additional factorsWaist-to-hip ratio Waist circumferenceClinical measuresInsulin 

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2. UNCLEAR 

unclear (can not determine from abstract alone OR no abstract available)--move to Article Review without identifying a Key Question

Clear SelectionThis article may apply to one of the following Key Questions (KQ)--choose all that apply. 3. KEY QUESTION 1: What is the evidence for the risks and benefits of FDA approved oral hypoglycemic agents (glyburide) to treat GDM and metformapproved, it is used in certain clinical situations) compared to all types of insulin approved by the FDA for use in pregnancy for both the mother and neNote: If the study DOES NOT contain an appropriate comparison group (see listing of appropriate comparisons below) it is not eligible for Q1. Note: FDA approved insulins for use during pregnancy: lispro, aspart, regular, nph, and the insulin pump that includes lispro or aspart

Applies to KQ 1

4. For studies that apply to KQ1, indicate the study design: 

RCTs

Observational study or other study type

Clear Selection

 Comparisons: i. diet v approved insulin  ii. diet v metformin  iii. diet v gliburide  iv. metformin v approved insulin  v. metformin v gliburide  vi. gliburide v insulin  vii. approved insulin v approved insulin  viii. metformin v placebo  ix. gliburide v placebo  x. insulin v placebo 

 Maternal Outcomes: · hypoglycemia,  · glycemic control (Note: studies measuring glycemic control should report specific measures (e.g., fasting blood sugar, 1 hour and 2 hour post prandial glucose)),  · cesarean delivery,  · pre-eclampsia, and postpartum hemorrhage  · maternal weight,  · perineal lacerations,  · operative vaginal delivery 

 N ·  ·  · syn ·  ·  ·  ·  ·  · hyp · adm ·  · 

5. KEY QUESTION 2: What is the evidence that medically indicated cesarean delivery or choice of timing of induction result in beneficial or harmful ne

outlined above for Key Question #1) and maternal outcomes? Note: intended method of delivery should be clearly defined (e.g., for cesarean delivery, groups must be defined as either elective cesarean or cesareNote: studies should report a measure of gestational age at induction for KQ2b Note: studies should only be included for KQ2c if intrauterine fetal weight was measured using ultrasound

Applies to KQ 2a: What is the evidence for elective cesarean delivery at term compared to an attempt at vaginal delivery (spontaneous or induced

i. cesarean v spontaneous labor and vaginal delivery at term ii. cesarean v induced labor and vaginal delivery at term iii. cesarean v any attempt at vaginal delivery at term

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Reviewer Comments ( Add a Comment ) 

Refid: 1, Geremia, C. and Cianfarani, S., Insulin Sensitivity in Children Born Small for Gestational Age (SGA), Rev Diabet Stud, 1(2), 2004, p.58-65

State: Excluded, Level: 2

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ARTICLE Review Form

Does this article POTENTIALLY apply to any of the key questions?

1. NO, this article does not apply to any of our Key Questions 

not written in English

study evaluates outcomes in animals only (no humans evaluated)not evaluating people with gestational diabetes (Note: Exclude if there is not a separate analysis for gestational diabetes AND if less than 90% of 

total sample has gestational diabetes.)

does not include original data (e.g., is a meeting abstract, review, commentary, letter, editorial)case report or case series of less than 50 cases (Note: there is no sample size criteria for studies with a comparison group)diagnosis of GDM NOT confirmed using either a 3-hr 100g OGTT or a 2-hr 75g OGTT for a majority of patients (Note: WHO, NDDG, and 

International Workshop Conference are acceptable diagnostic protocols)

evaluates a maternal or fetal outcome NOT being evaluated in our reportdoes not include a medication of interest for Key Questsion 1no appropriate comparison group for Key Questions 1, 2a or 2b (Note: there cannot be a historical comparison group for KQ1)no relevant risk factor for Key Question 3does not apply to any of the key questionsreview article—may include important information—pull for hand searchingreview article that does not apply to any of the key questions

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cesarean delivery or choice of timing of induction (i.e. gestational age range) of labor 

5. KEY QUESTION 3: What risk factors are associated with short-term and long-term glucose tolerance, and/or 2) type 2 diabetes mellitus following a pregnancy with GDMNote: If the study DOES NOT use an accepted diagnostic method (FBS > 125 mg/dl; 

200 mg/dl; random glucose > 200 mg/dl; self-reported type 2 diabetes mellitus; curren

medication) for type 2 diabetes mellitus it is not eligible for Q3

Applies to KQ3 for type 2 diabetes mellitus

Applies to KQ3 for impaired glucose tolerance

6. KEY QUESTION 4: What are the performance characteristics (sensitivity, specificitfor diagnosing diabetes when conducted in postpartum GDM patients after pregnancyperformance characteristics of the test results based on sub-group analysis? 

Applies to KQ 4

7. Reviewer initials (only enter if sharing a user id). Enlarge Shrink

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2. UNCLEAR 

unclear (can not determine from abstract alone OR no abstract available)--move 

identifying a Key Question

Clear SelectionThis article may apply to one of the following Key Questions (KQ)-3. KEY QUESTION 1: What is the evidence for the risks and benefits of FDA approve(glyburide) to treat GDM and metformin (although not officially approved, it is used in compared to all types of insulin approved by the FDA for use in pregnancy for both thNote: If the study DOES NOT contain an appropriate comparison group (see listing of below) it is not eligible for Q1. Note: FDA approved insulins for use during pregnancy: lispro, aspart, regular, nph, anincludes lispro or aspart

Applies to KQ 1

 Comparisons: i. diet v approved insulin ii. diet v metformin  iii. diet v gliburide  iv. metformin v approved insulin  v. metformin v gliburide  vi. gliburide v insulin  vii. approved insulin v approved insulin  viii. metformin v placebo  ix. gliburide v placebo  x. insulin v placebo 

 Maternal Outcomes: · hypoglycemia,  · glycemic control (fasting blood sugar, 1 hour and 2 hour post prandial glucose),  · cesarean delivery,  · pre-eclampsia, and postpartum hemorrhage  · maternal weight,  · perineal lacerations,  · operative vaginal delivery 

        h a  

4. KEY QUESTION 2: What is the evidence that medically indicated cesarean deliverinduction result in beneficial or harmful neonatal outcomes in GDM (as outlined above 

Applies to KQ 2a: What is the evidence for elective cesarean delivery at term com

delivery (spontaneous or induced) at term? i. cesarean v spontaneous labor and vaginal delivery at term ii. cesarean v induced labor and vaginal delivery at term iii. cesarean v any attempt at vaginal delivery at term

Applies to KQ 2b: What is the evidence for vaginal labor induction at 40 weeks co

an earlier gestational age (<40 weeks) or spontaneous labor in the pregnancy of gesi. labor induction at <40 weeks v labor induction at 40 weeks ii. labor induction at 40 weeks v spontaneous labor iii. labor induction at <40 weeks v spontaneous labor

Applies to KQ 2c: How is the estimated intrauterine fetal weight related to outcom

with medically indicated cesarean delivery or timing (i.e., gestational age range) of la

Applies to KQ 2d: How is gestational age related to outcomes of management of 

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Refid: 1, Geremia, C. and Cianfarani, S., Insulin Sensitivity in Children Born Small for Gestational Age (SGA), Rev Diabet Stud, 1(2), 2004, p.58-65

State: Excluded, Level: 2

Keywords:No keywords available 

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Abstract:In the past decade, several epidemiological studies have shown a relationship between intrauterine growth retardation and insulin resistance, type 2 diabetes and cardiovascular disease in adulthood. Although the biological mechanisms underlying this association are still largely unknown, different explanatory hypotheses have been proposed. It seems likely that the various pathways may interact with each other, all contributing at different degrees to the development of the metabolic disturbances. 

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ABSTRACT Review Form

Does this article POTENTIALLY apply to any of the key questions?

1. NO, this article does not apply to any of our Key Questions 

not written in English

study evaluates outcomes in animals only (no humans evaluated)not evaluating ANY people with gestational diabetes (exclude even if our list of 

maternal and fetal outcomes are evaluated)

does not include original data (e.g., is a meeting abstract, review, commentary, 

letter, editorial)

case report or case series of less than 50 casesdiagnosis of GDM NOT based on either a 3-hr 100g OGTT, or a 2-hr 75g OGTT 

for a majority of patients

evaluates a maternal or fetal outcome NOT being evaluated in our reportdoes not include a medication of interest for Key Questsion 1no appropriate comparison group for Key Questions 1, 2a or 2bdoes not apply to any of the key questionsreview article—may include important information—pull for hand searchingother: specify

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Yes No

11. Were confidence intervals or standard errors reported for point estimates? Clear

12. Were estimates reported for demographic or clinical subgroups? Clear

13. Did the authors provide a description of participants that were loss to follow-up? Clear

14. Was a cross tabulation of the screening test with the reference test included (e.g. are you able to recreate the 

contingency tables from the data provided)? Clear

15. Comments: 

Enlarge Shrink 

Yes No Not 

reported

16. Was the screening test(s) interpreted independently (i.e., evaluated without knowledge) of the 

results of the reference test? Clear

17. Was the reference test interpreted independently (i.e., evaluated without knowledge) of the results 

of the screening test? Clear

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Evidence Table 1. Characteristics of studies reporting on the effects of oral hypoglycemic agents or insulin on maternal and ne

randomized controlled trials 

F-1 

Author, year 

Country 

Study 

design 

Time 

period 

OGTT 

GA at 

diagnosis (in 

weeks) 

OGTT 

results 

(in 

mg/dL) 

Mean 

age (in 

years) 

(Age 

range) Race, n (%) 

Weight (in kg) 

/ BMI (in 

kg/m2), mean

Gravida/ 

parity, mean Treatment, N 

Insulin versus glyburide 

75-gm WHO G1: 22.62 

G1: 2hr: 174.92 

G1: 27.46 

G1: Asian: 13 (100) 

G1: Prepregnancy BMI: 25.32 

G1: NR G1: Insulin, 13 G1

(esMaMe

Anjalakshi, 200633India RCT 

NR 

G2: 22.5 G2: 2hr: 

167.1* 

G2: 24.9 G2: Asian: 10 

(100) 

G2: Prepregnancy BMI: 22.82 

G2: NR G2: 

Glibenclamide, 10 

G2(esMaMe

75-gm WHO and the Brazilian Health Ministry F: 110 mg/dL 2hr: 140 mg/dL G1: NR 

G1: NR G1: 28.7 G1: NR G1: Prepregnancy 

BMI: 27 

G1: Gravida: 2.5 

G1: Insulin, 27 G1

in tsectimeMaMe

G2: NR G2: NR G2: 31.2 G2: NR G2: Prepregnancy 

BMI: 27.5 

G2: Gravida: 3.2 

G2: Glyburide, 24 

G2per MaMe

Bertini, 200537Brazil RCT 

Start year: October 1, 2003 End year: July 1, 2004 Planned study period: 8 months 

G3: NR G3: NR G3: 31.5 G3: NR G3: Prepregnancy 

BMI: 25.7 

G3: Gravida: 2.9 

G3: Acarbose, 19 

G3timeMaMe

3hr 100-gm OGTT†F: 95 mg/dL G1: 25 

G1: F: 98 1hr: 201 2hr: 174 3hr: 134 

G1: 30 G1: NR G1: Prepregnancy BMI 

(n, % with BMI>=27.3): 132 (65) 

G1: (Number of nulliparity: 59) 

G1: Insulin, 203 G1

3 tiMaMe

Langer, 200032 107US RCT 

NR 

G2: 24 G2: F: 97 

1hr: 197 2hr: 174 3hr: 140 

G2: 29 G2: NR G2: Prepregnancy BMI 

(n, % with BMI>=27.3): 141 (70) 

G2: (Number of nulliparity: 56) 

G2: Glyburide, 201 

G2time MaMe
Evidence Table 1. Characteristics of studies reporting on the effects of oral hypoglycemic agents or insulin on maternal and ne

randomized controlled trials (continued) 

F-2 

Author, year 

Country 

Study 

design 

Time 

period 

OGTT 

GA at 

diagnosis (in 

weeks) 

OGTT 

results 

(in 

mg/dL) 

Mean 

age (in 

years) 

(Age 

range) Race, n (%) 

Weight (in kg) 

/ BMI (in 

kg/m2), mean

Gravida/ 

parity, mean Treatment, N 

Insulin versus insulin lispro 

100-gm, Carpenter and Coustan criteria G1: 25.6 

G1: NR G1: 29.8 G1: C: 0 (0) 

Hisp: 23 (100) 

G1: Prepregnancy weight: 78.5 Pre-pregnancy BMI: 33.3 

G1: Gravida: 2.4 Parity: 1.7 

G1: Regular human insulin, 23 

G13 + (esMaMe

Jovanovic, 199936US RCT 

NR 

G2: 27.3 G2: NR G2: 34.2 G2: C: 2 (11) 

Hisp: 17 (89) 

G2: Prepregnancy weight: 76.3 Pre-pregnancy BMI: 31.5 

G2: Gravida: 1.8 Parity: 1.4 

G2: Insulin lispro, 19 

G23 + (esMaMe

100-gm, Carpenter and Coustan criteria G1: median 28 (26-32) 

G1: F: 91 1hr: 197 2hr: 189 3hr: 138 

G1: (28-41) (median 35) 

G1: C: 24 (100) 

G1: Prepregnancy weight: (Median: 60.5) Pre-pregnancy BMI: (Median: 22.3) 

G1: Parity: (median 1 (range 0-1)) 

G1: Regular human insulin, 24 

G1gmmeMaMe

Mecacci, 200334Italy RCT 

Start year: June 1999 End year: Dec 2000 

G2: median 28 (25-32) 

G2: F: 92 1hr: 193 2hr: 170 3hr: 126 

G2: (24-40) (median 34.5) 

G2: C: 25 (100) 

G2: Prepregnancy weight: (Median: 61.4) Pre-pregnancy BMI: (Median: 21.5) 

G2: Parity: (median 1 (range 0-2)) 

G2: Insulin lispro, 25 

G2gmmeMaMe

Insulin versus insulin 

100-gm, O'Sullivan or NDDG G1: 28 

G1: NR G1: 33 G1: NR G1: Prepregnancy 

weight: 72 Pre-pregnancy BMI: 27.8 

G1: Gravida: 3.4 

G1: Insulin twice daily, 136 

G1per MaMe

Nachum, 199935Israel RCT 

Start year: 1993 End year: 1997 Planned study period: 48 months 

G2: 27.4 G2: NR G2: 33 G2: NR G2: Prepregnancy 

weight: 73 Pre-pregnancy BMI: 27.9 

G2: Gravida: 3.5 

G2: Insulin four times daily, 138 

G2per MaMe
Evidence Table 1. Characteristics of studies reporting on the effects of oral hypoglycemic agents or insulin on maternal and ne

randomized controlled trials (continued) 

F-3 

Author, year 

Country 

Study 

design 

Time 

period 

OGTT 

GA at 

diagnosis (in 

weeks) 

OGTT 

results 

(in 

mg/dL) 

Mean 

age (in 

years) 

(Age 

range) Race, n (%) 

Weight (in kg) 

/ BMI (in 

kg/m2), mean

Gravida/ 

parity, mean Treatment, N 

2hr, 75-gm F: 4.8 mmol/L 1hr: 10 mmol/L 2hr: 8.7 mmol/L G1: (24-28) 

G1: NR G1: NR G1: NR G1: NR G1: NR G1: Short-acting 

insulin, 11 

G1timebre(esMaMe

PoyhonenAlho, 200231Finland RCT 

NR 

G2: NR G2: NR G2: NR G2: NR G2: NR G2: NR G2: Long-acting 

insulin, 12 

G2per MaMe

Diet versus insulin 

100-gm, O'Sullivan or NDDG G1: NR 

G1: F: 101 

G1: 26 G1: NR G1: Postpregnancy 

weight: 200 lb 

G1: Gravida: 2.5 Parity: 1.3 

G1: Diet, 50 G1

kilowei

Thompson, 199030US RCT 

Start year: 1985 End year: 1988 G2: NR G2: F: 

101 

G2: 27 G2: NR G2: Postpregnancy 

weight: 192 lb 

G2: Gravida: 3 Parity: 1.4 

G2: Diet and insulin, 45 

G2+ 1day MaMe

* This is the 2 hr PG status after 2 weeks of diet, not the 2hr PG after 75-gm OGTT. † Only used FBG to determine treatment and eligibility for study. 

Asian = Asian or Asian American; BMI = body mass index; C = Caucasian; dL = deciliter; esc = escalated; F = fasting; FBG = fasting blood glucose; age; gm = gram; Hisp = Hispanic; hr = hour; IU = international units; kg = kilogram; L = liter; lb = pound; m = meter; mg = milligram; mmol = millimDiabetes Data Group; NPH = neutral protamine Hagedorn; NR = not reported; OGTT = oral glucose tolerance test; PG = plasma glucose; RCT = rand

regular insulin; US = United States; WHO = World Health Organization 
Evidence Table 1. Characteristics of studies reporting on the effects of oral hypoglycemic agents or insulin on maternal and ne

randomized controlled trials (continued) 

F-2 

Author, year 

Country 

Study 

design 

Time 

period 

OGTT 

GA at 

diagnosis (in 

weeks) 

OGTT 

results 

(in 

mg/dL) 

Mean 

age (in 

years) 

(Age 

range) Race, n (%) 

Weight (in kg) 

/ BMI (in 

kg/m2), mean

Gravida/ 

parity, mean Treatment, N 

Insulin versus insulin lispro 

100-gm, Carpenter and Coustan criteria G1: 25.6 

G1: NR G1: 29.8 G1: C: 0 (0) 

Hisp: 23 (100) 

G1: Prepregnancy weight: 78.5 Pre-pregnancy BMI: 33.3 

G1: Gravida: 2.4 Parity: 1.7 

G1: Regular human insulin, 23 

G13 + (esMaMe

Jovanovic, 199936US RCT 

NR 

G2: 27.3 G2: NR G2: 34.2 G2: C: 2 (11) 

Hisp: 17 (89) 

G2: Prepregnancy weight: 76.3 Pre-pregnancy BMI: 31.5 

G2: Gravida: 1.8 Parity: 1.4 

G2: Insulin lispro, 19 

G23 + (esMaMe

100-gm, Carpenter and Coustan criteria G1: median 28 (26-32) 

G1: F: 91 1hr: 197 2hr: 189 3hr: 138 

G1: (28-41) (median 35) 

G1: C: 24 (100) 

G1: Prepregnancy weight: (Median: 60.5) Pre-pregnancy BMI: (Median: 22.3) 

G1: Parity: (median 1 (range 0-1)) 

G1: Regular human insulin, 24 

G1gmmeMaMe

Mecacci, 200334Italy RCT 

Start year: June 1999 End year: Dec 2000 

G2: median 28 (25-32) 

G2: F: 92 1hr: 193 2hr: 170 3hr: 126 

G2: (24-40) (median 34.5) 

G2: C: 25 (100) 

G2: Prepregnancy weight: (Median: 61.4) Pre-pregnancy BMI: (Median: 21.5) 

G2: Parity: (median 1 (range 0-2)) 

G2: Insulin lispro, 25 

G2gmmeMaMe

Insulin versus insulin 

100-gm, O'Sullivan or NDDG G1: 28 

G1: NR G1: 33 G1: NR G1: Prepregnancy 

weight: 72 Pre-pregnancy BMI: 27.8 

G1: Gravida: 3.4 

G1: Insulin twice daily, 136 

G1per MaMe

Nachum, 199935Israel RCT 

Start year: 1993 End year: 1997 Planned study period: 48 months 

G2: 27.4 G2: NR G2: 33 G2: NR G2: Prepregnancy 

weight: 73 Pre-pregnancy BMI: 27.9 

G2: Gravida: 3.5 

G2: Insulin four times daily, 138 

G2per MaMe
Evidence Table 1. Characteristics of studies reporting on the effects of oral hypoglycemic agents or insulin on maternal and ne

randomized controlled trials (continued) 

F-3 

Author, year 

Country 

Study 

design 

Time 

period 

OGTT 

GA at 

diagnosis (in 

weeks) 

OGTT 

results 

(in 

mg/dL) 

Mean 

age (in 

years) 

(Age 

range) Race, n (%) 

Weight (in kg) 

/ BMI (in 

kg/m2), mean

Gravida/ 

parity, mean Treatment, N 

2hr, 75-gm F: 4.8 mmol/L 1hr: 10 mmol/L 2hr: 8.7 mmol/L G1: (24-28) 

G1: NR G1: NR G1: NR G1: NR G1: NR G1: Short-acting 

insulin, 11 

G1timebre(esMaMe

PoyhonenAlho, 200231Finland RCT 

NR 

G2: NR G2: NR G2: NR G2: NR G2: NR G2: NR G2: Long-acting 

insulin, 12 

G2per MaMe

Diet versus insulin 

100-gm, O'Sullivan or NDDG G1: NR 

G1: F: 101 

G1: 26 G1: NR G1: Postpregnancy 

weight: 200 lb 

G1: Gravida: 2.5 Parity: 1.3 

G1: Diet, 50 G1

kilowei

Thompson, 199030US RCT 

Start year: 1985 End year: 1988 G2: NR G2: F: 

101 

G2: 27 G2: NR G2: Postpregnancy 

weight: 192 lb 

G2: Gravida: 3 Parity: 1.4 

G2: Diet and insulin, 45 

G2+ 1day MaMe

* This is the 2 hr PG status after 2 weeks of diet, not the 2hr PG after 75-gm OGTT. † Only used FBG to determine treatment and eligibility for study. 

Asian = Asian or Asian American; BMI = body mass index; C = Caucasian; dL = deciliter; esc = escalated; F = fasting; FBG = fasting blood glucose; age; gm = gram; Hisp = Hispanic; hr = hour; IU = international units; kg = kilogram; L = liter; lb = pound; m = meter; mg = milligram; mmol = millimDiabetes Data Group; NPH = neutral protamine Hagedorn; NR = not reported; OGTT = oral glucose tolerance test; PG = plasma glucose; RCT = rand

regular insulin; US = United States; WHO = World Health Organization 
Evidence Table 2. Effects of oral hypoglycemic agents or insulin on maternal outcomes: randomized controlled trials 

F-4 

Author, 

year Treatment, N 

Operative 

vaginal 

delivery, n (%) 

Pre-eclampsia, 

n (%) 

Cesarean 

delivery, n (%) Weight, mean 

Glycemic control during 

pregnancy, mean 

H

Insulin versus glyburide 

G1: Insulin, 13 2 hr PG at entry and before 

confinement (mg/dL) Baseline: 174.92 (sd: 31.05) Final: 93 (sd: 9.75) 

Anjalakshi, 200633

G2: Glibenclamide, 10 

2 hr PG at entry and before confinement (mg/dL) Baseline: 167.1 (sd: 22.97) Final: 95.29 (sd: 7.41) 

G1: Insulin, 27 Total cesarean 

deliveries: 12 (44) 

Maternal weight (kg) Mean difference from baseline: 11.5 (sd: 3.8) 

Rhoad

G2: Glyburide, 24 

Total cesarean deliveries: 12 (50) 

Maternal weight (kg) Mean difference from baseline: 10 (sd: 5.2) 

Rhoad

Bertini, 200537

G3: Acarbose, 19 

Total cesarean deliveries: 10 (52) 

Maternal weight (kg) Mean difference from baseline: 10.6 (sd: 3.2) p = 0.46* 

Rhoad
Evidence Table 2. Effects of oral hypoglycemic agents or insulin on maternal outcomes: randomized controlled trials (continue

F-5 

Author, 

year Treatment, N 

Operative 

vaginal 

delivery, n (%) 

Pre-eclampsia, 

n (%) 

Cesarean 

delivery, n (%) Weight, mean 

Glycemic control during 

pregnancy, mean 

H

G1: Insulin, 203 12 (6) Total cesarean 

deliveries: 49 (24) 

FBG (mg/dL) Baseline: 108 (sd: 26) Final: 96† (sd: 16) Pre-prandial glucose (mg/dL) Baseline: 107 (sd: 23) Final: 97† (sd: 14) 2 hr PPG (mg/dL) Baseline: 129 (sd: 27) Final: 112† (sd: 15) Combined glucose (mg/dL) Baseline: 116‡ (sd: 22) Final: 105 (sd: 18) 

F4

Langer, 2000 32

G2: Glyburide, 201 

12 (6) Total cesarean 

deliveries: 46 (23) 

FBG (mg/dL) Baseline: 104 (sd: 25) p = 0.12¶Final: 98† (sd: 13) p = 0.17¶Pre-prandial glucose (mg/dL) Baseline: 104 (sd: 20) p = 0.16¶Final: 95† (sd: 15) p = 0.17¶2 hr PPG (mg/dL) Baseline: 130 (sd: 25) p = 0.69¶Final: 113† (sd: 22) p = 0.6¶Combined glucose (mg/dL) Baseline: 114‡ (sd: 19) p = 0.33¶Final: 105 (sd: 16) p = 0.99¶

F4 p 
Evidence Table 2. Effects of oral hypoglycemic agents or insulin on maternal outcomes: randomized controlled trials (continue

F-6 

Author, 

year Treatment, N 

Operative 

vaginal 

delivery, n (%) 

Pre-eclampsia, 

n (%) 

Cesarean 

delivery, n (%) Weight, mean 

Glycemic control during 

pregnancy, mean 

H

Insulin versus insulin lispro 

G1: Regular human insulin, 23 

Total cesarean deliveries: 6 (27.27) 

HbA1c (%) Baseline: 5.24 (sd: 0.09) Final: 5.16 (sd: 0.12) Mean difference from baseline: 0.07 

Fmhyebd2

Jovanovic, 1999 36

G2: Insulin lispro, 19 

Total cesarean deliveries: 7 (36.84) 

HbA1c (%) Baseline: 5.47 (sd: 0.09) Final: 5.12 (sd: 0.11) Mean difference from baseline: 0.35 

Fmhyebd0

G1: Regular human insulin, 24 

Cesarean delivery for CPD: 2 (8) Total cesarean deliveries: 6 (25)

Pre-prandial glucose (mg/dL) Mean: 74.3§ (sd: 8.6) 1 hour PPG (mg/dL) Mean: 88§ (sd: 11) 2 hour PPG (mg/dL) Mean: 97.9§ (sd: 12.5) 

Mecacci, 2003 34

G2: Insulin lispro, 25 

Cesarean delivery for CPD: 1 (4) p > 0.05║Total cesarean deliveries: 7 (28) p > 0.05║

Pre-prandial glucose (mg/dL) Mean: 73.4§ (sd: 8.1) p > 0.05║1 hour PPG (mg/dL) Mean: 108.4§ (sd: 10.7) p < 0.001║2 hour PPG (mg/dL) Mean: 93.6§ (sd: 11.1) p > 0.05║
Evidence Table 2. Effects of oral hypoglycemic agents or insulin on maternal outcomes: randomized controlled trials (continue

F-7 

Author, 

year Treatment, N 

Operative 

vaginal 

delivery, n (%) 

Pre-eclampsia, 

n (%) 

Cesarean 

delivery, n (%) Weight, mean 

Glycemic control during 

pregnancy, mean 

H

Insulin versus insulin 

G1: Insulin twice daily, 136 

Total cesarean deliveries: 52 (38) 

Maternal weight gain (kg) Mean difference from baseline: 11.4 (sd: 3.5) 

Combined glucose (mmol/L) Final mean: 5.6 (sd: 0.48) HbA1c (%) Final: 5.8 (sd: 1) 

Shyrefrp

Nachum, 1999 35

G2: Insulin four times daily, 138 

Total cesarean deliveries: 54 (39) Risk difference: 0 

Maternal weight gain (kg) Mean difference from baseline: 10.7 (sd: 3.6) 

Combined glucose (mmol/L) Final: 5.42 (sd: 0.54) HbA1c (%) Final: 5.5 (sd: 1) 

Shyrefrp

Diet versus insulin 

G1: Diet, 50 Total cesarean 

deliveries: 8 (23.53) 

FBG (mg/dL) Baseline: 95 (sd: 13) Final: 79.7 (sd: 11) 

Thompson, 1990 30

G2: Diet and insulin, 45 

Total cesarean deliveries: 8 (23.53) 

FBG (mg/dL) Baseline: 96 (sd: 12) Final: 81.3 (sd: 8) 

* Comparing G1 to G2 to G3. † Mean values throughout pregnancy. ‡ Mean glucose 1 week prior to treatment assignment. ¶ Comparing G1 to G2. § Mean from diagnosis of GDM to 38 weeks. ║Comparing G1 to G2 to G3, where G3 is a nondiabetic control group whose data is not shown. 

CPD = cephalopelvic disproportion; dL = deciliter; FBG = fasting blood glucose; fsg = finger stick glucose; G = group; HbA1c = Hemoglobin A1c; hr 

= milligrams; N = no; NR = not reported; PG = plasma glucose; PPG = postprandial glucose; sd = standard deviation; Y = yes 
Evidence Table 3. Grading of the body of evidence of the effects of oral hypoglycemic agents or insulin on maternal or neonata

F-8 

Maternal outcomes 

 Insulin versus glyburide 

Insulin versus insulin 

lispro 

Quantity of evidence:

Number of studies 

7 2 

Total number of patients studied 1310 91 Quality and consistency of evidence:

Were study designs mostly randomized trials (high quality), nonrandomized controlled trials (medium quality), observational studies (low quality), or about a 50:50 mix of experimental and observational (medium quality)? 

Medium High 

Did the studies have serious (-1) or very serious (-2) limitations in quality? (Enter 0 if none) 

-2 -2 

Did the studies have important inconsistency? (-1) -1 -1 Was there some (-1) or major (-2) uncertainty about the directness (i.e. extent to which the people, interventions and outcomes are similar to those of interest)? Reminder: we're looking for head to head comparisons of different diabetes meds to get full credit for directness in addressing our question.

-1 -1 

Were data imprecise or sparse? (-1) (i.e. lack of data or very wide confidence intervals that may change conclusions) 

-1 -1 

Did the studies have high probability of reporting bias? (-1) -1 0 Did the studies show strong evidence of association between intervention and outcome? (“strong” if significant relative risk or odds ratio > 2 based on consistent evidence from 2 or more studies with no plausible confounders (+1); “very strong” if significant relative risk or odds ratio > 5 based on direct evidence with no major threats to validity (+2)) - use your clinical judgment for absolute differences.

0 0 

Did the studies have evidence of a dose-response gradient? (+1) 0 0 Did the studies have unmeasured plausible confounders that most likely reduced the magnitude of the observed association? (+1) 

+1 +1 

Overall grade of evidence (high, moderate, low, very low) Very low Very low 

High = further research is very unlikely to change our confidence in the estimates; moderate = further research is likely to have an important impact on estimate of effect and may change the estimate; low = further research is likely to have an important impact on our confidence in the estimate of effect 

estimate; very low = any estimate of effect is very uncertain. 
Evidence Table 3. Grading of the body of evidence of the effects of oral hypoglycemic agents or insulin on maternal or neonata

(continued) 

F-9 

Neonatal outcomes 

 Insulin versus glyburide 

Insulin versus insulin 

lispro 

Quantity of evidence:

Number of studies 

7 2 

Total number of patients studied 1310 91 Quality and consistency of evidence:

Were study designs mostly randomized trials (high quality), nonrandomized controlled trials (medium quality), observational studies (low quality), or about a 50:50 mix of experimental and observational (medium quality)? 

Medium High 

Did the studies have serious (-1) or very serious (-2) limitations in quality? (Enter 0 if none) 

-2 -2 

Did the studies have important inconsistency? (-1) -1 -1 Was there some (-1) or major (-2) uncertainty about the directness (i.e. extent to which the people, interventions and outcomes are similar to those of interest)? Reminder: we're looking for head to head comparisons of different diabetes meds to get full credit for directness in addressing our question.

-1 -1 

Were data imprecise or sparse? (-1) (i.e. lack of data or very wide confidence intervals that may change conclusions) 

-1 -1 

Did the studies have high probability of reporting bias? (-1) 0/-1 0 Did the studies show strong evidence of association between intervention and outcome? (“strong” if significant relative risk or odds ratio > 2 based on consistent evidence from 2 or more studies with no plausible confounders (+1); “very strong” if significant relative risk or odds ratio > 5 based on direct evidence with no major threats to validity (+2))- use your clinical judgment for absolute differences.

0 0 

Did the studies have evidence of a dose-response gradient? (+1) 0 0 Did the studies have unmeasured plausible confounders that most likely reduced the magnitude of the observed association? (+1) 

+1 +1 

Overall grade of evidence (high, moderate, low, very low) Very low Very low 

High = further research is very unlikely to change our confidence in the estimates; moderate = further research is likely to have an important impact on estimate of effect and may change the estimate; low = further research is likely to have an important impact on our confidence in the estimate of effect 

estimate; very low = any estimate of effect is very uncertain. 
Evidence Table 4. Effects of oral hypoglycemic agents or insulin on neonatal outcomes: randomized controlled trials 

F-10 

Author, 

year Treatment, N 

Hypoglycemia, n 

(%) 

Hyperbilirubinemia, 

n (%) 

Macrosomia, 

n (%) LGA, n (%) SGA, n (%) 

Mortality, n 

(%) 

Other ou

(%

Insulin versus glyburide 

G1: Insulin, 13 

Anjalakshi, 200633

G2: Glibenclamide, 10 

 

G1: Insulin, 27 Capillary 

glucose < 40 mg/dL: 1 (4) 

 Birth weight > 

4000 gm: 0 (0)

Percentile weight > 90: 1 (4) 

Criteria NR: 2 (7) 

Perinatal mortality: 0 (0) 

 

G2: Glyburide, 24 

Capillary glucose < 40 mg/dL: 8 (33) 

 Birth weight > 

4000 gm: 4 (16) 

Percentile weight > 90: 6 (25) 

Criteria NR: 0 (0) 

Perinatal mortality: 0 (0) 

 

Bertini, 200537

G3: Acarbose, 19 

Capillary glucose < 40 mg/dL: 1 (5) p = 0.006* 

 Birth weight > 

4000 gm: 0 (0)

Percentile weight > 90: 2 (10) p = 0.073* 

Criteria NR: 0 (0) 

Perinatal mortality: 0 (0) 

 

G1: Insulin, 203 

Two consecutive blood glucose < 40 mg/dL: 12 (6) 

Serum bilirubin> 12 mg/dL: 8 (4) 

Birth weight > 4000 gm: 9 (4)

Percentile weight > 90: 26 (13) 

 Perinatal 

mortality: 2 (1) 

Congenitmalforma(2) NICU ad14 (7) 

Langer, 2000 32

G2: Glyburide, 201 

Two consecutive blood glucose < 40 mg/dL: 18 (9) p = 0.25†

Serum bilirubin> 12 mg/dL: 12 (6) p = 0.36†

Birth weight > 4000 gm: 14 (7) p = 0.26†

Percentile weight > 90: 24 (12) p = 0.76†

 Perinatal 

mortality: 2 (1) p = 0.99†

Congenitmalforma(2) p = 0.74†NICU ad12 (6) p = 0.68†
Evidence Table 4. Effects of oral hypoglycemic agents or insulin on neonatal outcomes: randomized controlled trials (continue

F-11 

Author, 

year Treatment, N 

Hypoglycemia, n 

(%) 

Hyperbilirubinemia, 

n (%) 

Macrosomia, 

n (%) LGA, n (%) SGA, n (%) 

Mortality, n 

(%) 

Other ou

(%

Insulin versus insulin lispro 

G1: Regular human insulin, 23 

 

Jovanovic, 1999 36

G2: Insulin lispro, 19 

 

G1: Regular human insulin, 24 

 Percentile 

weight >= 90: 3 (12) 

Percentile weight <= 10: 1 (4) 

 

Mecacci, 2003 34

G2: Insulin lispro, 25 

 Percentile 

weight >= 90: 2 (8) p > 0.05‡

Percentile weight <= 10: 1 (4) p > 0.05‡

 
Evidence Table 4. Effects of oral hypoglycemic agents or insulin on neonatal outcomes: randomized controlled trials (continue

F-12 

Author, 

year Treatment, N 

Hypoglycemia, n 

(%) 

Hyperbilirubinemia, 

n (%) 

Macrosomia, 

n (%) LGA, n (%) SGA, n (%) 

Mortality, n 

(%) 

Other ou

(%

Insulin versus insulin 

G1: Insulin twice daily, 136 

Plasma glucose < 1.9 mmol/l in term infants or < 1.4 mmol/l in preterm infants at least on two different occasions during first 48 hours of life: 8 (6) 

Serum bilirubin> 205 mmol/l at >= 34 weeks of gestation or > 137 mmol/l at < 34 weeks of gestation: 29 (21) 

Birth weight > 4000 gm: 26 (19) 

Percentile weight > 90: 41 (30) 

Percentile weight < 10: 7 (5) 

Perinatal mortality: 1 (1) 

Congenitmalformafatal, reqsurgery, significanpsycholoeffects olater life: RDS, hyamembrandisease: birth trauperipherainjury or fracture: 

Nachum, 1999 35

G2: Insulin four times daily, 138 

Plasma glucose < 1.9 mmol/l in term infants or < 1.4 mmol/l in preterm infants at least on two different occasions during first 48 hours of life: 1 (1) 

Serum bilirubin> 205mmol/l at >= 34 weeks of gestation or > 137 mmol/l at < 34 weeks of gestation: 15 (11) 

Birth weight > 4000 gm: 22 (16) 

Percentile weight > 90: 36 (26) 

Percentile weight < 10: 4 (3) 

Perinatal mortality: 0 (0.00) 

Congenitmalformafatal, reqsurgery, significanpsycholoeffects olater life: RDS, hyamembrandisease: birth trauperipherainjury or fracture: 
Evidence Table 4. Effects of oral hypoglycemic agents or insulin on neonatal outcomes: randomized controlled trials (continue

F-13 

Author, 

year Treatment, N 

Hypoglycemia, n 

(%) 

Hyperbilirubinemia, 

n (%) 

Macrosomia, 

n (%) LGA, n (%) SGA, n (%) 

Mortality, n 

(%) 

Other ou

(%

G1: Shortacting insulin, 11 

NR: 0 (0.00) NR: 3 (27.27) (Greater than 

2 sd of the mean birth weight = 3079 ± 722): 0 (0.00) 

 Birth trau

(nerve pa(0.00) 

PoyhonenAlho, 2002 31

G2: Longacting insulin, 12 

NR: 1 (8.33) NR: 3 (25.00) (Greater than 

2 sd of the mean birth weight = 3079 ± 722): 4 (33.33) p: 0.05†

 Birth trau

(nerve pa(8.33) 

Diet versus insulin 

G1: Diet, 50 Plasma 

glucose < 30 mg/dL: 5 (14.71) 

Serum bilirubin> 10 mg/dL: 0 (0.00) 

Birth weight > 4000 gm: 9 (26.47)¶

 

Thompson, 1990 30

G2: Diet and insulin, 45 

Plasma glucose < 30 mg/dL: 6 (17.65) 

Serum bilirubin> 10 mg/dL: 0 (0.00) 

Birth weight > 4000 gm: 2 (5.88)§

 

* Comparing G1 to G2 to G3. † Comparing G1 to G2. ‡ Comparing G1 to G2 to G3, where G3 is a nondiabetic control group, whose data is not shown. ¶ Macrosomia in mothers with delivery weight<200lb (N=22 in both groups): 0. Macrosomia in mothers with delivery weight>=200lb (N=12 in both g§ Macrosomia in mothers with delivery weight<200lb (N=22 in both groups): 0. Macrosomia in mothers with delivery weight>=200lb (N=12 in both g

dL = deciliter; G = group; gm = gram; kg = kilogram; l = liter; LGA = large for gestational age; mg = milligram; mmol = millimole; NICU = neonatal reported; RDS = respiratory distress syndrome; SGA = small for gestational age; sd = standard deviation 
Evidence Table 5. Quality of the studies reporting on the effects of oral hypoglycemic agents or insulin on maternal and neona

randomized controlled trials 

F-14 

Author, year Randomized 

Randomization 

scheme described Double blinded 

Blinding 

described 

Withdrawa

describe

Anjalakshi, 200633 ● Bertini, 200537 ● ● ● Langer, 200032 ● ● Jovanovic, 199936 ● ● ● Mecacci, 200334 ● ● Nachum, 199935 ● ● Poyhonen-Alho, 200231 ● Thompson, 199030 ● ● ● 

● = Yes; blank space = No/Not reported *Total quality score calculated using the Jadad22 criteria.
Evidence Table 6. Characteristics of studies reporting on the effects of oral hypoglycemic agents or insulin on maternal and ne

randomized controlled trials and observational studies 

F-15 

Author, year 

Country 

Study 

design 

Time 

period 

OGTT 

GA at 

diagnosis (in 

weeks) 

OGTT 

results 

(in 

mg/dL) 

Mean 

age (in 

years) 

(Age 

range) Race, n (%) 

Weight (in kg) 

/ BMI (in 

kg/m2), mean

Gravida/ 

parity, mean Treatment, N 

100-gm O'Sullivan or NDDG G1: 26.3 

G1: F: 105 1hr: 223 2hr: 197 3hr: 140 

G1: 32.1 G1: AA: 10 (4) 

C: 116 (43) Asian: 64 (24) Hisp: 66 (25) 

G1: 1st

documented BMI during pregnancy: 31.9 

G1: (number of nulliparous women: 91 (34%)) 

G1: Insulin in 1999-2000, 268 

G1MaMe

G2: 25.5 G2: 

F: 102 1hr: 220 2hr: 195 3hr: 137 

G2: 32.8 G2: AA: 9 (4) 

C: 65 (28) Asian: 88 (37) Hisp: 56 (24) 

G2: 1st

documented BMI during pregnancy: 30.6 

G2: (number of nulliparous women: 78 (33%)) 

G2: Glyburide in 2001-2002, 236 

G2time MaMe

Jacobson, 200548

US Cohort 

Start year: 1999 End year: 2002 

G3: stated similar to G2 

G3: F: 109 1hr: NR 2hr: NR 3hr: NR 

G3: stated similar to G2 

G3: AA: stated similar to G2 C: stated similar to G2 Asian: NR (24) Hisp: stated similar to G2 

G3: 1stdocumented BMI during pregnancy: 33.9 

G3: (number of nulliparous women: stated similar to G2) 

G3: Insulin in 2001-2002, 80 

G3MaMe

100-gm OGTT using 2003 ADA criteria F: 95 mg/dL 1hr: 180 mg/dL 2hr: 155 mg/dL 3hr: 140 mg/dL G1: 20; 23.3 (at time of initiation of glyburide) 

G1: F: 115 1hr: 230 2hr: 204 3hr: 176 

G1: 30.3 G1: NR G1: Prepregnancy 

BMI: NR (stated similar between groups) 

G1: Parity: 2.2 G1: Glyburide 

failure, 12 

G1glybwas Mainsuwas Me

Conway, 200447

US Cohort 

Start year: Dec 2000 End year: July 2003 

G2: 18.4; 28.7 (at initiation of glyburidep < 0.05) 

G2: F: 102 1hr: 205 2hr: 169 3hr: 133 

G2: 31.3 G2: NR G2: Prepregnancy 

BMI: NR (stated similar between groups) 

G2: Parity: 1.8 G2: Glyburide 

success, 63 

G2time MaMe
Evidence Table 6. Characteristics of studies reporting on the effects of oral hypoglycemic agents or insulin on maternal and ne

randomized controlled trials and observational studies (continued) 

F-16 

Author, year 

Country 

Study 

design 

Time 

period 

OGTT 

GA at 

diagnosis (in 

weeks) 

OGTT 

results 

(in 

mg/dL) 

Mean 

age (in 

years) 

(Age 

range) Race, n (%) 

Weight (in kg) 

/ BMI (in 

kg/m2), mean

Gravida/ 

parity, mean Treatment, N 

100-gm Carpenter and Coustan criteria G1: 20 

G1: F: 105 1hr: 206 2hr: 192 3hr: 128 

G1: 31 G1: Hisp: 9 

(69) non-Hispanic: 4 (31) 

G1: NR G1: 

(Nulliparity: 1 (7.7%)) 

G1: glyburide failure (glyburide + diet + insulin OR insulin + diet), 13 

G1stainsuwee

per Mainsu(10 Me

Chmait, 200445

US Cohort 

Start year: 2000 End year: 2002 

G2: 27.3 G2: 

F: 94 1hr: 199 2hr: 169 3hr: 126 

G2: 32 G2: Hisp: 51 

(91) non-Hispanic: 5 (9) 

G2: NR G2: 

(Nulliparity: 8 (14.3%)) 

G2: glyburide success (glyburide + diet), 56 

G21 tiMamg Me

100-gm Carpenter and Coustan criteria G1: NR 

G1: F: 96 

G1: 26.4 G1: NR G1: Prepregnancy 

BMI: 26 

G1: (Nulliparity: 9 (33%)) 

G1: Diet, 27 G1

G2: NR G2: 

F: 99 

G2: 28.1 G2: NR G2: Prepregnancy 

BMI: 27.6 

G2: (Nulliparity: 8 (27%)) 

G2: Insulin, 30 G2

3 tiMe

Yogev, 200446

US Non-RCT 

Start year: 2001 End year: 2003 Planned study period: 2 years 

G3: NR G3: 

F: 98 

G3: 28.3 G3: NR G3: Prepregnancy 

BMI: 27.5 

G3: (Nulliparity: 7 (28%)) 

G3: Glyburide, 25 

G3time MaMe
Evidence Table 6. Characteristics of studies reporting on the effects of oral hypoglycemic agents or insulin on maternal and ne

randomized controlled trials and observational studies (continued) 

F-17 

Author, year 

Country 

Study 

design 

Time 

period 

OGTT 

GA at 

diagnosis (in 

weeks) 

OGTT 

results 

(in 

mg/dL) 

Mean 

age (in 

years) 

(Age 

range) Race, n (%) 

Weight (in kg) 

/ BMI (in 

kg/m2), mean

Gravida/ 

parity, mean Treatment, N 

100-gm Carpenter and Coustan criteria G1: 24 

G1: F: 107 1hr: 223 2hr: 189 3hr: 114 

G1: 31.3 G1: 

AA: 6 (29) C: 1 (5) Asian: 2 (10) Hisp: 12 (57) 

G1: BMI at 1st

prenatal visit: 32.2 

G1: (Multiparous: 18 (86%)) 

G1: Glyburide failure (NPH and regular insulin), 21 

G1stastarep(esMe

Rochon, 200649US Cohort 

Start year: 2002 End year: 2005 Planned study period: 30 months 

G2: 26 G2: 

F: 102 1hr: 200 2hr: 179 3hr: 138 

G2: 30.5 G2: 

AA: 24 (30) C: 1 (1) Asian: 8 (10) Hisp: 47 (59) 

G2: BMI at 1st

prenatal visit: 31.5 

G2: (Multiparous: 56 (70%) 

G2: Glyburide success (glyburide + diet), 80 

G2time Mamg Me

*Only available for 249 women †Only available for 229 women ‡ Insulin dose for 1 to 18 weeks gestation was 0.7 units/kg; for 18 to 26 weeks gestation was 0.8 units/kg; for 26 to 36 weeks gestation used 0.9 units/k

gestation was 1.0 units/kg. AA = African American; ADA = American Diabetes Association; Asian = Asian or Asian American; bid = twice daily; BMI = body mass index; C = = escalated; F = fasting; G = group; GA = gestational age; gm = gram; Hisp. = Hispanic; hr = hour; kg = kilogram; mg = milligram; NA = not applicabDiabetes Data Group; NR = not reported; OGTT = oral glucose tolerance test; RCT = randomized controlled trial; US = United States 
Evidence Table 7. Effects of oral hypoglycemic agents or insulin on maternal outcomes: non-randomized controlled trials and 

F-18 

Author, year Treatment, N 

Operative 

vaginal 

delivery, n (%) 

Pre-eclampsia, 

n (%) 

Cesarean 

delivery, n (%) Weight, mean

Glycemic control during 

pregnancy, mean 

G1: Insulin in 1999-2000, 268 

15 (6) 16 (6) 

OR: ref 

Total cesarean deliveries: 94 (36) 

 FBG (mg/dL) 

Baseline: 105.4 (sd: 12.9) Final: 97.7 (sd: 12.2) 1 hour PPG (mg/dL) Baseline: 222.8 (sd: 28.9) Final: 137.8 (sd: 23.6) 2 hour PPG (mg/dL) Baseline: 197.4 (sd: 33.6) Final: 118.8 (sd: 19.6) 

Jacobson, 200548

G2: Glyburide in 2001-2002, 236 

12 (5) 28 (12) 

OR: 2.32 (95% CI: 1.17-4.63) 

Total cesarean deliveries: 91 (39) 

 FBG (mg/dL) 

Baseline: 102.4 (sd: 14.2) p = 0.005* Final: 90.2 (sd: 12.7) p < 0.001* 1 hour PPG (mg/dL) Baseline: 220 (sd: 27.2) p = 0.48* Final: 131.4 (sd: 23.3) p < 0.001* 2 hour PPG (mg/dL) Baseline: 194.7 (sd: 32.1) p = 0.44* Final: 117.6 (sd: 23.2) p < 0.05* 

G1: glyburide failure (glyburide + diet + insulin OR insulin + diet), 13 

 Elective cesarean 

delivery: 1 (7.69) total cesarean deliveries: 5 (38) 

 Fasting glucose† (mg/dL) 

Mean: 114 (sd: 17) 1 hour PPG† (mg/dL) 

Mean: 145 (sd: 20) 

Chmait, 200445

G2: glyburide success (glyburide + diet), 56 

 Elective cesarean 

delivery: 4 (7.14) total cesarean deliveries: 19 (34) p > 0.05* 

 Fasting glucose† (mg/dL) 

Mean: 88 (sd: 11) p < 0.001* 1 hour PPG† (mg/dL) 

Mean: 124 (sd: 12) p < 0.001* 
Evidence Table 7. Effects of oral hypoglycemic agents or insulin on maternal outcomes: non-randomized controlled trials and 

(continued) 

F-19 

Author, year Treatment, N 

Operative 

vaginal 

delivery, n (%) 

Pre-eclampsia, 

n (%) 

Cesarean 

delivery, n (%) Weight, mean

Glycemic control during 

pregnancy, mean 

G1: Diet, 27 FBG (mg/dL) 

Baseline: 96 (sd: 21) Final: 99 (sd: 13) 

G2: Insulin, 30 FBG (mg/dL) 

Baseline: 99 (sd: 23) Final: 104 (sd: 15) 

Yogev, 200446

G3: Glyburide, 25 

 FBG (mg/dL) 

Baseline: 98 (sd: 27) p = 0.17¶Final: 105 (sd: 14) p = 0.24¶
Evidence Table 7. Effects of oral hypoglycemic agents or insulin on maternal outcomes: non-randomized controlled trials and 

(continued) 

F-20 

Author, year Treatment, N 

Operative 

vaginal 

delivery, n (%) 

Pre-eclampsia, 

n (%) 

Cesarean 

delivery, n (%) Weight, mean

Glycemic control during 

pregnancy, mean 

G1: Glyburide failure (NPH and regular insulin), 21 

Rochon, 9 (43) 200649

G2: Glyburide success (glyburide + diet), 80 

 30 (38) 

* Comparing G1 to G2 † During treatment with glyburide ‡ Comparing G1 to G2 to G3 ¶ Comparing G2 to G3 CGMS = continuous glucose monitoring system; CI = confidence interval; dL = deciliter; FBG = fasting blood glucose; fsg = finger stick glucose; G = 

NPH = Neutral Protamine Hagedorn; OR = odds ratio; PPG = postprandial glucose; ref = reference group; sd = standard deviation 
Evidence Table 8. Effects of oral hypoglycemic agents or insulin on neonatal outcomes: non-randomized controlled trials and 

F-21 

Author, 

year Treatment, N 

Hypoglycemia, n 

(%) 

Hyperbilirubinemia, 

n (%) 

Macrosomia, 

n (%) LGA, n (%) SGA, n (%) 

Mortality, n 

(%) 

Other ou

(%

G1: Insulin in 1999-2000, 268 

ICD-9-CM codes: 73 (27) OR: ref 

Serum bilirubin > 12 mg/dL within first 7 days of birth: 58 (22) OR: ref 

Birth weight > 4000 gm: 64 (24) OR: ref 

Percentile weight > 90: 63 (24) OR: ref 

Percentile weight < 10: 18 (7) OR: ref 

 NICU ad

65 (24) OR: ref birth trauclaims dacodes, toinjuries: 3 congenitmalformaclaims dacodes: 4 

Jacobson, 200548

G2: Glyburide in 2001-2002, 236 

ICD-9-CM codes: 72 (31) OR: 1.27 (95% CI: 0.84-1.94) 

Serum bilirubin> 12 mg/dL within first 7 days of birth: 59 (25) OR: 1.18 (95% CI: 0.75-1.85) 

Birth weight > 4000 gm: 60 (25) OR: 1.28 (95% CI: 0.82-2) 

Percentile weight > 90: 60 (25) OR: 1.44 (95% CI: 0.91-2.27) 

Percentile weight < 10: 12 (6) OR: 0.62 (95% CI: 0.26-1.43) 

 NICU ad

35 (15) OR: 0.57 0.34-0.93birth trauclaims dacodes toinjuries: 8 congenitmalformaclaims dacodes: 4 

G1: glyburide failure, 12 

 Birth weight > 

4000 gm: 1 (8)

 

Conway, 200447

G2: glyburide success, 63 

 Birth weight > 

4000 gm: 7 (11) p = 1.0* 

 
Evidence Table 8. Effects of oral hypoglycemic agents or insulin on neonatal outcomes: non-randomized controlled trials and 

(continued) 

F-22 

Author, 

year Treatment, N 

Hypoglycemia, n 

(%) 

Hyperbilirubinemia, 

n (%) 

Macrosomia, 

n (%) LGA, n (%) SGA, n (%) 

Mortality, n 

(%) 

Other ou

(%

G1: glyburide failure (glyburide + diet + insulin OR insulin + diet), 13 

Fsg < 40 mg/dL: 0 (0.00) 

Serum bilirubin> 15 mg/dL: 1 (8.33) 

Birth weight > 4000 gm: 2 (10) 

 Fetal mortality: 

0 (0) 

NICU ad(8) 

Chmait, 200445

G2: glyburide success (glyburide + diet), 56 

Fsg < 40 mg/dL: 1 (1.85) 

Serum bilirubin> 15 mg/dL: 2 (3.70) 

Birth weight > 4000 gm: 15 (18) p > 0.05* 

 Fetal mortality: 

1 (2) p > 0.05* 

NICU ad(7) p > 0.05* 

G1: Glyburide failure (NPH and regular insulin), 21 

Any heel stick < 40 mg/dL: 2 

(10) 

Requiring NICU admission: 0 (0) 

Birth weight > 4000 gm: 2 (11) 

 NICU ad

(10) OR: ref shoulder 2 (11) 

Rochon, 200649

G2: Glyburide success (glyburide + diet), 80 

Any heel stick < 40 mg/dL: 10 

(13) 

Requiring NICU admission: 2 (3) 

Birth weight > 4000 gm: 13 (16) p = 0.445* 

 NICU ad

26 (33) p = 0.037 OR: 4.57 3.04-6.10shoulder 7 (10) p = 0.932 

* Comparing G1 to G2 CI = confidence interval; dL = deciliter; fsg = fingerstick glucose; G = group; gm = gram; ICD-9-CM = International Classification of Diseases – 9th r

Modification; LGA = large for gestational age; mg = milligrams; NICU = neonatal intensive care unit; OR = odds ratio; ref = reference group; sd = stasmall for gestational age 
Evidence Table 9. Quality of studies reporting on the effects of oral hypoglycemic agents or insulin on maternal and neonatal 

randomized controlled trials and observational studies 

F-23 

Author, year 

Are prespecified 

hypotheses 

stated? 

Are inclusion 

and exclusion 

criteria 

reported? Sampling 

Were power 

or sample size 

calculations 

used? 

Does the 

article state 

how the 

outcome was 

defined? 

Loss to 

followup / 

Loss to 

followup 

described 

Missi

des

how 

data 

Jacobson, 200548

● Consecutive ●

Yogev, 200446 ● Consecutive ● <10% / NA <10Chmait, 200445 ● ● Consecutive ● <10% / ● <10Conway, 200447

● ● Consecutive ● <10% / 

Rochon, 200649

● Consecutive ● <10% / 

● = Yes; blank space = No/Not reported NA = not applicable
Evidence Table 10. Characteristics of studies reporting on the effects of labor management on maternal and neonatal outcome

F-24 

Author, year 

Country 

Study design Time period 

OGTT 

GA at diagnosis (in 

weeks) 

Mean age (in 

years), (Age 

range) Race, n (%) 

Gravida and 

parity, mean Interv

100-gm O'Sullivan or NDDG C: 38 weeks, 2 days 

C: 31.9 (30.8-33.0) 

C: NR C: Gravidity: 4.1 

Parity: 2.4 

C: Induced if 

weeks, 100 

Kjos, 199355

US RCT 

Start year: 1987 End year: 1991 

I: 38 weeks, 1 day I: 32.1 (30.9-33.2) I: NR I: Gravidity: 4.3 

Parity: 2.5 

I: Induced at 

100-gm O'Sullivan or NDDG HC: NR 

HC: NR HC: Hisp: (84.7) 

Cauc: (12.1) AA: (3.2) 

Conway, 1998 HC: NR HC: Expecta

53

US Cohort 

Start year: 1990 End year: 1995 

E: NR E: NR E: Hisp: (86.4) 

Cauc: (9.9) AA: (3.7) 

E: NR E: Ultrasoun

EFW > 4250 EFW < 4250 

100-gm O'Sullivan or NDDG HC: NR 

HC: 33.1 HC: NR HC: Parity: 2.5 HC: Induced 

CD if EFW > 

Lurie, 199658

Israel Cohort 

Start year: 1983 End year: 1994 

E: NR E: 32.5 E: NR E: Parity: 1.9 E: Induced a

4500 gm, 96 

Lurie, 199257

Israel Cohort 

Start year: 1983 End year: 1988 

100-gm O'Sullivan or NDDG NR for any group 

NR for any group NR for any group NR for any group GDMA1: 

> 40 weeks: gm, CD if EF< 40 weeks: gm, CD if EFGDMA2: > 40 weeks: gm, CD if EF< 40 weeks: gm, CD if EF
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Evidence Table 10. Characteristics of studies reporting on the effects of labor management on maternal and neonatal outcome

F-25 

Author, year 

Country 

Study design Time period 

OGTT 

GA at diagnosis (in 

weeks) 

Mean age (in 

years), (Age 

range) Race, n (%) 

Gravida and 

parity, mean Interv

Peled, 200459

Israel Cohort 

Start year: 1980 End year: 1999 

100-gm Carpenter and Coustan criteria 100-gm O'Sullivan or NDDG 75-gm ADA NR for any group 

NR for any group NR for any group NR for any group Period A: Ind

EFW > 4500 Period B: IndCD if EFW > Period C: IndCD if EFW > Period D: IndCD if EFW > 

100-gm, 3-hr OGTT, ACOG C: NR 

C: 30 C: AA: (1) 

Cauc: (15) Hisp: (60) Am. Ind: (20) Other: (4) 

C: (0, %: 31; 1, %: 20; >=2, %: 49) 

C: GDMA1, 137 

Rayburn, 200556

US Cohort 

Start year: 2000 End year: 2004 Planned study period: 49 months 

E: NR E: 30 E: AA: (0) 

Cauc: (17) Hisp: (70) Am. Ind: (6) Other: (7) 

E: (0, %: 18; 1, %: 33; >=2, %: 49) 

E: GDMA2, 

100-gm O'Sullivan or NDDG C: 38.3 

C: 31.1 C: AA: (25) 

Cauc: (57) Asian: (3) Hisp: (11) Other: (4) 

Marchiano, 2004 C: Gravida: 3.4 C: Trial of la

52

US Cohort 

Start year: 1995 End year: 1999 

E: 38 E: 32.2 E: AA: (20) 

C: (64) Asian: (3) Hisp: (9) Other : (5) 

E: Gravida: 3.1 E: Repeat el

Keller, 199154US Cohort 

Start year: 1983 End year: 1989 Planned study period: 70 months 

100-gm O'Sullivan or NDDG 

NR for any group NR for any group NR for any group C: Trial of la

AA = African American; ACOG = American College of Obstetrics and Gynecologists; ADA = American Diabetes Association; Asian = Asian or Asiagroup; Cauc = Caucasian; CD = cesarean delivery; E = exposure group; EFW = estimated fetal weight; GA = gestational age; GDMA1 = diet-controllmedical therapy; gm = gram; HC = historical control group; Hisp = Hispanic; I = intervention group; LGA = large for gestational age; NDDG = Natio

= not reported; OGTT = oral glucose tolerance test; RCT = randomized controlled trial; US = United States 
Evidence Table 11. Effects of labor management on maternal outcomes 

F-26 

Author, year 

Level of 

analysis Intervention/Exposure, N 

GA at delivery 

(in weeks), 

mean (SD) GA determined by

Operative va

delivery, n 

C: Induced if EFW > 4200 gm or 42 weeks, 

100 

40 LMP; 1st trimester 

ultrasound 

Kjos, 1993 

55 Intervention 

I: Induced at 38 weeks, 100 39 LMP; 1st trimester 

ultrasound; amniocentesis if indicated 

 

Conway, 1998 HC: Expectant management, 1227 39.3 (1.5) NR 

53 Protocol-based 

E: Ultrasound at 37-38 weeks; CD if EFW > 4250 gm, induced if LGA and EFW < 4250 gm, 1337 

39.2 (1.6) NR 

HC: Induced if EFW > 4000 gm CD if EFW > 4500 gm, 164 

39.2 LMP; 1st trimester 

ultrasound 

Lurie, 1996 Vacuum: 9 (6) 

58 Protocol-based 

E: Induced at 38 weeks, CD if EFW > 4500 gm, 96 

38.4 LMP 1st trimester 

ultrasound; amniocentesis to confirm fetal lung maturity 

Vacuum: 5 (5) p: NS 

GDMA1: > 40 weeks: Induced if EFW > 4000 gm, CD if EFW > 4500 gm, 65 

40.9 LMP; 1st trimester 

ultrasound 

Vacuum: 4 (6) 

< 40 weeks: Induced if EFW > 4000 gm, CD if EFW > 4500 gm, 65 

38.2 LMP; 1st trimester 

ultrasound 

Vacuum: 0 (0) p = 0.0997†

> 40 weeks: Induced if EFW > 4000 gm, CD if EFW > 4500 gm, 59 

40.5 LMP; 1st trimester 

ultrasound 

Vacuum: 4 (7) 

Lurie, 199257 Protocol-based 

GDMA2: < 40 weeks: Induced if EFW > 4000 gm, CD if EFW > 4500 gm, 59 

37.5 LMP; 1st trimester 

ultrasound 

Vacuum: 1 (2) p = 0.6216†
Evidence Table 11. Effects of labor management on maternal outcomes (continued) 

F-27 

Author, year 

Level of 

analysis Intervention/Exposure, N 

GA at delivery 

(in weeks), 

mean (SD) GA determined by

Operative va

delivery, n 

Period A: Induced at 42 weeks, CD if EFW > 4500 gm, 878 

39 (2.5) LMP; +/- 1st 

trimester ultrasound

 

Period B: Induced at 40 weeks if LGA, CD if EFW > 4000 gm, 347 

39 (1.5) LMP; +/- 1st 

trimester ultrasound 

 

Period C: Induced at 40 weeks if LGA, CD if EFW > 4000 gm, 317 

38 (1.6) LMP; +/- 1st 

trimester ultrasound

 

Peled, 200459 Protocol-based 

Period D: Induced at 38 weeks if LGA, CD if EFW > 4000 gm, 518 

38.1 (3.1) LMP; +/- 1st 

trimester ultrasound

 

Additional studies 

C: GDMA1, Expectant management, 137 39 (1) 1st trimester 

ultrasound; amniocentesis if needed 

Rayburn, 2005 

56 Exposure 

E: GDMA2, Induced at 38 weeks, 143 38.1 (0.3) 1st trimester 

ultrasound; amniocentesis if needed 

 

C: Trial of labor after CD, 423 38.3 (2.2) NR 

Marchiano, 200452 exposure 

E: Repeat elective cesarean, 440 NR NR 

Keller, 199154 exposure C: Trial of labor, 173 NR NR Forceps: 8 

* The birth weight was greater than or equal to 4000 gm for 32 (25%) and less than 4000 gm for 96 (75%) of the infants of the 128 women who failed † Comparing > 40 weeks to < 40 weeks for all modes of delivery 

C = control group; CD = cesarean delivery; E = exposure group; EFW = estimated fetal weight; GDMA1 = diet-controlled; GDMA2 = requiring medi

= historical control group; I = intervention group; LGA = large for gestational age; LMP = last menstrual period; NR = not reported; NS = not signific

VBAC = vaginal birth after cesarean 
Evidence Table 12. Effects of labor management on neonatal outcomes 

F-28 

Author, 

year 

Level of 

analysis 

Intervention/Exposure, 

N 

GA at 

delivery 

(in 

weeks), 

mean 

(SD) 

GA determined by 

Macrosomia 

or LGA 

(PW>90%), n 

(%) 

Birth weight 

(in grams), 

mean 

Shoulder dystocia, 

n (%) 

Birth 

trauma, n 

(%) 

Morta

(

C: Induced if EFW >

4200 gm or 42 weeks, 100 

40 LMP; 1st 

trimester ultrasound 

Birth weight > 4000 gm: 27 (27) > 4500 gm: 2 (2) LGA: 23 (23) 

3672 (95% CI: 3595 – 3749) 

3 (3.00) Bone 

fracture, nerve palsy: 0 (0) 

Perinaneonatmortali

Kjos, 199355

Intervention 

I: Induced at 38 weeks, 100 

39 LMP; 1st 

trimester ultrasound; amniocentesis if indicated 

Birth weight > 4000 gm: 15 (15) p = 0.05* > 4500 gm: 0 (0) LGA: 10 (10) p = 0.02* 

3446 (95% CI: 3368 – 3522) p < 0.0001* 

0 (0) Bone 

fracture, nerve palsy: 0 (0) 

Perinaneonatmortali

HC: Expectant management, 1227 

39.3 (1.5) 

NR Birth weight > 

4000 gm: 147 (12) LGA: 233 (19) 

 (2.8) 

OR: 1.9 (95% CI: 1 - 3.5) 

Bone fracture, nerve palsy: 12 (41) 

Conway, 1998 53

Protocolbased 

E: Ultrasound at 37-38 weeks; CD if EFW > 4250 gm, induced if LGA and EFW < 4250 gm, 1337 

39.2 (1.6) 

NR Birth weight > 

4000 gm: 120 (9) p = 0.04†

LGA: 227 (17) p: NS†

 (1.5) Bone 

fracture, nerve palsy: 7 (47) 
Evidence Table 12. Effects of labor management on neonatal outcomes (continued) 

F-29 

Author, 

year 

Level of 

analysis 

Intervention/Exposure, 

N 

GA at 

delivery 

(in 

weeks), 

mean 

(SD) 

GA determined by 

Macrosomia 

or LGA 

(PW>90%), n 

(%) 

Birth weight 

(in grams), 

mean 

Shoulder dystocia, 

n (%) 

Birth 

trauma, n 

(%) 

Morta

(

HC: Induced if EFW > 4000 gm; CD if EFW > 4500 gm, 164 

39.2 LMP; 1st 

trimester ultrasound 

Birth weight > 4000 gm: 30 (18) 

3430.1 (530.0) 

7 (5) Clavicle 

fracture, nerve palsy: 3 (1.83) 

Perinaneonatmortali(0.00) 

Lurie, 1996 58

Protocolbased 

E: Induced at 38 weeks, CD if EFW > 4500 gm, 96 

38.4 LMP; 1st 

trimester ultrasound; amniocentesis for lung maturity 

Birth weight > 4000 gm: 9 (9)p: NS†

3406.7 (493.4) 

1 (1) p: NS†

Clavicle fracture, nerve palsy: 0 (0.00) 

Perinaneonatmortali(1.04) 
Evidence Table 12. Effects of labor management on neonatal outcomes (continued) 

F-30 

Author, 

year 

Level of 

analysis 

Intervention/Exposure, 

N 

GA at 

delivery 

(in 

weeks), 

mean 

(SD) 

GA determined by 

Macrosomia 

or LGA 

(PW>90%), n 

(%) 

Birth weight 

(in grams), 

mean 

Shoulder dystocia, 

n (%) 

Birth 

trauma, n 

(%) 

Morta

(

GDMA1: > 40 weeks: Induced if EFW > 4000 gm, CD if EFW > 4500 gm, 65 

40.9 LMP; 1st 

trimester ultrasound 

Birth weight > 4000 gm: 16 (25) 

3617.85 (sd: 485.12) 

2 (3.57) Clavicle 

fracture, nerve palsy: 0 (0) 

Perinaneonatmortali

< 40 weeks: Induced if EFW > 4000 gm, CD if EFW > 4500 gm, 65 

38.2 LMP; 1st 

trimester ultrasound 

Birth weight > 4000 gm: 10 (15) p = 0.1853‡

3439.00 (sd: 584.21) p = 0.0619‡

0 (0.00) p = 0.5328‡

Clavicle fracture, nerve palsy: 0 (0) 

Perinaneonatmortali

GDMA2: > 40 weeks: Induced if EFW > 4000 gm, CD if EFW > 4500 gm, 59 

40.5 LMP; 1st 

trimester ultrasound 

Birth weight > 4000 gm: 12 (20) 

3639.15 (sd: 491.84) 

1 (2.17), Clavicle 

fracture, nerve palsy: 2 (4.35) 

Perinaneonatmortali

Lurie, 1992 57

Protocolbased; divided into groups based on gestational age at delivery 

< 40 weeks: Induced if EFW > 4000 gm, CD if EFW > 4500 gm, 59 

37.5 LMP; 1st 

trimester ultrasound 

Birth weight > 4000 gm: 4 (7)p = 0.0567‡

3275.34 (sd: 570.15) p = 0.0003‡

2 (4.55) p = 0.9676‡

Clavicle fracture, nerve palsy: 1 (2.27) 

Perinaneonatmortali
Evidence Table 12. Effects of labor management on neonatal outcomes (continued) 

F-31 

Author, 

year 

Level of 

analysis 

Intervention/Exposure, 

N 

GA at 

delivery 

(in 

weeks), 

mean 

(SD) 

GA determined by 

Macrosomia 

or LGA 

(PW>90%), n 

(%) 

Birth weight 

(in grams), 

mean 

Shoulder dystocia, 

n (%) 

Birth 

trauma, n 

(%) 

Morta

(

Period A: Induced at 42 weeks, CD if EFW > 4500 gm, 878 

39 (2.5) LMP; +/- 

1st trimester ultrasound 

Birth weight > 4000 gm: 167 (19) 

 18 (2) Perina

neonatmortali(8) 

Period B: Induced at 40 weeks if LGA, CD if EFW > 4000 gm, 347 

39 (1.5) LMP; +/- 

1st trimester ultrasound 

Birth weight > 4000 gm: 56 (16) 

 3 (1) Perina

neonatmortali(3) 

Period C: Induced at 40 weeks if LGA, CD if EFW > 4000 gm, 317 

38 (1.6) LMP; +/- 

1st trimester ultrasound 

Birth weight > 4000 gm: 38 (12) 

 3 (1) Perina

neonatmortali

Peled, 2004 59 protocol period 

Period D: Induced at 38 weeks if LGA, CD if EFW > 4000 gm, 518 

38.1 (3.1) 

LMP; +/- 1st trimester ultrasound 

Birth weight > 4000 gm: 21 (4) 

 0 (0) Perina

neonatmortali

Additional studies 

C: GDMA1, Expectant management, 137 

39 (1) 1st 

trimester ultrasound amniocentesis if needed 

Birth weight > 4000 gm: 11 (8) 

3311 (sd: 489) 

3 (2) clavicle 

fracture, nerve palsy: 0 (0.00) 

Fetal m1 (1) 

Rayburn, 2005 56 exposure 

E: GDMA2, Induced at 38 weeks, 143 

38.1 (0.3) 

1st trimester ultrasound amniocentesis if needed 

Birth weight > 4000 gm: 6 (4)p = 0.18¶

3306 (sd: 396) p = 0.93¶

6 (4) p = 0.77¶

clavicle fracture, nerve palsy: 0 (0.00) 

Fetal m0 (0) 
Evidence Table 12. Effects of labor management on neonatal outcomes (continued) 

F-32 

Author, 

year 

Level of 

analysis 

Intervention/Exposure, 

N 

GA at 

delivery 

(in 

weeks), 

mean 

(SD) 

GA determined by 

Macrosomia 

or LGA 

(PW>90%), n 

(%) 

Birth weight 

(in grams), 

mean 

Shoulder dystocia, 

n (%) 

Birth 

trauma, n 

(%) 

Morta

(

C: Trial of labor after CD, 423 

38.3 (2.2) 

NR Birth weight > 

4000 gm: 76 (18) 

Marchiano, 2004 52

exposure 

E: Repeat elective cesarean, 440 

38 (3.2) NR Birth weight > 

4000 gm: 145 (33) p < 0.0001¶

* Comparing C to I. † Comparing HC to E. ‡ Comparing >40 weeks to <40 weeks. ¶ Comparing C to E. C = control group; CD = cesarean delivery; CI = confidence interval; E = exposure group; EFW = estimated fetal weight; GA = gestational age; GDM

GDMA2 = requiring medical therapy; gm = gram; HC = historical control group; I = intervention group; LGA = large for gestational age; LMP = last reported; NS = not significant; OR = odds ratio; PW = percentile weight; RDS = respiratory distress syndrome; SD = standard deviation 
Evidence Table 13. Quality of studies reporting on the effects of labor management on maternal and neonatal outcomes 

F-33 

Author, year

Hypotheses 

stated

Inclusion 

criteria 

reported Sampling

Power/ 

Sample size 

calculations

Outcomes 

defined

Loss to 

followup/ 

reported in 

analysis

Miss

repo

an

Conway, 199853 ● ● Consecutive ● <10%/ NA <10%/ Lurie, 199658 ● Consecutive ● ● <10% / NA <10% / Lurie, 199257 ● Consecutive <10% / NA <10% / Peled, 200459 Consecutive ● <10% / NA <10% / Rayburn, 200556 ● Consecutive ● <10% / NA <10% / Marchiano, 200452 ● ● Consecutive ● <10% / NA 10-20% Keller, 199154 ● Consecutive ● <10% / NA <10% / 

Author, year Randomized 

Randomization 

scheme described Double blinded 

Blinding 

described 

Withdrawals 

described 

Kjos, 199355 ● ● 

● = Yes; blank space = No/Not reported; NA= not applicable *Total quality score calculated using the Jadad22 criteria.
Evidence Table 14. Grading of the body of evidence of the effects of labor management on maternal and neonatal outcomes (K

F-34 

Labor management on maternal and neonatal outcomes 

Quantity of evidence:

Number of studies 

8 

Total number of patients studied 6648 Quality and consistency of evidence:

Were study designs mostly randomized trials (high quality), nonrandomized controlled trials (medium quality), observational studies (low quality), or about a 50:50 mix of experimental and observational (medium quality)? 

Low 

Did the studies have serious (-1) or very serious (-2) limitations in quality? (Enter 0 if none) 

-2 

Did the studies have important inconsistency? (-1) -1 Was there some (-1) or major (-2) uncertainty about the directness (i.e. extent to which the people, interventions and outcomes are similar to those of interest)? 

0 

Were data imprecise or sparse? (-1) (i.e. lack of data or very wide confidence intervals that may change conclusions) 

-1 

Did the studies have high probability of reporting bias? (-1) 0 Did the studies show strong evidence of association between intervention and outcome? (“strong” if significant relative risk or odds ratio > 2 based on consistent evidence from 2 or more studies with no plausible confounders (+1); “very strong” if significant relative risk or odds ratio > 5 based on direct evidence with no major threats to validity (+2))- use your clinical judgment for absolute differences.

0 

Did the studies have evidence of a dose-response gradient? (+1) 0 Did the studies have unmeasured plausible confounders that most likely reduced the magnitude of the observed association? (+1) 

+1 

Overall grade of evidence (high, moderate, low, very low) Very low 

High = further research is very unlikely to change our confidence in the estimates; moderate = further research is likely to have an important impact on estimate of effect and may change the estimate; low = further research is likely to have an important impact on our confidence in the estimate of effect 

estimate; very low = any estimate of effect is very uncertain. 
Evidence Table 15. List of covariates considered and included in models assessing the association of risk factors with the dev

diabetes following a pregnancy with gestational diabetes 

F-35 

Covariate 

Buchanan, 

199875

Buchanan, 

199974 Cheung, 200660 Cho, 200561 Cho, 200662 Dacus, 199465 

# abnormal OGTT results # prior GDM pregnancies 

○ ●

% pre-pregnancy obesity 1-hr plasma glucose diagnostic OGTT 

○ ● ●

2-hr glucose 2-hr OGTT ○ ●3-hr insulin on diagnostic OGTT 50-gm GCT 75-gm OGTT glucose AUC 

○

8-year DM risk (%) Additional pregnancy Age ○ ○ ○ ○ ○ ● ● ● ● ● ● ● ● ● ● ○ Antepartum 30 min incremental plasma insulin/glucose 

●

Antepartum OGTT glucose AUC Antepartum plasma glucose 1-hr at screening 

○ ○ ○

Area under the glucose curve or pregnancy OGTT AUC at initial postpartum OGTT Basal glucose production rate 

● ● ●

Beta-cell compensation index 

○ ○ ●

Blood pressure ● ● ● ● ● ● ● ●BMI BMI at GTT 
Evidence Table 15. List of covariates considered and included in models assessing the association of risk factors with the dev

diabetes following a pregnancy with gestational diabetes (continued) 

F-36 

Covariate 

Buchanan, 

199875

Buchanan, 

199974 Cheung, 200660 Cho, 200561 Cho, 200662 Dacus, 199465 

BMI at index pregnancy 

○ ●

Body fat % ○ ○ ○ ○ ○ ○ ○ ○Body fat weight ○ ○ ○ ● ○ ○ ○ ○Breastfeeding ○Clamp SI ● ● ○Class A2 Completion of 2nd

pregnancy 

Contraceptive use C-peptide glucose score Dose of bedtime intermediate-acting insulin required 

● ○

Duration of followup ● ● ● ● ● ● ● ●Duration of OC use Fasting blood glucose level 

● ○

Fasting blood sugar FHxT2DM ○ ● ● ● ● ○ ● ● ● ● ● FPG at diagnosis ○ ● ●FSIGT acute insulin response 

○ ○ ○

FU months GAD and IA-2 antibody status GDM class A1 Gestational age at delivery 

○ ○ ○ ○ 

Gestational age at GDM diagnosis 

● ○ 

GTT total HDL cholesterol Height Highest antepartum fasting glucose Highest FPG ○
Evidence Table 15. List of covariates considered and included in models assessing the association of risk factors with the dev

diabetes following a pregnancy with gestational diabetes (continued) 

F-37 

Covariate 

Buchanan, 

199875

Buchanan, 

199974 Cheung, 200660 Cho, 200561 Cho, 200662 Dacus, 199465 

HLA DR3 or DR4-DQ8 Homocysteine level ●Hospital ○ ●Incremental glucose area, diagnostic OGTT 

● ○ ○

Insulin Interaction term for breastfeeding and OC use Interaction term of OC use and triglyceride level Lipid profile which includes triglyceride, HDL and LDL and cholesterol 

● ● ● ● ● ● ● ●

Mean arterial pressure Mean BMI at 1stantenatal visit Method of glucose control 

○ ○ ● ○ ○

OGTT 30-min incremental insulin: glucose 

● ● ○

OGTT glucose area Parity ○ ● ○ ● ● ● ● ● ● ● ● Postpartum BMI ○ ○ ○ ○ ○ ○ ○ ○ ● ○ ○ ○ ○ Postpartum FPG Postpartum OGTT glucose AUC Postpartum weight Postpartum weight change 

○ ○ ○ ○ ○ ○ ○ ○ ○ ● ○

Pregnancy weight gain 

○ ○ ○ ○
Evidence Table 15. List of covariates considered and included in models assessing the association of risk factors with the dev

diabetes following a pregnancy with gestational diabetes (continued) 

F-38 

Covariate 

Buchanan, 

199875

Buchanan, 

199974 Cheung, 200660 Cho, 200561 Cho, 200662 Dacus, 199465 

Pre-pregnancy BMI ○ ○ ○ ○ ● Pre-pregnancy weight Previous macrosomia Previous stillbirth Prior OC use Race ○ ○ ○ ○ ○ Serum CRP Spontaneous abortions Subscapular skin fold thickness 

○ ○ ○ ○ ○ ● ○ ○

Suprailiac skin fold thickness 

● ○ ○ ○ ○ ○ ○ ○

Total AUC for diagnostic antepartum 100-gm OGTT glucose 

●

Total cholesterol ○ ○ ○ ○ ○ ○ ○ ○Triceps skin fold thickness 

○ ● ○ ○ ○ ○ ○ ○

Triglycerides ○ ○ ○ ○ ○ ○ ○ ○Waist circumference ○ ○ ○ ○ ○ ○ ○ ●Wait-to-hip ratio ○ ○ ● ○ ○ ○ ○ ○Working status ● ● ○ ● ● ● ● ●
Evidence Table 15. List of covariates considered and included in models assessing the association of risk factors with the dev

diabetes following a pregnancy with gestational diabetes (continued) 

F-39 

Covariate 

Kjos, 

199869

Lobner, 

200666

Pallardo, 

199973

Peters, 

199672

SchaeferGraf, 200270 Steinhart, 199771 Xiang, 200664 Met

199

# abnormal OGTT results 

●

# prior GDM pregnancies 

○ ● ○

% pre-pregnancy obesity 

○

1-h plasma glucose diagnostic OGTT 2-hr glucose ○ 2-hr OGTT 3-hr insulin on diagnostic OGTT 3-hr integrated insulin 

● 

50-gm GCT ●75-gm OGTT glucose AUC 8-year DM risk (%) 

○

Additional pregnancy 

○ ●

Age ○ ● ○ ○ ○ ○ ○ ○ ○ ○ Antepartum 30 min incremental plasma insulin/glucose Antepartum OGTT glucose AUC Antepartum plasma glucose 1-hr at screening Area under the glucose curve of pregnancy OGTT 

●

AUC at initial postpartum OGTT 

●
Evidence Table 15. List of covariates considered and included in models assessing the association of risk factors with the dev

diabetes following a pregnancy with gestational diabetes (continued) 

F-40 

Covariate 

Kjos, 

199869

Lobner, 

200666

Pallardo, 

199973

Peters, 

199672

SchaeferGraf, 200270 Steinhart, 199771 Xiang, 200664 Met

199

Basal glucose production rate 

○ 

Basal Insulin ○ Beta-cell compensation index Blood pressure BMI ○BMI at GTT ○BMI at index pregnancy Body fat % Body fat weight Breastfeeding ● ● ● ○Clamp S1 Class A2 ●Completion of 2nd

pregnancy 

●

Contraceptive use 

● ○ ● ○ ○

C-peptide glucose score 

●

Diagnostic OGTT Dose of bedtime intermediateacting insulin required Duration of followup 

○

Duration of OC use 

●

Fasting blood glucose level Fasting blood sugar 

○

FHxT2DM ○ ● ● ● ○ FPG at diagnosis ●FSIGT acute insulin response 
Evidence Table 15. List of covariates considered and included in models assessing the association of risk factors with the dev

diabetes following a pregnancy with gestational diabetes (continued) 

F-41 

Covariate 

Kjos, 

199869

Lobner, 

200666

Pallardo, 

199973

Peters, 

199672

SchaeferGraf, 200270 Steinhart, 199771 Xiang, 200664 Met

199

FU months GAD and IA-2 antibody status 

●

GDM class A1 GDM recurrence ○ ○Gestational age at delivery 

○

Gestational age at GDM diagnosis 

●

GTT total ○HDL cholesterol ● ● ○Height Highest antepartum fasting glucose Highest FPG HLA DR3 or DR4-DQ8 

○

Homocysteine level Hospital Incremental glucose area Insulin Interaction term for breastfeeding and OC use 

○ ○ ●

Interaction term of OC use and triglyceride level 

○ ● ○

Lipid profile which includes triglyceride, HDL and LDL and cholesterol Mean arterial pressure 

○

Mean BMI at 1stantenatal visit 
Evidence Table 15. List of covariates considered and included in models assessing the association of risk factors with the dev

diabetes following a pregnancy with gestational diabetes (continued) 

F-42 

Covariate 

Kjos, 

199869

Lobner, 

200666

Pallardo, 

199973

Peters, 

199672

SchaeferGraf, 200270 Steinhart, 199771 Xiang, 200664 Met

199

Method of glucose control 

● ● ○ ○ ○ ○

Obesity ● OGTT 30-min incremental insulin: glucose OGTT 30-min stimulated insulin secretion 

○ 

OGTT glucose area 

●

Parity ○ ● ○ ○ ○ ○ ○ ○ ○ ● Postpartum BMI ○ ● ● ● ●Postpartum FPG ○Postpartum OGTT glucose AUC Postpartum weight Postpartum weight change 

● ● ● ● ●

Pregnancy weight gain Pre-pregnancy BMI 

○

Pre-pregnancy weight Previous GDM ○Previous macrosomia 

○

Previous stillbirth ○Prior OC use ●Race ○ ○ ○ ○ ○ ○ ○ ○ Serum CRP ○Spontaneous abortions 

○

Subscapular skin fold thickness 
Evidence Table 15. List of covariates considered and included in models assessing the association of risk factors with the dev

diabetes following a pregnancy with gestational diabetes (continued) 

F-43 

Covariate 

Kjos, 

199869

Lobner, 

200666

Pallardo, 

199973

Peters, 

199672

SchaeferGraf, 200270 Steinhart, 199771 Xiang, 200664 Met

199

Suprailiac skin fold thickness Total AUC for diagnostic antepartum 100-gm OGTT glucose Total cholesterol ○Triceps skin fold thickness Triglycerides ● ○ ●Waist circumference Wait-to-hip ratio Working status ○ = Variable considered in multivariate model; ● = variable included in multivariate model AUC = area under the curve; BMI = body mass index; CRP= C-reactive protein; DM = diabetes mellitus; FH = family history; FPG = fasting plasma g

sampled intravenous glucose tolerance; FU = followup; GAD = glutamic acid decarboxylase; GCT = glucose challenge test; GDM = Gestational diabeGTT = glucose tolerance test; HDL = high density lipoprotein; HLA = human leukocyte antigen; hr = hour; IA-2 = Insulinoma antigen-2; LDL = low 

minute; OC = oral contraceptive; OGTT = oral glucose tolerance test; T2DM = Type 2 diabetes mellitus. 
Evidence Table 16. Characteristics of studies reporting on the risk associated with the development of type 2 diabetes mellitus 

with gestational diabetes 

F-44 

Author, year 

Country 

Study design 

Age (in 

years), 

mean Race, n (%) 

Gravida and 

parity, mean N 

Diabetes 

diagnosis 

Followup 

time Covaria

NGT: 30.8 NGT: Hisp: 49 

(100) 

IGT: 29.3 IGT: Hisp: 61 (100) 

Buchanan, 199875

US Cohort 

T2DM: 32.3 T2DM: Hisp: 12 

(100) 

NR 122 Abnormal 75-gm 

OGTT 

0-6 months Age, race, pregna

pregnancy BMI, pgestational age at glucose control, 7AUC, breastfeediantepartum 30 miinsulin/glucose, toantepartum 100-g

Buchanan, ND: 30.3 ND: Hisp: 77 (100) 199974

US Cohort 

T2DM: 29.6 T2DM: Hisp: 14 

(100) 

NR 91 Abnormal 75-gm 

OGTT 

11-26 months 

Age, race, pregnapregnancy BMI, pgestational age at plasma glucose (incremental glucoOGTT, postpartum plasma glucose dcompensation indproduction rate, Oinsulin:glucose, cinsulin response

ND: 32.3 ND: parity: 1.6 T2DM: 31.9 T2DM: parity: 0.9 

Cheung, 200660

Australia Cohort 

T: 32.1 

NR 

T: parity: 1.4 

102 Abnormal 75-gm 

OGTT, self report followed by verification from local doctor or abnormal 75-gm OGTT at retest 

0-8 years, mean=4.5 years 

Age, parity, FPG pregnancy, 2-hr Opregnancies, metFHxT2DM, hospitlevel, dose of bedinsulin required

NGT: 30.6 NGT: (≥ 3 children 

(%): 32.1) 

IGT: 32.1 IGT: (≥ 3 children 

(%): 55.8) 

Cho, 200561

Korea Cohort T2DM: 30 

NR 

T2DM: (≥ 3 children (%): 33.3) 

170 Abnormal 75-gm 

OGTT 

6 weeks and annually thereafter 

Age, pre-pregnanglucose control, gdiagnosis, FHxT2homocysteine lev
Evidence Table 16. Characteristics of studies reporting on the risk associated with the development of type 2 diabetes mellitus 

with gestational diabetes (continued) 

F-45 

Author, year 

Country 

Study design 

Age (in 

years), 

mean Race, n (%) 

Gravida and 

parity, mean N 

Diabetes 

diagnosis 

Followup 

time Covaria

NGT: 33.2 NGT: 

(para 1 (%): 39.0; para 2 (%): 51.4; para 3+ (%): 9.5) 

IGT: 34.2 IGT: 

(para 1 (%): 37.8; para 2 (%): 56.9; para 3+ (%): 3.4) 

Cho, 200662

Korea Cohort 

T2DM: 33 

NR 

T2DM: (para 1 (%): 39.7; para 2 (%): 56.9; para 3+ (%): 3.4) 

909 Abnormal 75-gm 

OGTT 

6 weeks, annually up to 6 years 

Age, parity, body triglycerides, postpressure, lipid proFHxT2DM, workinwaist circumferenpostpartum subscpostpartum suprapostpartum tricep postpartum body waist-to-hip ratio

ND: ≥30 year (n, %): 40 (47%); <30 year (n, %): 46 (53%) 

ND: AA: 60 (70); C: 23 (27); Other: 3 (3) 

Dacus, 199465

US Cohort 

T2DM: ≥30 year (n, %): 5 (36%); <30 year (n, %): 9 (64%) 

T2DM: AA: 11 (72); C: 2 (21); Other: 1 (7) 

NR 100 Abnormal 75-gm 

OGTT 

5-10 weeks postpartum

Age, race, gestatidiagnosis, method postpartum BMI

Jang, 200363

Korea Cohort 

T: 30.9 T: NR T: parity: 0.5 311 Abnormal 75-gm 

OGTT 

NR Age, pre-pregnan

BMI, parity, gestaGDM class A1, gediagnosis, 2-hr gldiagnostic OGTT, postpartum weigh
Evidence Table 16. Characteristics of studies reporting on the risk associated with the development of type 2 diabetes mellitus 

with gestational diabetes (continued) 

F-46 

Author, year 

Country 

Study design 

Age (in 

years), 

mean Race, n (%) 

Gravida and 

parity, mean N 

Diabetes 

diagnosis 

Followup 

time Covaria

Kjos, 199568

US Cohort 

T: 30.3 T: Hisp: 671 (100) T: parity: 2.8 671 Abnormal 75-gm 

OGTT 

Between 4 to 16 weeks; Additional followup within 7.5 years postpartum

Age, race, postpapostpartum OGTT gestational age at antepartum OGTT antepartum fastin

COC: 28.5 COC: Hisp: 383 

(100) 

Kjos, 1998 COC: parity: 2.3 69

US Cohort 

Progestin only: 29.4 

Progestin only: Hisp: 78 (100) 

Progestin only: parity: 3.1 

443 Abnormal 75-gm 

OGTT 

Varied (Cox model) 

Age, race, postpaof glucose controarterial pressure, contraceptive usepostpartum OGTTpregnancy, postpduration of OC us

Autoantibody (+): 29.9 Autoantibody (-): 31.4 

Lobner, 200666

Germany Cohort 

T: NR 

NR NR 302 Abnormal 75-gm 

OGTT 

9 months and 2, 5, 8 and 11 years postpartum

Age, BMI at first pglucose control, Hyear DM risk (%), status, parity, ser

Metzger, 199367

US Cohort 

Model 1 ND: 31.7 IGT: 32.0 T2DM: 33.0 Model 2 ND: 31.4 IGT: 31.7 T2DM: 32.3 

NR Model 1: parity 

ND: 1.5 IGT: 1.5 T2DM: 1.7 Model 2: parity ND: 1.6 IGT: 1.3 T2DM: 2.1 

Model 1 177 Model 2 172 

Abnormal 100-gm OGTT 

3-6 months (model 1), and year 1,2,3,4,&5 (model 2) 

Age, race, FHxT2glucose, basal insintegrated insulin, insulin secretion
Evidence Table 16. Characteristics of studies reporting on the risk associated with the development of type 2 diabetes mellitus 

with gestational diabetes (continued) 

F-47 

Author, year 

Country 

Study design 

Age (in 

years), 

mean Race, n (%) 

Gravida and 

parity, mean N 

Diabetes 

diagnosis 

Followup 

time Covaria

Pallardo, ND: 33.1 ND: C: 745 (100) ND: parity: 1.89 199973

Spain Cohort 

T2DM: 32.6 T2DM: C: 43 (100) T2DM: parity: 1.94 

788 Abnormal 75-gm 

OGTT 

3-6 months Age, race, parity, 

recurrence of GDabnormal OGTT rC-peptide glucose 

No additional pregnancy: 30.4 

No additional pregnancy: Hisp: 578 (100) 

No additional pregnancy: parity: 2.8 

Peters, 199672

US Cohort 

Additional pregnancy: 29.9 

Additional pregnancy: Hisp: 87 (100) 

Additional pregnancy: parity: 2.8 

666 Abnormal 75-gm 

OGTT 

3-89 months 

Age, race, parity, delivery, duration contraceptive usepostpartum weigharea, postpartum 

ND: 31.1 ND: parity: 1.9 T2DM: 32.2 T2DM: parity: 2.2 

SchaeferGraf, 200270

US Cohort 

T: 31.2 

NR 

T: NR 

1636 Abnormal 75-gm 

OGTT, taking diabetes medications 

1-4 months Age, parity, previo

stillbirth, FPG at dunder the glucose OGTT, gestationaprevious GDM, 50

ND: 31 ND: American 

Indian: 41 

Steinhart, ND: parity: 2.45 199771

US Cohort 

NIDDM: 32.7 NIDDM: American 

Indian: 47 

NIDDM: parity: 3.43

88 Abnormal 75-gm 

OGTT, type 2 diabetes diagnosed in medical record 

9-12 years Age, race, parity, 

sugar, spontaneorecurrent GDM, m
Evidence Table 16. Characteristics of studies reporting on the risk associated with the development of type 2 diabetes mellitus 

with gestational diabetes (continued) 

F-48 

Author, year 

Country 

Study design 

Age (in 

years), 

mean Race, n (%) 

Gravida and 

parity, mean N 

Diabetes 

diagnosis 

Followup 

time Covaria

DMPA: 30 DMPA: Hisp: 96 

(100) 

Xiang, 2006 DMPA: parity: 2.6 64

US Cohort 

COC: 29 COC: Hisp: 430 

(100) 

COC: parity: 2.3 

526 Abnormal 75-gm 

OGTT 

4-6 weeks, 3-6 month intervals thereafter 

Age, race, parity, control, contracepbreastfeeding, FHtriglycerides, weigfollowup, interactitriglyceride level, breastfeeding and 

* Includes triglyceride, high density lipoprotein, and low density lipoprotein cholesterol 

AA = African American; AUC = area under the curve; BMI = body mass index; C = Caucasian; COC = combination oral contraceptive; CRP = C-reac

depomedroxyprogesterone acetate; FPG = fasting plasma glucose; FSIGT = frequently sampled intravenous glucose tolerance; GAD = glutamic acid d

glucose challenge test; GDM = gestational diabetes mellitus; gm = gram; GTT = glucose tolerance test; HDL = high density lipoprotein; Hisp = Hispa

antigen; hr = hour; IA-2 = insulinoma antigen-2; IGT = impaired glucose tolerance; min = minutes; ND = non-diabetic; NGT = normal glucose toleran

dependent diabetes mellitus; NR = not reported; OC = oral contraceptive; OGTT = oral glucose tolerance test; SI = sensitivity index; T2DM = type 2 dUS = United States
Evidence Table 17. Quality of studies reporting on the risk associated with the development of type 2 diabetes following a preg

diabetes 

F-49 

Author, year 

Are pre-specified 

hypotheses 

stated? 

Are inclusion and 

exclusion criteria 

reported? Sampling 

Were power or 

sample size 

calculations 

used? 

Does the article 

state how the 

outcome was 

defined? 

Loss to follow

/ Report 

comparisons 

those lost t

followup vs 

participant

Buchanan, 199875 ● Consecutive ● 10-20% / ●Buchanan, 199974 ● ● Convenience ● 10-20% / Cheung, 200660 ● ● Convenience ● >20% / ●Cho, 200561 ● Convenience ● >20% / Cho, 200662 ● Convenience ● >20% / Dacus, 199465 ● ● Convenience ● >20% / Jang, 200363 ● ● Convenience ● 10-20% / ●Kjos, 199568 ● ● Convenience ● >20% / Kjos, 199869 ● Consecutive ●Lobner, 200666 ● ● Convenience ● >20% / Pallardo, 199973 ● ● Convenience ● >20% / ●Peters, 199672 ● Consecutive ●Schaefer-Graf, 200270 ● ● Convenience ● >20% / ● Steinhart, 199771 ● Consecutive ● >20% / Xiang, 200664 ● Convenience 

●=yes; blank space=no/not reported 
Evidence Table 18. Studies reporting on the association between a family history of type 2 diabetes mellitus and the developm

mellitus following a pregnancy with gestational diabetes 

F-50 

Author, year Risk factor Units N 

Measure of 

association (95% CI) Covariates include

Cheung, 200660 FHxT2DM NR 102 Yes/no Age, parity, FPG at diagnosis, BMI at index p

prior GDM pregnancies, method of glucose c

Cho, 200561 FHxT2DM Yes/no 170 No: ref 

Yes: RR = 1.706 (0.638 - 4.566) 

Age, gestational age at GDM diagnosis, pre-pdiagnosis, homocysteine level 

Cho, 200662 FHxT2DM NR 909 NR Cho reported 8 models, which adjusted for bl

profile*, age, duration of followup, parity, worfollowing measures of adiposity at postpartumcircumference, weight, subscapular skin fold fold thickness, tricep skin fold thickness, body hip ratio. The relative measure for FHxT2DM of the models. 

Jang, 200363 FHxT2DM Yes/no 311 NR Pre-pregnancy weight, gestational age at GD

glucose, 3-hr insulin on diagnostic OGTT, agBMI, postpartum weight 

Xiang, 200664 FHxT2DM Yes/no 526 NR Contraceptive use, postpartum BMI, breastfe

triglycerides, postpartum weight change 

Xiang, 200664 FHxT2DM Yes/no 526 NR Interaction term for breastfeeding and OC us

triglycerides, HDL cholesterol, postpartum we

Xiang, 200664 FHxT2DM Yes/no 526 NR Interaction term for OC use and triglyceride le

breastfeeding, HDL cholesterol, postpartum w

* Includes triglyceride, high density lipoprotein, and low density lipoprotein cholesterol 

BMI = body mass index; CI = confidence interval; FHxT2DM = family history of type 2 diabetes mellitus; FPG = fasting plasma glucose; GDM = gesHDL = high density lipoprotein; hr = hour; NR = not reported; OC = oral contraceptive; OGTT = oral glucose tolerance test; ref = reference group; RR 
Evidence Table 19. Studies reporting on the association between sociodemographics and the development of type 2 diabetes m

pregnancy with gestational diabetes 

F-51 

Author, year Risk factor Units N 

Measure of 

association (95% CI) Covariates include

Cho, 200561 Age Years 170 ≤30: ref 

>30: RR = 2.03 (0.682 - 6.03) 

Gestational age at GDM diagnosis, pre-pregnFPG at diagnosis, homocysteine level 

Dacus, 199465 Age Years 100 <30: ref 

≥30: RR = 0.68 (0.24 - 1.88) 

None 

Cheung, 200660 Age NR 102 NR Parity, FPG at diagnosis, BMI at index pregna

GDM pregnancies, method of glucose contro

Cho, 200662 Age Years 909 NR Cho reported 8 models, which adjusted for bl

profile*, age, duration of followup, parity, FHxand one of the following measures of adiposiwaist circumference, weight, subscapular skiskin fold thickness, tricep skin fold thickness, waist-to-hip ratio. The relative measure for aany of the models.

Jang, 200363 Age Years 311 NR Pre-pregnancy weight, gestational age at GD

glucose, 3-hr insulin on diagnostic OGTT, heFHxT2DM, postpartum weight 

Lobner, 200666 Age Years 302 NR GAD and IA-2 antibody status, method of glu

pregnancy visit, parity, serum CRP 

Cheung, 200660 Hospital NR 102 NR Age, parity, FPG at diagnosis, BMI at index p

prior GDM pregnancies, method of glucose c

Cho, 200662 Working status Yes/no 909 NR Cho reported 8 models, which adjusted for bl

profile*, age, duration of followup, parity, FHxand one of the following measures of adiposiwaist circumference, weight, subscapular skiskin fold thickness, tricep skin fold thickness, waist-to-hip ratio. The relative measure for wreported in any of the models. 

Dacus, 199465 Race NR 100 Other: ref 

Black: RR = 1.5 (0.45 - 4.98) 

None 

* Includes triglyceride, high density lipoprotein, and low density lipoprotein cholesterol 

BMI = body mass index; CI = confidence interval; CRP = C-reactive protein; FHxT2DM = family history of type 2 diabetes; FPG = fasting plasma gl

decarboxylase; GDM = gestational diabetes mellitus; hr = hour; NR = not reported; OGTT = oral glucose tolerance test; ref = reference group; RR = r
Evidence Table 20. Studies reporting on the association between parity and the development of type 2 diabetes mellitus follow

gestational diabetes 

F-52 

Author, year Risk factor Units N 

Measure of 

association (95% CI) Covariates include

Cheung, 200660 Parity NR 102 NR Age, FPG at diagnosis, BMI at index pregnan

GDM pregnancies, method of glucose contro

Cho, 200662 Parity NR 909 NR Cho reported 8 models, which adjusted for bl

profile*, age, duration of followup, parity, FHxand one of the following measures of adiposiwaist circumference, weight, subscapular skiskin fold thickness, tricep skin fold thickness, waist-to-hip ratio. The relative measure for pany of the models. 

Lobner, 200666 Parity NR 302 0: ref 

1-2: RH = 1.2 (0.8 - 1.7; p = 0.45) >2: RH = 2.5 (1.1 - 5.3; p = 0.02) 

GAD and IA-2 antibody status, method of glupregnancy visit, age, serum CRP 

Metzger, 199367

Parity NR 172 OR = 1.21 (p = 0.09) 3-hr integrated insulin, obesity 

* Includes triglyceride, high density lipoprotein, and low density lipoprotein cholesterol 

BMI = body mass index; CI = confidence interval; CRP = C-reactive protein; FHxT2DM = family history of type 2 diabetes mellitus; FPG = fasting p

glutamic acid decarboxylase; GDM = gestational diabetes mellitus; IA-2 = insulinoma antigen-2; NR = not reported; OGTT = oral glucose tolerance te

reference group; RH = relative hazard 
Evidence Table 21. Studies reporting on the association between pregnancy-related factors and the development of type 2 diab

pregnancy with gestational diabetes 

F-53 

Author, year Risk factor Units N 

Measure of 

association (95% CI) Covariates include

Kjos, 199568 Gestational age 

at GDM diagnosis 

Weeks 671 Q1: ref 

Q2: RH = 0.66 (0.39 - 1.12) Q3: RH = 0.73 (0.45 - 1.18) Q4: RH = 0.48 (0.29 - 0.82) p = 0.01 

Postpartum OGTT glucose AUC, antepartum highest antepartum fasting glucose 

Schaefer-Graf, 200270 Gestational age at GDM 

diagnosis 

Weeks 1636 Q1: ref 

Q2: OR = 1.12 (0.72 - 1.74) Q3: OR = 0.45 (0.27 - 0.76) Q4: OR = 0.35 (0.23 - 0.54) 

FPG at diagnosis, class A2, area under the gpregnancy OGTT, previous GDM, 50-gm GC

Cho, 200561 Gestational age 

at GDM diagnosis 

Weeks 170 ≥26 weeks: ref 

<26 weeks: RR = 2.399 (0.875 - 6.577) 

Age, pre-pregnancy BMI, FHxT2DM, FPG at level 

Jang, 200363 Gestational age 

at GDM diagnosis 

Weeks 311 Coefficient = 

-0.00928 (se = 0.0539) 

Pre-pregnancy weight, 2-hr glucose, 3-hr insuage, height, pre-pregnancy BMI, FHxT2DM, p

Dacus, 199465 Gestational age 

at GDM diagnosis 

Weeks 100 <24: ref 

≥24: RR = 2.49 (0.9 - 6.88) 

None 

Cheung, 200660 Method of 

glucose control 

Yes/no 102 No insulin: ref 

Insulin: RR = 3.2 (1.6 - 7) 

Age, parity, FPG at diagnosis, BMI at index pprior GDM pregnancies, FHxT2DM, hospital 

Lobner, 200666 Method of 

glucose control 

Yes/no 302 Diet: ref 

Insulin: RH = 4.7 (3.2 - 7.1; p < 0.0001) 

GAD and IA-2 antibody status, BMI at first preserum CRP 

Kjos, 199869 Method of 

glucose control 

NR 443 NR Contraceptive use, AUC at the initial postpart

additional pregnancy, postpartum weight loss

Steinhart, 199771 Method of 

glucose control 

Yes/no 88 No insulin: ref 

Insulin: OR = 2.83 (0.8 - 11.2) 

None 

Dacus, 199465 Method of 

glucose control 

Yes/no 100 Diet: ref 

Insulin: RR = undefined (0 DM treated with diet only) 

None 

Cheung, 200660 Dose of bedtime 

intermediateacting insulin required 

Insulin units unspecified 

102 RR = 1.09 (1.03 - 1.17) fasting blood glucose level 

Schaefer-Graf, 200270 50-gm GCT mg/dL 1636 Q1: ref Q2: OR = 2.86 (1.24 - 6.58) 

Q3: OR = 3.82 (1.72 - 8.48) Q4: OR = 3.46 (1.57 - 7.64) 

FPG at diagnosis, class A2, area under the gpregnancy OGTT, gestational age at GDM di
Evidence Table 21. Studies reporting on the association between pregnancy-related factors and the development of type 2 diab

pregnancy with gestational diabetes (continued) 

F-54 

Author, year Risk factor Units N 

Measure of 

association (95% CI) Covariates include

Schaefer-Graf, 200270 Class A2 (any FBG ≥ 105) Yes/no 1636 No: ref Yes: OR = 2.4 (1.22 - 4.72) FPG at diagnosis, area under the glucose cu

gestational age at GDM diagnosis, previous G

Schaefer-Graf, 200270

Previous GDM Yes/no 1636 No: ref 

Yes: OR = 1.63 (1.07 - 2.47) 

FPG at diagnosis, class A2, area under the gpregnancy OGTT, gestational age at GDM di

Cheung, 200660 # prior GDM 

pregnancies 

NR 102 NR Age, parity, FPG at diagnosis, BMI at index p

method of glucose control, FHxT2DM, hospit

Steinhart, 199771 Spontaneous 

abortions 

Yes/no 88 No: ref 

Yes: OR = 1.36 (0.5 - 3.5) 

None 

AUC = area under the glucose tolerance curve; BMI = body mass index; CI = confidence interval; class A2 = insulin requiring gestational diabetics; C= diabetes mellitus; FHxT2DM = family history of type 2 diabetes mellitus; FPG = fasting plasma glucose; GAD = glutamic acid decarboxylase; GCT 

GDM = gestational diabetes mellitus; gm = gram; hr = hour; NR = not reported; OC = oral contraceptive; OGTT = oral glucose tolerance Test; OR = o

reference group; RH = relative hazard; RR = relative risk; se = standard error 
Evidence Table 22. Studies reporting on the association between postpartum factors and the development of type 2 diabetes m

pregnancy with gestational diabetes 

F-55 

Author, year Risk factor Units N 

Measure of 

association (95% CI) Covariates include

Peters, 199672 Additional 

pregnancy 

Yes/no 666 No: ref 

Yes: RH = 3.34 (1.8 - 6.19) 

Postpartum weight change, OGTT glucose abreastfeeding 

Kjos, 199869 Additional 

pregnancy 

NR 443 NR Contraceptive use, AUC at the initial postpart

method of glucose control, postpartum weigh

Peters, 199672 Breastfeeding Yes/no 666 NR Additional pregnancy, postpartum weight cha

postpartum BMI 

Xiang, 200664 Breastfeeding Yes/no 526 NR Contraceptive use, postpartum BMI, FHxT2D

triglycerides, weight change during followup 

Xiang, 200664 Breastfeeding Yes/no 526 NR Interaction term for OC use and triglyceride le

FHxT2DM, HDL cholesterol, weight change d

Cho, 200662 Duration of 

followup 

Yes/no 909 NR Cho reported 8 models, which adjusted for bl

profile*, age, duration of followup, parity, FHxand one of the following measures of adiposipostpartum BMI, waist circumference, weightthickness, suprailiac skin fold thickness, tricefat weight, and waist-to-hip ratio. The relative followup was not reported in any of the mode

Steinhart, 199771 Recurrent GDM Yes/no 88 No: ref 

Yes: OR = 24.8 (3 - 1132.2) 

None 

* Includes triglyceride, high density lipoprotein, and low density lipoprotein cholesterol 

AUC = area under the glucose tolerance curve; BMI = body mass index; CI = confidence interval; FHxT2DM = family history of type 2 diabetes mell

diabetes mellitus; HDL = high density lipoprotein; NR = not reported; OC = oral contraceptive; OGTT = oral glucose tolerance test; OR = odds ratio; 

relative hazard
Evidence Table 23. Studies reporting on the association between anthropometric measures and the development of type 2 diab

pregnancy with gestational diabetes 

F-56 

Author, year Risk factor Units N 

Measure of 

association (95% CI) Covariates include

Pallardo, 199973 Pre-pregnancy 

BMI 

kg/m2 788 ≤27: ref 

>27: OR = 8.66 (2.27 - 32.94; p < 0.01) 

# of abnormal OGTT results (including fastingscore 

Jang, 200363 Pre-pregnancy 

BMI 

kg/m2 311 NR Pre-pregnancy weight, gestational age at GD

glucose, 3-hr insulin on diagnostic OGTT, agpostpartum weight 

Cho, 200561 Pre-pregnancy 

BMI 

kg/m2 170 ≤23: ref 

>23: RR = 0.779 (0.27 - 2.246) 

Age, gestational age at GDM diagnosis, FHxThomocysteine level 

Jang, 200363 Pre-pregnancy 

weight 

kg 311 Coefficient = 0.3639 (se = 

0.1027) 

Gestational age at GDM diagnosis, 2-hr glucodiagnostic OGTT, age, height, pre-pregnancy postpartum weight 

Lobner, 200666 BMI at first 

pregnancy visit 

kg/m2 302 ≤30: ref 

>30: RH = 1.5 (1 - 2.2; p = 0.04) 

GAD and IA-2 antibody status, method of gluserum CRP 

Metzger, 199367

Obesity (defined as ≥ 120% of ideal body weight) 

% 172 OR = 2.83 (p < 0.001) 3-hr integrated insulin, parity 

Cheung, 200660 BMI at index 

pregnancy 

kg/m2 102 RR = 1.1 (1 - 1.2) Age, parity, FPG at diagnosis, 2-hr OGTT, # 

method of glucose control, FHxT2DM, hospit

Cho, 200662 Postpartum BMI kg/m2 909 Lowest quartile: ref 

Highest quartile: OR = 3.34 (1.7 - 6.5) 

Blood pressure, lipid profile*, age, duration of FHxT2DM, working status 

Cho, 200662 Postpartum 

weight 

kg 909 Lowest quartile: ref 

Highest quartile: OR = 3.06 (1.6 - 6) 

Blood pressure, lipid profile*, age, duration of FHxT2DM, working status 

Jang, 200363 Postpartum 

weight 

kg 311 NR Pre-pregnancy weight, gestational age at GD

glucose, 3-hr insulin on diagnostic OGTT, agBMI, FHxT2DM 

Cho, 200662 Postpartum 

body fat weight 

kg 909 Lowest quartile: ref 

Highest quartile: OR = 3.76 (1.8 - 7.6) 

Blood pressure, lipid profile*, age, duration of FHxT2DM, working status 

Cho, 200662 Postpartum 

subscapular skin fold thickness 

mm 909 Lowest quartile: ref 

Highest quartile: OR = 2.82 (1.4 - 5.6) 

Blood pressure, lipid profile*, age, duration of FHxT2DM, working status 

Cho, 200662 Postpartum 

suprailiac skin fold thickness 

mm 909 Lowest quartile: ref 

Highest quartile: OR = 2.1 (1.2 - 3.7) 

Blood pressure, lipid profile*, age, duration of FHxT2DM, working status 
Evidence Table 23. Studies reporting on the association between anthropometric measures and the development of type 2 diab

pregnancy with gestational diabetes (continued) 

F-57 

Author, year Risk factor Units N 

Measure of 

association (95% CI) Covariates include

Cho, 200662 Postpartum 

tricep skin fold thickness 

mm 909 Lowest quartile: ref 

Highest quartile: OR = 2.02 (1.1 - 3.6) 

Blood pressure, lipid profile*, age, duration of FHxT2DM, working status 

Cho, 200662 Postpartum 

waist circumference 

cm 909 Lowest quartile: ref 

Highest quartile: OR = 3.86 (1.8 - 8.2) 

Blood pressure, lipid profile*, age, duration of FHxT2DM, working status 

Cho, 200662 Postpartum 

waist-to-hip ratio 

no units 909 Lowest quartile: ref 

Highest quartile: OR = 3.11 (1.7 - 5.6) 

Blood pressure, lipid profile*, age, duration of FHxT2DM, working status 

Peters, 199672 Postpartum BMI NR 666 NR Additional pregnancy, postpartum weight cha

breastfeeding 

Xiang, 200664 Postpartum BMI kg/m2 526 NR Contraceptive use, breastfeeding, FHxT2DM

triglycerides, weight change during followup 

Xiang, 200664 Postpartum BMI kg/m2 526 NR Interaction term for breastfeeding and OC us

triglycerides, HDL cholesterol, weight change 

Xiang, 200664 Postpartum BMI kg/m2 526 NR Interaction term for OC use and triglyceride le

breastfeeding, HDL cholesterol, weight chang

Dacus, 199465 Postpartum BMI kg/m2 100 <27: ref 

≥27: RR = 4.11 (0.57 - 29.78) 

None 

Peters, 199672 Postpartum 

weight change 

Per 10 lbs 

666 RH = 1.95 (1.64 - 2.33) Additional pregnancy, OGTT glucose area, p

breastfeeding 

Kjos, 199869 Postpartum 

weight loss 

NR 443 NR Contraceptive use, AUC at the initial postpart

method of glucose control, additional pregnan

Xiang, 200664 Weight change 

during followup 

NR 526 NR Interaction term for breastfeeding and OC us

FHxT2DM, triglycerides, HDL cholesterol 

Xiang, 200664 Weight change 

during followup 

NR 526 NR Interaction term for OC use and triglyceride le

FHxT2DM, breastfeeding, HDL cholesterol 

Xiang, 200664 Weight change 

during followup 

NR 526 NR Contraceptive use, postpartum BMI, breastfe

cholesterol, triglycerides 

Jang, 200363 Height NR 311 NR Pre-pregnancy weight, gestational age at GD

glucose, 3-hr insulin on diagnostic OGTT, agFHxT2DM, postpartum weight 

* Includes triglyceride, high density lipoprotein, and low density lipoprotein cholesterol 

AUC = area under the glucose tolerance curve; BMI = body mass index; cm = centimeters; CRP = C-reactive protein; FHxT2DM = family history of t

= fasting plasma glucose; GAD = glutamic acid decarboxylase; GDM = gestational diabetes mellitus; HDL = high density lipoprotein; hr = hour; IA-2 = kilograms; lbs = pounds; m = meters; mm = millimeters; NR = not reported; OC = oral contraceptive; OGTT = oral glucose tolerance test; OR = oddrelative hazard; RR = relative risk; se = standard error 
Evidence Table 24. Studies reporting on the association between oral contraceptive use and the development of type 2 diabete

pregnancy with gestational diabetes 

F-58 

Author, year Risk factor Units N 

Measure of 

association (95% CI) Covariates include

Kjos, 199869 Contraceptive 

use 

Yes/no 443 Combination therapy: ref 

Progestin only: RH = 2.87 (1.57 - 5.27) 

AUC at the initial postpartum OGTT, prior OC control, additional pregnancy, postpartum weuse 

Xiang, 200664 Contraceptive 

use 

Yes/no 526 COC use: ref 

DMPA use: RH = 1.07 (0.61 - 1.89; p = 0.81) 

Postpartum BMI, breastfeeding, FHxT2DM, Htriglycerides, weight change during followup 

Kjos, 199869 Duration of OC 

use 

Months 443 ≤4: RH = 0.72 (0.09 - 5.89) 

4-8: RH = 2.96 (1.35 - 6.52) >8: RH = 4.92 (1.76 - 13.73) 

Contraceptive use, AUC at the initial postpartmethod of glucose control, additional pregnanloss 

Xiang, 200664 Interaction term 

for breastfeeding and OC use 

NR 526 COC without breastfeeding: ref

DMPA w/o breastfeeding: RH = 1.06 (0.58 - 1.95; p = 0.85) DMPA with breastfeeding: RH = 2.21 (0.96 - 5.11; p = 0.06) 

Postpartum BMI, FHxT2DM, triglycerides, HDchange during followup 

Xiang, 200664 Interaction term 

for OC use and triglyceride level 

NR 526 COC & below median 

triglyceride: ref COC & above median triglyceride: RH = 1.39 (0.88 - 2.19; p = 0.16) DMPA & below median triglyceride: RH = 0.55 (0.22 - 1.31; p = 0.2) DMPA & above median triglyceride: RH = 2.28 (1.08 - 4.81; p = 0.03) 

Postpartum BMI, FHxT2DM, breastfeeding, Hchange during followup 

Kjos, 199869 Prior OC use NR 443 NR Contraceptive use, AUC at the initial postpart

glucose control, additional pregnancy, postpa

of OC use 

AUC = area under the glucose tolerance curve; BMI = body mass index; CI = confidence interval; COC = combination oral contraception; DMPA = dacetate; FHxT2DM = family history of type 2 diabetes mellitus; HDL = high density lipoprotein; NR = not reported; OC = oral contraceptive; OGTT ref = reference group; RH = relative hazard 
Evidence Table 25. Studies reporting on the association between metabolic risk factors and the development of type 2 diabetes 

pregnancy with gestational diabetes 

F-59 

Author, year Risk factor Units N 

Measure of 

association (95% CI) Covariates include

Cheung, 200660 Fasting blood 

glucose level 

mmol/L 102 RR = 1.37 (1.08 - 1.72) Dose of bedtime intermediate-acting insulin r

Cheung, 200660 FPG at 

diagnosis 

mmol/L 102 RR = 1.5 (1.3 - 1.9) Age, Parity, BMI at index pregnancy, 2-hr OG

pregnancies, method of glucose control, FHx

Steinhart, 199771 Fasting blood 

sugar 

mmol/L 88 ≤5.83: ref 

>5.83: OR = 11.05 (2.3 - 103.4)

None 

Cho, 200561 FPG at 

diagnosis 

mmol/L 170 ≤5.3: ref 

>5.3: RR = 4.004 (1.405 - 11.409) 

Age, gestational age at GDM diagnosis, pre-pFHxT2DM, homocysteine level 

Schaefer-Graf, 200270

FPG at diagnosis 

mg/dL 1636 Q1: ref 

Q2: OR = 7.82 (1.77 - 34.52) Q3: OR = 11.13 (2.44 - 50.72) Q4: OR = 21.01 (4.58 - 96.29) 

FPG at diagnosis, class A2, area under the gpregnancy OGTT, gestational age at GDM di50-gm GCT 

Kjos, 199568 Highest 

antepartum fasting glucose 

mmol/L 671 Q1: ref 

Q2: RH= 1.39 (0.7 - 2.75) Q3: RH= 2.09 (1.12 - 3.9) Q4: RH= 2.47 (1.25 - 4.9) 

Postpartum OGTT glucose AUC, gestational antepartum OGTT glucose AUC 

Pallardo, 199973 # of abnormal 

OGTT results (including fasting) 

NR 788 OR = 3.03 (1.43 - 6.37; p = 

<0.01) 

Pre-pregnancy BMI, C-peptide glucose score 

Steinhart, 199771 GTT total mmol/L 88 ≤41.63: ref 

>41.63: OR = 15.5 (2 - 678) 

None 

Buchanan, 199974 1-hr plasma glucose, 

diagnostic OGTT 

mmol/L 91 Lowest tertile: ref 

Highest tertile: OR = 15.2 (1.4 - 166.3) 

Beta-cell compensation index, basal glucose 

Buchanan, 199974 1-hr plasma glucose, 

diagnostic OGTT 

mmol/L 91 Lowest tertile: ref 

Highest tertile: OR = 22 (1.5 - 328.5) 

OGTT 30-min incremental insulin:glucose, barate, clamp SI 

Jang, 200363 2-hr glucose mmol/L 311 Coefficient = 0.0156 (se = 

0.0075) 

Pre-pregnancy weight, gestational age at GDon diagnostic OGTT, age, height, pre-pregnapostpartum weight 

Metzger, 199367

2-hr glucose mmol/L 177 OR = 1.03 (p < 0.001) OGTT 30-min stimulated insulin secretion, ba

Cheung, 200660 2-hr OGTT mmol/L 102 RR = 1.3 (1.1 - 1.4) Age, parity, FPG at diagnosis, BMI at index p

pregnancies, method of glucose control, FHx
Evidence Table 25. Studies reporting on the association between metabolic risk factors and the development of type 2 diabetes 

pregnancy with gestational diabetes (continued) 

F-60 

Author, year Risk factor Units N 

Measure of 

association (95% CI) Covariates include

Jang, 200363 3-hr insulin on 

diagnostic OGTT 

Pmol/L 311 OR = 0.98 (0.96-0.99) Pre-pregnancy weight, gestational age at GD

glucose, age, height, pre-pregnancy BMI, FHweight 

Metzger, 199367

3-hr integrated insulin 

pM.min 172 NR (p < 0.01) 3-hr integrated insulin, parity, obesity 

Buchanan, 199875 Antepartum 30 minutes 

incremental plasma insulin/glucose ratio 

NR 122 NR (p = 0.002) Total AUC for diagnostic antepartum 100-gm 

Buchanan, 199974

OGTT 30-min incremental insulin:glucose 

NR 91 lowest tertile: ref 

highest tertile: OR = 0.1 (0.005 - 2.2) 

Incremental glucose area diagnostic OGTT, Fresponse, basal glucose production rate, clam

Buchanan, 199974

OGTT 30-min incremental insulin:glucose 

NR 91 lowest tertile: ref 

highest tertile: OR = 0.08 (0.005 - 1.1) 

1-hr plasma glucose diagnostic OGTT, basal clamp SI 

Kjos, 199568 Antepartum 

OGTT glucose AUC (mmol per min/l) 

mmol/l. min. -1 

671 Q1: ref 

Q2: RH = 1.13 (0.58 - 2.22) Q3: RH = 1.42 (0.77 - 2.62) Q4: RH = 2.13 (1.18 - 3.85) p = 0.004 

Postpartum OGTT glucose AUC, gestational highest antepartum fasting glucose 

Schaefer-Graf, 200270

Area under the glucose curve of pregnancy OGTT 

g.min/dL 1636 Q1: ref 

Q2: OR = 0.93 (0.41 - 2.13) Q3: OR = 1.47 (0.73 - 2.99) Q4: OR = 3.64 (1.93 - 6.84) 

FPG at diagnosis, class A2, gestational age aprevious GDM, 50-gm GCT 

Buchanan, 199875

Total AUC for diagnostic antepartum 100-gm OGTT glucose 

NR 122 NR (p = 0.003) Antepartum 30 minutes incremental plasma i

Buchanan, 199974

Incremental glucose area, diagnostic OGTT 

min/mol/L 91 lowest tertile: ref 

highest tertile: OR = 15 (1.1 - 207.9) 

FSIGT acute insulin response, OGTT 30-min insulin:glucose, basal glucose production rate

Peters, 199672 OGTT glucose 

area 

NR 666 NR Additional pregnancy, postpartum weight cha

breastfeeding 
Evidence Table 25. Studies reporting on the association between metabolic risk factors and the development of type 2 diabetes 

pregnancy with gestational diabetes (continued) 

F-61 

Author, year Risk factor Units N 

Measure of 

association (95% CI) Covariates include

Kjos, 199869 AUC at the initial 

postpartum OGTT 

NR 443 NR Contraceptive use, prior OC use, method of g

pregnancy, postpartum weight loss, duration 

Kjos, 199568 Postpartum 

OGTT glucose AUC 

mmol/l. min. -1 

671 Q1: ref 

Q2: RH = 2.67 (1 - 7.25) Q3: RH = 5.53 (2.16 - 14.16) Q4: RH = 11.48 (4.52 - 29.14) p < 0.0001 

Gestational age at GDM diagnosis, antepartuhighest antepartum fasting glucose 

Buchanan, 199974 Basal glucose production rate mmol.min .m2 91 Lowest tertile: ref Highest tertile: OR = 7 Incremental glucose area, diagnostic OGTT, 

response, OGTT 30-min incremental insulin:g

Buchanan, 199974 Basal glucose production rate mmol.min .m2 91 Lowest tertile: ref Highest tertile: OR = 5.3 (0.63 - 

44.4) 

1-hr plasma glucose diagnostic OGTT, beta-c

Buchanan, 199974 Basal glucose production rate mmol.min .m2 91 Lowest tertile: ref Highest tertile: OR = 6.8 (0.7 - 

65.5) 

1-hr plasma glucose diagnostic OGTT, OGTT insulin:glucose, clamp SI 

Buchanan, 199974

Beta-cell compensation index 

NR 91 Lowest tertile: ref 

Highest tertile: OR = 0.09 (0.009 - 0.09) 

1-hr plasma glucose diagnostic OGTT, basal 

Buchanan, 199974 Clamp SI mmol.min .m2/micr

oU/ml*1000 

91 Lowest tertile: ref 

Highest tertile: OR = 0.18 (0.03 - 1.2) 

1-hr plasma glucose diagnostic OGTT, OGTT insulin:glucose, basal glucose production rate 

Buchanan, 199974 Clamp SI mmol.min .m2/micr

o U/ml*1000 

91 Lowest tertile: ref 

Highest tertile: OR = 0.15 (0.02 - 1.2) 

Incremental glucose area, diagnostic OGTT, response, OGTT 30-min incremental insulin:gproduction rate 

Buchanan, 199974

FSIGT acute insulin response 

mmol/l.min 

91 Lowest tertile: ref 

Highest tertile: OR = 0.08 (0.005 - 1) 

Incremental glucose area, diagnostic OGTT, insulin:glucose, basal glucose production rate

Pallardo, 199973 C-peptide 

glucose score 

mmol/L 788 OR = 0.46 (0.25 - 0.85; 

p < 0.05) 

Pre-pregnancy BMI, # of abnormal OGTT res

Xiang, 200664 HDL cholesterol mg/dL 526 NR Contraceptive use, postpartum BMI, breastfe

triglycerides, weight change during followup 
Evidence Table 25. Studies reporting on the association between metabolic risk factors and the development of type 2 diabetes 

pregnancy with gestational diabetes (continued) 

F-62 

Author, year Risk factor Units N 

Measure of 

association (95% CI) Covariates include

Cho, 200662 Blood pressure NR 909 NR Cho reported 8 models, which adjusted for bl

profile*, age, duration of followup, parity, FHxand one of the following measures of adiposiwaist circumference, weight, subscapular skiskin fold thickness, tricep skin fold thickness, waist-to-hip ratio. The relative measure for breported in any of the models. 

Xiang, 200664 HDL cholesterol mg/dL 526 NR Interaction term for breastfeeding and OC us

FHxT2DM, triglycerides, weight change durin

Xiang, 200664 HDL cholesterol mg/dL 526 NR Interaction term for OC use and triglyceride le

FHxT2DM, breastfeeding, weight change dur

Xiang, 200664 Triglycerides mg/dL 526 NR Contraceptive use, postpartum BMI, breastfe

cholesterol, weight change during followup 

Xiang, 200664 Triglycerides mg/dL 526 NR Interaction term for breastfeeding and OC us

FHxT2DM, HDL cholesterol, weight change d

Cho, 200662 Lipid profile 

which includes triglycerides, HDL and LDL cholesterol 

NR 909 NR Cho reported 8 models, which adjusted for bl

profile*, age, duration of followup, parity, FHxand one of the following measures of adiposiwaist circumference, weight, subscapular skiskin fold thickness, tricep skin fold thickness, waist-to-hip ratio. The relative measure for threported in any of the models. 

Cho, 200561 Homocysteine 

level at baseline 6 weeks postpartum 

mmol 170 ≤6.38: ref 

>6.38: RR = 3.555 (1.059 - 11.934) 

Age, gestational age at GDM diagnosis, pre-pFHxT2DM, FPG at diagnosis 

Lobner, 200666 GAD and IA-2 

antibody status 

NR 302 both GAD and IA-2 antibody 

negative: ref GAD or IA-2 antibody positive: RH = 4.1 (2.6 - 6.7; p < 0.0001)

Method of glucose control, BMI at first pregnaserum CRP 

Metzger, 199367

Basal insulin NR 177 OR = 0.19 (p < 0.0001) 2-hr glucose, OGTT 30-min stimulated insulin 

Metzger, 199367

OGTT 30-min stimulated insulin secretion 

NR 177 OR = 0.07 (p = 0.07) 2-hr glucose, basal insulin 
Evidence Table 25. Studies reporting on the association between metabolic risk factors and the development of type 2 diabetes 

pregnancy with gestational diabetes (continued) 

F-63 

Author, year Risk factor Units N 

Measure of 

association (95% CI) Covariates include

Lobner, 200666 Serum CRP mg/L 302 ≤0.8: ref 

>0.8: RH = 1.2 (0.7 - 2.2; p = 0.47) 

GAD and IA-2 antibody status, method of glupregnancy visit, parity, age 

AUC = area under the glucose tolerance curve; BMI = body mass index; CI = confidence interval; class A2 = insulin-requiring gestational diabetics; CdL = deciliter; FHxT2DM = family history of type 2 diabetes mellitus; FPG = fasting plasma glucose; FSIGT = frequently sampled intravenous gluco

glutamic acid decarboxylase; GDM = gestational diabetes mellitus; gm = grams; GTT = glucose tolerance test; HDL = high density lipoprotein; hr = h

min = minutes; mg = milligram; mmol = millimole; NR = not reported; OC = oral contraceptive; OGTT = oral glucose tolerance test; OR = odds ratioquartile; RH = relative hazard; RR = relative risk; se = standard error; SI = sensitivity index 
Evidence Table 26. Grading of the body of evidence on the association of risk factors with the development of type 2 diabetes f

with gestational diabetes (KQ3) 

F-64 

Family history 

type 2 

diabetes 

Sociodemographics Maternal lifestyle Par

Quantity of Evidence:Number of studies 

5 6 0 4 

Total number of patients studied 2018 1894 0 14Quality and Consistency of Evidence:

Were the study designs mostly high quality (e.g., cohort study or 

case-control study with multivariate adjustment for most or all major potential confounding factors), medium quality (e.g., cohort study or 

case-control study with adjustment for only a few major potential confounding factors), or low quality (e.g., no multivariate adjustment 

for confounding factors)? 

low medium hig

Did the studies have other serious (-1) or very serious (-2) limitations in quality? (Enter 0 if none) 

0 0 0 

Did the studies have important inconsistency? (-1) 0 -1 0 Was there some (-1) or major (-2) uncertainty about the directness (i.e. extent to which the people, risk factors, and outcomes are similar to those of interest)? 

0 0 0 

Were data imprecise or sparse? (-1) (i.e. lack of data or very wide confidence intervals that may change conclusions) 

-1 -1 -1 

Did the studies have high probability of reporting bias? (-1) 0 0 0 Did the studies show strong evidence of association between the risk factors and outcome? (“strong” if significant relative risk or odds ratio > 2 based on consistent evidence from 2 or more studies with no plausible confounders (+1); “very strong” if significant relative risk or odds ratio > 5 based on direct evidence with no major threats to validity (+2))- use your clinical judgment for absolute differences.

-1 -1 0 

Did the studies have evidence of a dose-response gradient? (+1) 0 0 +Did the studies have unmeasured plausible confounders that most likely reduced the magnitude of the observed association? (+1) 

0 +1 0 

Overall grade of evidence (high, moderate, low, very low) very low low very low lo

High = further research is very unlikely to change our confidence in the estimates; moderate = further research is likely to have an important impact on estimate of effect and may change the estimate; low = further research is likely to have an important impact on our confidence in the estimate of effect 

estimate; very low = any estimate of effect is very uncertain. 
Evidence Table 26. Grading of the body of evidence on the association of risk factors with the development of type 2 diabetes f

with gestational diabetes (KQ3) (continued) 

F-65 

Postpartum 

factors 

Measures of 

anthropometry Oral contracept

use 

Quantity of Evidence:Number of studies 

5 11 2 

Total number of patients studied 2632 4489 969 Quality and Consistency of Evidence:

Were the study designs mostly high quality (e.g., cohort study or 

case-control study with multivariate adjustment for most or all major potential confounding factors), medium quality (e.g., cohort study or 

case-control study with adjustment for only a few major potential confounding factors), or low quality (e.g., no multivariate adjustment 

for confounding factors)? 

medium medium Medium 

Did the studies have other serious (-1) or very serious (-2) limitations in quality? (Enter 0 if none) 

0 0 0 

Did the studies have important inconsistency? (-1) -1 0 -1 Was there some (-1) or major (-2) uncertainty about the directness (i.e. extent to which the people, risk factors, and outcomes are similar to those of interest)? 

0 0 0 

Were data imprecise or sparse? (-1) (i.e. lack of data or very wide confidence intervals that may change conclusions) 

-1 0 0 

Did the studies have high probability of reporting bias? (-1) 0 0 0 Did the studies show strong evidence of association between the risk factors and outcome? (“strong” if significant relative risk or odds ratio > 2 based on consistent evidence from 2 or more studies with no plausible confounders (+1); “very strong” if significant relative risk or odds ratio > 5 based on direct evidence with no major threats to validity (+2))- use your clinical judgment for absolute differences.

0 +1 0 

Did the studies have evidence of a dose-response gradient? (+1) 0 0 0 Did the studies have unmeasured plausible confounders that most likely reduced the magnitude of the observed association? (+1) 

+1 0 0 

Overall grade of evidence (high, moderate, low, very low) very low moderate low 

High = further research is very unlikely to change our confidence in the estimates; moderate = further research is likely to have an important impact on estimate of effect and may change the estimate; low = further research is likely to have an important impact on our confidence in the estimate of effect 

estimate; very low = any estimate of effect is very uncertain. 
Evidence Table 27. Characteristics of studies evaluating the performance characteristics of tests for diagnosing type 2 diabete

with gestational diabetes 

F-66 

Author, year 

Country 

Study 

design 

Exclusion 

criteria 

Time since 

delivery 

Mean age (in 

years) (Age 

range) Race, n (%) 

Weight (in 

kg) / BMI (in 

kg/m2), mean 

Reference 

test*

Co

Agarwal, 200495

United Arab Emigrates 

Retrospective NR (range: 4-8 

weeks) 

32 Arab: (78.8) 

Indian Nationals: (20.5) 

NR A, B C 

Conway, 199997

US 

Prospective NR Median: 6-

weeks (range: 4-13 weeks) 

NR NR NR A B 

Costa, 2000100Spain 

Prospective NR (range: 2-12 

months) 

ND: 33.9 IGT or T2DM: 36 

C: 120 (100) Postpregnancy 

BMI: ND: 25.1 IGT or T2DM: 28.5 

A C 

Cypryk, 200498

Poland 

Retrospective Known 

T1DM and T2DM (23%) since delivery 

Mean: 3.1 years (range 0.5-8 years) 

34.3 C: (100) NR A C 

Holt, 200396United Kingdom 

Retrospective NR 6 weeks 31.1 (18.7 – 

38.9) 

C: (86) Asian: (14) 

NR A C 

Kousta, 1999101United Kingdom 

Prospective Known 

T2DM (14%) since delivery 

Median: 28 months (range: 1-86 months) 

36.6 European: 68 

(35) Asian: 56 (29) AfroCaribbean: 32 (17) Other: 36 (19) 

Prepregnancy BMI: 28.1 

A B, C 

Reichelt, 200299

Brazil 

Prospective NR Mean: 5.7 

years (range 4-8 years) 

NR NR NR B C 
Evidence Table 27. Characteristics of studies evaluating the performance characteristics of tests for diagnosing type 2 diabete

with gestational diabetes (continued) 

F-67 

Author, year 

Country 

Study 

design 

Exclusion 

criteria 

Time since 

delivery 

Mean age (in 

years) (Age 

range) Race, n (%) 

Weight (in 

kg) / BMI (in 

kg/m2), mean 

Reference 

test*

Co

Reinblatt, 200694

Canada 

Retrospective NR (range: 6 

weeks-6 months) 

32 (15-45) NR Prepregnancy 

BMI: 25.6 

B C 

* A= FBG > 7.8 mmol/L (140 mg/dL) or 2-hr plasma glucose after 75-gm OGTT > 11.1 mmol/L (200 mg/dL); B = FBG > 7.0 mmol/L (126 mg/dL) o75-gm OGTT > 11.1 mmol/L (200 mg/dL); C = FBG > 7.0 mmol/L (126 mg/dL) Asian = Asian or Asian American; BMI = body mass index; C = Caucasian; dL = deciliter; FBG = fasting blood glucose; gm = gram; hr = hour; IGT = kg = kilogram; L = liter; m = meter; mg = milligram; mmol = millimole; ND = nondiabetic; NR = not reported; OGTT = oral glucose tolerance test; Utype 1 diabetes mellitus; T2DM = type 2 diabetes mellitus 
Evidence Table 28. Performance characteristics of tests for diagnosing type 2 diabetes following a pregnancy with gestational 

F-68 

Author, year 

True 

positive 

False 

positive 

False 

negative 

True 

negative Total 

Sensitivity 

(%) 95% CI 

Specifici

(%) 

Comparison 1: Reference test: FBG > 7.8 mmol/L (140 mg/dL) or 2-hr plasma glucose after 75-gm OGTT > 11.1 mmol/L (200 mg/dL) Comparison test: FBG > 7.0 mmol/L (126 mg/dL) or 2-hr plasma glucose after 75-gm OGTT > 11.1 mmol/L (200 mg/dL) Conway, 1999 97 11 3 0 165 179 100* n/a 98 Kousta, 1999101 22 3 0 140 165 100* n/a 98 

Comparison 2: Reference test: FBG > 7.0 mmol/L (126 mg/dL) or 2-hr plasma glucose after 75-gm OGTT > 11.1 mmol/L (200 mg/dL) Comparison test: FBG > 7.0 mmol/L (126 mg/dL) 

Reinblatt, 200694 12 0 14 249 275 46 27, 66 100* Agarwal, 200495 36 0 14 499 549 72 58, 84 100* Reichelt, 200299 8 0 1 108 117 89 52, 100 100* Comparison 3: Reference test: FBG > 7.8 mmol/l (140 mg/dL) or 2-hr plasma glucose after 75-gm OGTT > 11.1 mmol/l (200 mg/dL) 

Comparison test: FBG > 7.0 mmol/l (126 mg/dL) 

Agarwal, 200495 31 5 14 499 549 69 53, 82 99 Cypryk, 200498 1 2 6 139 148 14 0.04, 58 99 

Holt, 200396 3 7 0 112 122 100 29, 100 94 

Costa, 2000100 2 1 0 117 120 100 16, 100 99 

Kousta, 1999101 16 3 6 140 165 73 50, 89 98 

* Fixed at 100% by definition of test criteria. CI = confidence interval; dL = deciliter; FBG = fasting blood glucose; gm = gram; hr = hour; L = liter; mg = milligram; mmol = millimole; n/a = not a

glucose tolerance test 
Evidence Table 29. Quality of studies evaluating the performance characteristics of tests for diagnosing type 2 diabetes follow

gestational diabetes

F-69 

Author, year Data collection Patient selection Loss to followup Disease spectrum 

Report of test 

reproducibility 

Agarwal, 200495 Retrospective Consecutive 67% Clinical population Laboratory metho

reported

Conway, 199997 Retrospective Consecutive 82% Clinical population Laboratory metho

reported

Costa, 2000100 Prospective NR NR Clinical population Laboratory metho

reported

Cypryk, 200498 Prospective Consecutive 33% Clinical population 

Excluded T1/2 DM diagnosed after delivery (23%) 

NR 

Holt, 200396 Retrospective Consecutive 20% Clinical population Yes Kousta, 1999101 Prospective Consecutive NR Clinical population 

Excluded T2DM diagnosed after delivery (14%) 

Laboratory methoreported

Reichelt, 200299 Prospective Consecutive 26% Clinical population NR Reinblatt, 200694 Retrospective Consecutive 79% Clinical population NR NR = not reported; T1DM = type 1 diabetes mellitus; T2DM = type 2 diabetes mellitus 
Evidence Table 30. Grading of the body of evidence of the performance characteristics of tests for diagnosing type 2 diabetes 

with gestational diabetes (KQ4) 

F-70 

Comparison 1* Comparison 2† 

Quantity of evidence:

Number of studies 

2 3 

Total number of patients studied 344 941 Quality and consistency of evidence:

Were the study designs mostly high quality (e.g., prospective, independent 

comparison of a test to a reference test), medium quality (e.g., retrospective, independent comparison of a test to a reference test), or low quality (e.g., no 

independent comparison)? 

Medium Medium 

Did the studies have other serious (-1) or very serious (-2) limitations in quality? (Enter 0 if none) 

-1 -1 

Did the studies have important inconsistency? (-1) 0 -1 Was there some (-1) or major (-2) uncertainty about the directness (i.e. extent to which the people, tests and outcomes are similar to those of interest)? 

0 0 

Were data imprecise or sparse? (-1) (i.e. lack of data or very wide confidence intervals that may change conclusions) 

-1 -1 

Did the studies have high probability of reporting bias? (-1) 0 0 Overall grade of evidence (high, moderate, low, very low) Very low Very low 

High = further research is very unlikely to change our confidence in the estimates; moderate = further research is likely to have an important impact on estimate of effect and may change the estimate; low = further research is likely to have an important impact on our confidence in the estimate of effect 

estimate; very low = any estimate of effect is very uncertain. *Comparison 1: Reference test: Fasting blood glucose > 7.8 mmol/L (140 mg/dL) or 2-hr plasma glucose after 75 gm OGTT > 11.1 mmol/L (200 mg/Comparison test: Fasting blood glucose > 7.0 mmol/L (126 mg/dL) or 2-hr plasma glucose after 75 gm OGTT > 11.1 mmol/L (200 mg/dL) † Comparison 2: Reference test: Fasting blood glucose > 7.0 mmol/L (126 mg/dL) or 2-hr plasma glucose after 75 gm OGTT > 11.1 mmol/L (200 mgComparison test: Fasting blood glucose > 7.0 mmol/L (126 mg/dL)‡ Comparison 3: Reference test: Fasting blood glucose > 7.8 mmol/l (140 mg/dL) or 2-hr plasma glucose after 75 gm OGTT > 11.1 mmol/l (200 mg/dComparison test: Fasting blood glucose > 7.0 mmol/l (126 mg/dL)