Observational Study of Patient Important Outcomes in Pregnant Patients With Type 1 Diabetes Mellitus on Insulin Pump
Conditions: Type 1 Diabetes Mellitus, Pregnancy in Diabetics
Sponsor: Sansum Diabetes Research Institute

Minimal Risk Protocol Template [IRB 10429.010] 
 
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IRB Minimal Risk Protocol Template  
 
General Study Information 
 
Principal Investigators:  Yogish Kudva – Mayo Clinic, Carol Levy – Mt. Sinai, Jordan Pinsker – Sansum 
Diabetes Research Institute, and Eyal Dassau – Harvard John A Paulson School of Engineering and Applied 
Sciences 
 
Study Title: Observational study of patient important outcomes in pregnant patients with type 1 diabetes 
mellitus on Insulin pump  
 
Protocol version number and date: V3, JUN 18, 2019.  
 
Research Question and Aims 
 
Hypothesis: We anticipate that when compared to subjects using an Artificial pancreas system(AP) as part of a 
future protocol, this comparator group of subjects undergoing usual care will exhibit less time in target 
Continuous glucose monitoring (CGM) glucose range defined as 63-140 mg/dL and an increased duration of 
hypoglycemia with CGM glucose <63 mg/dL.  
 
Aims, purpose, or objectives: The overall goal of this study is to serve as a comparator group to a group of 
patients that will be managed with AP for varying periods of time during pregnancy.  We will enroll this cohort 
and follow them prospectively throughout the pregnancy and into the post-partum period.  Data collected will 
include   records of continuous glucose monitoring (CGM) based glucose, insulin delivery, self-monitoring of 
blood glucose (SMBG), and maternal and fetal outcomes from pregnant women with type 1 diabetes. These 
data will be used to: (1) develop and refine algorithms for an AP system tailored to the needs of pregnant 
Note: If this study establishes a human specimen repository (biobank) for research 
purposes, do not use this template. Use the Mayo Clinic Human Specimen Repository 
Protocol Template found on the IRB home page under Forms and Procedures at 
http://intranet.mayo.edu/charlie/irb/ 
 
First-time Use: Use this template to describe your study for a new IRB submission. 
1. Complete the questions that apply to your study. 
2. Save an electronic copy of this protocol for future revisions.    
3. When completing your IRBe application, you will be asked to upload this document to the protocol 
section. 
Modification:  To modify this document after your study has been approved: 
1. Open your study in IRBe. Click on the study ‘Documents’ tab and select the most recent version of the 
protocol. Save it to your files. 
2. Open the saved document and activate “Track Changes”.  
3. Revise the protocol template to reflect the modification points , save the template to your files 
4. Create an IRBe Modification for the study and upload the revised protocol template. 

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women with type 1 diabetes, and (2) to serve as a comparator group for concurrent AP protocols (3)  describe 
Dexcom G6 CGM data throughout the pregnancy and (4) describe insulin changes which occur in pregnancy.   
 
Background (Include relevant experience, gaps in current knowledge, preliminary data, etc.):   
Pregnancy in patients with type 1 diabetes (T1D) continues to be associated with mortality, preeclampsia, 
hypertension, and premature labor, all linked to hyperglycemia throughout gestation. Pregestational and 
gestational elevations of hemoglobin A1c (HbA1c) (a standard measure of glucose control in people with 
diabetes) and gestational time in target glucose range, time in hyperglycemia, and perhaps incidence of severe 
hypoglycemia have been associated with poorer outcomes. To reduce the risk of poor maternal and fetal 
outcomes, more stringent glucose targets for pregnant T1D women are recommended; however the quest to 
reduce hyperglycemia results in a significantly higher risk of hypoglycemia [1]. The greatest risk for both 
hyperglycemia and hypoglycemia often occurs overnight when patients are least able to make insulin dose 
adjustments. To optimize outcomes for women with T1D, more knowledge regarding CGM based glucose 
variability during the pregnancy and the changes in insulin requirements and sensitivity throughout pregnancy 
are needed.  This information would facilitate the development of an automated insulin delivery system tailored 
to the specific needs of this population.   
Pregnancy is characterized by complex hormonal and metabolic changes. The first trimester of pregnancy is a 
time when women are the most insulin sensitive and hypoglycemia can be problematic for women with diabetes  
[2, 3]; whereas by late pregnancy, insulin resistance  develops and requires an increase of 200-250% in insulin 
secretion in women without diabetes [2, 4]. This increased insulin requirement in pregnant women with T1D 
makes it very challenging to maintain euglycemia, which is necessary to promote the health of both the mother 
and the developing fetus.  
Sansum Diabetes Research Institute (SDRI) was the only US clinical site for the recent landmark CONCEPTT 
trial which revealed the benefit of CGM use on pregnancy outcomes and modest improvement in HbA1c. The 
CONCEPTT study revealed benefits of CGM use in pregnant women with T1D, demonstrating that in the 
setting of comparable overall good glucose control reflected by HbA1c level (mean HbA1c 6.35% in CGM 
group vs 6.53% in non-CGM group; p=0.0207), pregnant CGM users spent more time in target (68% vs 61%; 
p=0.0034) and less time hyperglycemic (27% vs 32%; p=0.0279) than did pregnant control participants, with 
comparable severe hypoglycemia episodes (18 CGM and 21 control) and time spent hypoglycemic (3% vs 4%; 
p=0.10) [6]. Fewer fetal adverse outcomes were reported for subjects wearing CGM [6]. CGM wear in this 
study was reported at 70% using the Medtronic Guardian sensor which requires calibration 2-4 times each day, 
is inaccurate in the setting of acetaminophen use, and must be replaced every 6 days. The Dexcom G6 CGM 
which provides high accuracy, mean absolute relative difference (MARD) <10 %, factory calibration, ten-day 
wear, and no acetaminophen interference should be particularly advantageous in the pregnant population.  
There have been three hybrid AP studies published from European investigators showing safety and efficacy in 
pregnant women with T1D. The first study by Murphy et al. in 2011 conducted closed loop studies for 24 hours 
in an inpatient clinical research center in 10 pregnant women with T1D at 14.8 and 28 weeks of pregnancy [7]. 
The system required data entry by an RN every 15 minutes into a laptop computer that stored the algorithm. 
Overnight time in range was 84% and 100% (63-140 mg/dL) in the early and late gestation groups, respectively, 
with no hypoglycemia. Two follow up studies [8, 9] utilized a Sooil insulin pump and freestyle Navigator II 

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CGM. Neither of these off the shelf devices is available in the United States. Subjects (16 in each study) were 
studied in a randomized crossover fashion and served as their own controls. Subjects wore the system for 4 
weeks overnight (Stewart et al., 2016) or wore the system day and night (Stewart et al., 2018). Results of these 
studies revealed the safety of the system in the home setting with fewer episodes of hypoglycemia and increased 
overnight time in the target glucose range of 63-140 mg/dL. In the overnight study, time in range (74.7 vs. 
59.5% [95% CI 6.1 to 24.2]; P = 0.002) and mean glucose (119 vs. 133 mg/dL, P = 0.009) were significantly 
better. Time above goal was significantly reduced (>140 mg/dL: 24% vs 38.6%, P= 0.005; >180 mg/dL 7.4% vs 
15.7%, P=0.004). In the day and night study, there were significantly fewer hypoglycemic episodes (median 
[range] 8 [1–17] vs. 12.5 [1–53] over 28 days; P =0.04) and time below goal was less (<63 mg/dL: 1.6 vs. 2.7%; 
P = 0.02; <50-mg/dL: 0.24 vs. 0.47%; P = 0.03). The time in range overall for the latter study was comparable 
between groups, but there was a trend toward higher overnight time in target (67.7 vs. 60.6%; P = 0.06). 
Maternal glycemia, however, was variable. Five (31%) of the study participants spent less time in target range 
and had higher mean glucose levels during AP therapy. These data support the importance of studying AP 
systems further in pregnant women with T1D. We will study several outcomes prospectively in this study 
including insulin delivery, CGM glucose specifically Dexcom G6 based glucose and maternal/fetal outcomes 
We will also evaluate the accuracy of the G6 based system with glucose meter testing at specific time points 
throughout the pregnancy.   
Preliminary Data:   
At the Mayo Clinic, Rochester during the years 2009-2013, 52 pregnant patients with T1D were seen with 32 
(62%) using insulin pumps and none using sensor augmented insulin pumps (unpublished data). More recently, 
from 2013-2018, 60 pregnant patients with T1D were seen at Mount Sinai Hospital with 48 (80%) using insulin 
pumps and 34 (57%) using sensors. SDRI regularly provides care for 10 pregnant women with T1D per year 
who use these devices and was the only US clinical site for the recent landmark CONCEPTT trial.   
 The research teams at Barbara Davis Center and Joslin Clinic have studied CGM use   in T1D pregnancies [10, 
11].   
Twenty-five pregnancies occurring between 2012-2017 in 22 patients seen at Mount Sinai Hospital and Mayo 
Clinic have been retrospectively reviewed (see figures). Pump settings at the initial visit and at designated 2-
week intervals each trimester were analyzed. Compared to the initial visit, basal infusion rates overnight and in 
the morning decreased during the 1st trimester and rose in the 2nd and 3rd trimesters.  Midday and evening 
infusion rates peaked during the late 2nd trimester to early 3rd trimester before plateauing during the last month 
of pregnancy. Carbohydrate ratios became more aggressive after week 12 with the earliest change in settings 
seen at breakfast. By the end of pregnancy, carbohydrate ratios had decreased by an average of 45%. Insulin 
sensitivity factors became more aggressive starting in the late 2nd trimester resulting in a 20% change from 
baseline by the end of pregnancy [5]. 
 
 
 
 
 
 

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Summary:  Understanding the hormonal and metabolic complexity as well as the subsequent requirements of 
adaptive insulin management over the entire gestation period in T1D will enable us to develop mathematical 
models that will describe the fluctuating glucose-insulin interactions during pregnancy. A multicenter database 
including CGM and insulin settings/bolus information from pregnant women during the gestation period will be 
collected to: 1) to serve as a comparator group for analysis of future AP studies data, 2) to further examine the 
glycemic variability and insulin management requirements throughout pregnancy to refine our AP algorithms, 
3) to provide additional information on CGM use in pregnant women in comparison to fingerstick data utility, 
patient acceptance, and pregnancy outcomes.  
 
 
Study Design and Methods 
 
Methods:  Describe, in detail, the research activities that will be conducted under this protocol:   
All pregnant women with T1D at up to five sites on insulin pumps (CSII/SAP/PLGS) will be offered enrollment 
in a prospective study that will capture: 1) Dexcom G6 CGM data, 2) self-monitoring of blood glucose 
(SMBG), 3) insulin pump settings, 4) insulin delivery records, and 5) maternal and fetal outcomes.  
 
Outpatient Screening and Enrollment:  
Participants will be offered enrollment any time from pregnancy confirmation to 16 weeks and 6 days of 
gestational age. Participants will provide informed consent and will sign IRB-approved consent forms after 
eligibility has been confirmed based on pre-consent screening inclusion and exclusion criteria.  
 
The study physician will perform a detailed history and physical with special emphasis on diabetes history. We 
will record participants’ body weight, height, body mass index (BMI), average total daily insulin use (calculated 
over 1 week), insulin: carbohydrate ratio, correction factor (insulin sensitivity factor), insulin infusion basal rate 
profile, and HbA1c as a marker of overall glycemic control. Data from insulin pump and blood glucose meters 
will be downloaded using appropriate software and archived using an electronic process to avoid data recording 
errors.  
 
We will obtain routine vital signs and draw blood for screening labs, including HbA1c, hematocrit, AST, 
creatinine and TSH. Since all these subjects will be pregnant, these tests may be available close to recruitment. 
If so, those tests will be used, and unnecessary testing will be avoided. HbA1c measured within one month +/- 1 
week of screening and other tests within 3 months +/- 2 weeks of screening will be accepted. If the study 
physician feels it is necessary, a c-peptide lab (with simultaneous glucose for c-peptide validation) can also be 
conducted at screening to confirm a type 1 diabetes diagnosis. This study is not meant to find out if the 
participant has any other disease or problem. The study leaders will alert the participant if any of the research 
results are important to her health during the study. The participant may have a copy of the screening tests to 
discuss with her personal physician. 
 
Participants will be provided a study glucometer and supplies. They will be trained on the use of the meter 
including to perform fingersticks on clean, dry hands and to use only finger sticks for glucose assessments. 
Participants will be required to perform SMBG 8 times a day (before meals, after meals, at bedtime and 
overnight between 2-4 am) on one day during every  four week interval of their pregnancy.    Subjects will be 

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supplied tests strips and permitted to perform additional fingersticks for testing as they desire as is standard of 
care for pregnant women with T1D. 
 
Participants will be provided a study Dexcom G6 glucose sensor and supplies. They will be trained on proper 
insertion, calibration, and maintenance of the CGM sensor. Training will be tailored to their individual 
experiences (no prior CGM use, prior CGM use on different sensor).   G6 can be calibrated or used with factory 
calibration with the choice being made at the start of each probe insertion by the subjects. This information will 
be captured.  
 
Follow up visits:   
Research staff will contact patients 1 day and 1 week after G6 initiation visit and thereafter every 14±4 days. 
These contacts can occur at participants’ regularly scheduled follow up visits with maternal fetal medicine or at 
visits for diabetes management or over the phone. The number of follow up visits will depend on the week of 
pregnancy of the participant at enrollment. 
 
During these contacts, study CGM and blood glucose meters will be downloaded (either in person or remotely) 
to have data from every week of pregnancy. Concerns regarding subjects’ glycemic control will be conveyed to 
their provider for appropriate insulin titration.  
 
Personal insulin pumps will be downloaded whenever CGM data are downloaded and whenever settings are 
changed (either in person or remotely). Pregnancy complications will be recorded. At clinic visits, CGM sites 
will be inspected.  We will also collect self-reported food diary and activity log at least 2 times per pregnancy 
within 2 weeks ± 1 week of  enrollment and at 30 weeks ±2 weeks  to  assess  amount of carbohydrates 
consumed  per day to see if  the quantity changes during pregnancy.  In addition, food and activity logs will be 
collected if available. 
 
 
Study personnel will be available at all times throughout the trial to answer any question or troubleshoot any 
sensor problem.  
 
Postpartum visit: After delivery, the participants will return study devices at or around the time of their routine 
post-partum follow up visit. Medical records including method of delivery, gestational age at delivery, neonatal 
intensive care unit (NICU) admissions, neonatal hypoglycemia, fetal weight, and length of hospital stay will be 
reviewed. The infant’s medical record will also be accessed to retrieve post-delivery medical information. 
Subjects will also be asked if they were given any medications such as steroids that are known to cause insulin 
resistance which would impact blood glucose control.  Subjects will be asked to complete the CGM-SAT 
survey (a survey assessing satisfaction with the glucose sensor) at this visit[12].    
 
Data analysis:  
Data from the 3 sites will be de-identified and collected in a central HIPPA compliant data repository.  
 
Patterns of insulin and glucose control (including time in range 60-140 mg/dL, frequency of severe 
hypoglycemic events, time spent above target range, time spent in hypoglycemic range, episodes of clinically 
significant hyperglycemia with CGM >180 mg/dL, episodes of ketoacidosis requiring emergency room or 
hospital admission) will be analyzed and association with outcomes calculated.  

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Maternal and fetal outcomes include gestational age at delivery, birthweight of baby, fetal malformations, 
incidence of macrosomia [13], preterm birth, neonatal hypoglycemia (requiring IV dextrose), neonatal NICU 
stay, method of delivery, adverse events associated with delivery including shoulder dystocia, and maternal 
complications including preeclampsia and polyhydramnios.  
 
CGM data will be compared to time-matched SMBG data in the pregnant population.  
 
Dr. Walter Kremers from mayo Clinic Rochester is the Program Statistician and will be involved in the 
analyses.  
 
Resources:  Describe the available resources to conduct the research (personnel, time, facilities, mentor 
commitment, etc.):  
 
  (1a) This is a multisite study involving Mayo Clinic and non Mayo Clinic sites. When checked, describe in 
detail the research procedures or activities that will be conducted by Mayo Clinic study staff. 
Mayo Clinic staff will perform the activities described above for 10 participants. The other sites will conduct 
the same activities on their participants. Mayo Clinic staff will also collect de-identified data from all sites for 
analysis.  
 
  (1b) Mayo Clinic study staff will be engaged in research activity at a non Mayo Clinic site.  When checked, 
provide a detailed description of the activity that will be conducted by Mayo Clinic study staff. 
 
 
Subject Information 
 
Target accrual is the proposed total number of subjects to be included in this study at Mayo Clinic. A “Subject” 
may include medical records, images, or specimens generated at Mayo Clinic and/or received from external 
sources.    
 
Target accrual: 300   subjects across 3-5 sites.  We plan to enroll  60 patients each at Mount Sinai New York, 
Mayo Clinic Rochester, Sansum Diabetes Research Center, Santa Barbara, CA.  In addition, we hope to extend 
the study to sites such as the Barbara Davis Center, Denver, Colorado and Joslin Clinic, Boston, MA.   
 
Subject population (children, adults, groups): Pregnant women 18 years of age or older with T1D 
 
Inclusion Criteria:  
• 
Clinical diagnosis, based on investigator assessment, of T1D for at least one year and using insulin for at 
least 1 year. 
• 
Criteria for documented hyperglycemia (at least 1 must be met): 
o Fasting glucose ≥126 mg/dL 
o Two-hour OGTT glucose ≥200 mg/dL 
o HbA1c ≥6.5% documented 
o Random glucose ≥200 mg/dL with symptoms 

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o No data at diagnosis is available but the participant has a convincing history of hyperglycemia 
consistent with T1D 
• 
Criteria for requiring insulin at diagnosis (1 must be met): 
o Participant required insulin at diagnosis and continually thereafter. 
o Participant did not start insulin at diagnosis but upon investigator review likely needed insulin 
(significant hyperglycemia that did not respond to oral agents) and did require insulin eventually 
and used continually. 
o Participant did not start insulin at diagnosis but continued to be hyperglycemic, had positive islet 
cell antibodies – consistent with latent autoimmune diabetes in adults (LADA) and did require 
insulin eventually and used continually. 
• 
Currently using an insulin pump for diabetes management 
• 
Currently using  or willing to use an insulin-to-carbohydrate ratio to calculate meal bolus sizes 
• 
Willing to change insulin infusion site at least every 3 days. 
• 
Confirmed pregnancy 
• 
Current gestational age ≤16 weeks 
• 
Age 18-40 years 
• 
HbA1c <10.0% 
• 
Demonstration of proper mental status and cognition for the study 
• 
Ability to access the internet and upload CGM data remotely if needed 
• 
An understanding of and willingness to follow the protocol and sign the informed consent  
 
Exclusion Criteria:   
• 
670 G users in Auto mode 
• 
Current gestational age >16 weeks 
• 
Cystic fibrosis  
• 
A known medical condition that in the judgment of the investigator might interfere with the completion 
of the protocol such as the following examples: 
o Inpatient psychiatric treatment in the past 6 months  
o Abnormal renal function test results (calculated GFR <60 mL/min/1.73m2); testing required for 
subjects with diabetes duration of greater than 5 years post onset of puberty  
o Active gastroparesis 
o Abuse of alcohol or recreational drugs 
o Infectious process not anticipated to resolve prior to study procedures (e.g. meningitis, 
pneumonia, osteomyelitis)  
o Uncontrolled arterial hypertension (Resting diastolic blood pressure >95mmHg and/or systolic 
blood pressure >160 mmHg) at the time of screening 
o Chronic oral steroid use 
• 
A recent injury to body or limb, muscular disorder, use of any medication, any carcinogenic disease, or 
other significant medical disorder if that injury, medication or disease in the judgment of the investigator 
will affect the completion of the protocol  
 
 
Research Activity 
 

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Check all that apply and complete the appropriate sections as instructed.  
  
1. 
  Drug & Device:  Drugs for which an investigational new drug application is not required. Device for 
which (i) an investigational device exemption application is not required; or the medical device is 
cleared/approved for marketing and being used in accordance with its cleared/approved labeling. (Specify in 
the Methods section) 
 
2. 
  Blood:  Collection of blood samples by finger stick, heel stick, ear stick, or venipuncture.  
 
3. 
  Biological specimens other than blood:  Prospective collection of human biological specimens by 
noninvasive means that may include: urine, sweat, saliva, buccal scraping, oral/anal/vaginal swab, sputum, 
hair and nail clippings, etc. 
 
4. 
  Tests & Procedures:  Collection of data through noninvasive tests and procedures routinely employed 
in clinical practice that may include: MRI, surface EEG, echo, ultrasound, moderate exercise, muscular 
strength & flexibility testing, biometrics, cognition testing, eye exam, etc.  (Specify in the Methods section) 
 
5. 
  Data (medical record, images, or specimens):  Research involving use of existing and/or prospectively 
collected data. 
 
6. 
  Digital Record:  Collection of electronic data from voice, video, digital, or image recording. (Specify in 
the Methods section) 
 
7. 
  Survey, Interview, Focus Group:  Research on individual or group characteristics or behavior, survey, 
interview, oral history, focus group, program evaluation, etc.  (Specify in the Methods section) 
 
 
 NIH has issued a Certificate of Confidentiality (COC).  When checked, provide the institution and 
investigator named on the COC and explain why one was requested. ________________________ 
 
 
Biospecimens – Categories 2 and 3 
 
(2)  Collection of blood samples. When multiple groups are involved copy and paste the appropriate section 
below for example repeat section b when drawing blood from children and adults with cancer.  
 
a. From healthy, non-pregnant, adult subjects who weigh at least 110 pounds. For a minimal risk 
application, the amount of blood drawn from these subjects may not exceed 550ml in an 8 week period 
and collection may not occur more frequently than 2 times per week. 
Volume per blood draw: _____ml   
Frequency of blood draw (e.g. single draw, time(s) per week, per year, etc.) ___________ 
 

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b. From other adults and children considering age, weight, and health of subject. For a minimal risk 
application, the amount of blood drawn from these subjects may not exceed the lesser of 50 ml or 3 ml 
per kg in an 8 week period, and collection may not occur more frequently than 2 times per week.   
Volume per blood draw:  
Frequency of blood draw (e.g. single draw, time(s) per week, per year, etc.)  
 
(3)  Prospective collection of biological specimens other than blood: ______________________________ 
 
 
Review of medical records, images, specimens – Category 5 
 
For review of existing data: provide a date range or an end date for when the data was generated. The end date 
can be the date this application was submitted to the IRB.  Example: 01/01/1999 to 12/31/2015 or all records 
through mm/dd/yyyy.  
Date Range: 
 
Check all that apply (data includes medical records, images, specimens).  
 
  (5a)  Only data that exists before the IRB submission date will be collected.   
 
 
  (5b)  The study involves data that exist at the time of IRB submission and data that will be generated after 
IRB submission. Include this activity in the Methods section.  
Examples 
• The study plans to conduct a retrospective chart review and ask subjects to complete a questionnaire.  
• The study plans to include subjects previously diagnosed with a specific disease and add newly 
diagnosed subjects in the future.  
 
  (5c)  The study will use data that have been collected under another IRB protocol. Include in the Methods 
section and enter the IRB number from which the research material will be obtained. When appropriate, note 
when subjects have provided consent for future use of their data and/or specimens as described in this protocol.  
 
Enter one IRB number per line, add more lines as needed 
 
 Data    
 Specimens  
 Data & Specimens  ______________________________________ 
 
 Data    
 Specimens  
 Data & Specimens  ______________________________________ 
 
 Data    
 Specimens  
 Data & Specimens  ______________________________________ 
 
 

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  (5d) This study will obtain data generated from other sources. Examples may include receiving data from 
participating sites or an external collaborator, accessing an external database or registry, etc.  Explain the source 
and how the data will be used in the Methods section.  
 
  (6)  Video audio recording: Describe the plan to maintain subject privacy and data confidentiality, 
transcription, store or destroy, etc.  
HIPAA Identifiers and Protected Health Information (PHI) 
 
Protected health information is medical data that can be linked to the subject directly or through a combination 
of indirect identifiers.  
 
Recording identifiers (including a code) during the conduct of the study allows you to return to the medical 
record or data source to delete duplicate subjects, check a missing or questionable entry, add new data points, 
etc. De-identified data is medical information that has been stripped of all HIPAA identifiers so that it cannot be 
linked back to the subject. De-identified data is rarely used in the conduct of a research study involving a chart 
review.   
 
Review the list of subject identifiers below and, if applicable, check the box next to each HIPAA identifier 
being recorded at the time of data collection or abstraction.  Identifiers apply to any subject enrolled in the 
study including Mayo Clinic staff, patients and their relatives and household members.  
 
Internal refers to the subject’s identifier that will be recorded at Mayo Clinic by the study staff. 
External refers to the subject’s identifier that will be shared outside of Mayo Clinic. 
 
Check all that apply: 
INTERNAL 
EXTERNAL 
Name 
X 
 
Mayo Clinic medical record or patient registration number, lab accession, 
specimen or radiologic image number  
X 
 
Subject ID, subject code or any other person-specific unique identifying 
number, characteristic or code that can link the subject to their medical data   
X 
X 
Dates: All elements of dates [month, day, and year] directly related to an 
individual, their birth date, date of death, date of diagnosis, etc.   
Note: Recording a year only is not a unique identifier.  
X 
 
Social Security number 
 
 
Medical device identifiers and serial numbers 
X 
X 
Biometric identifiers, including finger and voice prints, full face photographic 
images and any comparable images 
 
 
Web Universal Resource Locators (URLs), Internet Protocol (IP) address 
numbers, email address 
 
 
Street address, city, county, precinct, zip code, and their equivalent geocodes 
X 
 
Phone or fax numbers 
X 
 
Account, member, certificate or professional license numbers, health 
beneficiary numbers 
 
 

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Vehicle identifiers and serial numbers, including license plate numbers 
 
 
Check ‘None’ when none of the identifiers listed above will be recorded, 
maintained, or shared during the conduct of this study.  (exempt category 4) 
 None 
 None 
 
 
 
 
Data Analysis 
 
 
Power analyses may not be appropriate if this is a feasibility or pilot study, but end-point analysis plans are 
always appropriate even if only exploratory. Provide all information requested below, or provide justification if 
not including all of the information.  
 
Power Statement: Previous studies have found a clear benefit between AP and standard using 16 patients per 
group, so the sample size of 40 patients for data collection and comparator should be sufficient.  
 
Data Analysis Plan: Data from the 5 sites will be de-identified and collected at each site. CGM data will be 
compared to time-matched SMBG data to confirm accuracy in the pregnant population. Patterns of insulin and 
glucose control change will be analyzed and association with outcomes calculated. This data will also be used 
as a comparator for AP studies as a historical or active control group. 
 
Endpoints 
Primary:  
Time in range defined as 63-140 mg/dL as determined by CGM analysis 
 
Secondary:  
Glycemic Outcomes: 
-Frequency of hypoglycemia defined as <63 mg/dL and percent of time in the hypoglycemic range 
-Frequency and duration of severe hypoglycemic events defined as requiring assistance from another, an 
emergency room visit or treatment with glucagon due to unconsciousness  
-Time spent above target range defined as >140 mg/dL  
-Episodes of clinically significant hyperglycemia with CGM> 180 mg/dL 
-Extent of glucose variability 
-Percent of time CGM active 
-Concordance of CGM data in relation to SMBG data 
 
Insulin Delivery Outcomes: 
-Change in total daily insulin during pregnancy and the postpartum period 
-Change in basal insulin during pregnancy and the postpartum period 
-Change in insulin-to-carbohydrate ratio during pregnancy and the postpartum period 
-Change in insulin sensitivity during pregnancy and the postpartum period 
-Change in carbohydrate consumption during pregnancy and the postpartum period 
 

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Pregnancy Outcomes: 
-Episodes of ketoacidosis requiring emergency room or hospital admission 
-Maternal complications including preeclampsia, pregnancy induced hypertension and polyhydramnios 
-Gestational weight gain 
 
Delivery and Neonatal Outcomes to be collected: 
-Gestational age at delivery 
-Birth weight of baby 
-Fetal malformations 
-Incidence of Large for Gestational Age based on WHO criteria at time of delivery   
-Incidence of Small for Gestational Age based on WHO criteria at time of delivery 
-Preterm birth (<37 weeks and early preterm < 34 weeks) 
-Neonatal hypoglycemia requiring IV dextrose 
-Neonatal NICU stay > 24 hours and indication 
-Method of delivery and adverse events associated with delivery including shoulder dystocia 
-Mode of delivery including induction rates and incidence of primary cesarean section (and indication noted) 
-Length of hospital stay 
 
 
 
 

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References:  
 
[1] M. G. Dalfra, G. Sartore, G. Di Cianni, G. Mello, C. Lencioni, S. Ottanelli, et al., "Glucose variability in 
diabetic pregnancy," Diabetes Technol Ther, vol. 13, pp. 853-9, Aug 2011. 
[2] L. A. Barbour, C. E. McCurdy, T. L. Hernandez, J. P. Kirwan, P. M. Catalano, and J. E. Friedman, 
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