bluuebunny/crossref_metadata_2025_split huggingface dataset:
757-P: Financial Strain and Relationship Quality in Young Married Couples Managing Type 1 Diabetes
Authors: YORGASON JEREMY B. , SAYLOR JENNIFER , RELLAFORD SUSANNAH , PORTER MATTHEW S. 
Published: June 2020

Over the last 5 years, individual diabetes management costs have increased 26%, with the average diabetes patient spending $16,752 per year and those with type 1 diabetes mellitus (T1DM) paying a disproportionately higher amount than their type 2 counterparts. With T1DM diagnoses increasing by around 40,000 each year and the majority of diagnoses among adolescents and emerging adults approaching financial independence with limited funds, young T1DM patients and their partners may experience relational strain that often accompanies financial stress. Using data from a nationally representative sample of over 2,000 young married couples involved in the CREATE study, we identified 16 couples wherein one partner had T1DM. Among these, 8 wives had T1DM and 8 husbands had T1DM. For comparisons, we matched these couples with others in the CREATE study based on household income, husband and wife education, and husband and wife approximate number of weekly hours worked. A total of 116 matches were found, for a total of 132 couples in the analytic sample. Among the 16 couples with T1DM, half earned less than $50,000 annually (mean = $50,000-60,000/year). Mean comparisons indicated that both partners in couples with T1DM reported higher levels of financial distress and worry compared to matched couples, albeit not at a statistically significant level. Financial distress and worry were both significant predictors of relationship quality a year later for all couples in the study. However, associations between financial distress and relationship quality did not differ for couples with T1DM. Additional research is needed to explore specific diabetes supplies costs and how these may relate to relationship quality.

Disclosure
J.B. Yorgason: None. J. Saylor: None. S. Rellaford: None. M.S. Porter: None.

Funding
Brigham Young University
793-P: Exploring the Lived Experience of Inner-City, Food Insecure, African Americans with Type 2 Diabetes
Authors: WALKER REBEKAH J. , MOSLEY-JOHNSON ELISE , EGEDE LEONARD E. 
Published: June 2020

Food insecurity influences the health of adults with diabetes, however, limited information exists on the contribution of the lived experience of inner-city African Americans on clinical outcomes. The goal of this study was to understand the lived experience and its role in managing type 2 diabetes in inner-city, food insecure, African Americans. Two focus groups and two semi-structured interviews were conducted. Participants had a diagnosis of diabetes and indicated it was difficult to obtain enough food, or worried food would run out. Questions explored a) challenges and barriers in managing diabetes, b) the role of food insecurity in managing diabetes, and c) facilitators and resources that improve diabetes management. A grounded theory approach was used by reviewing field notes and identifying overarching concepts. In addition, following each session, facilitators and notetakers discussed key findings and incorporated into themes identified. Four themes emerged. 1) Barriers to eating healthy foods, included availability and cost of food, lack of discipline to follow a healthy diet, and uncertainty in taste of new foods. 2) Life stressors, included difficult decisions regarding money, the inner-city environment, such as violence and poverty, and needs of family and friends that distract from their needs. 3) Support resources, included obtaining food at pantries, community resources, such as social workers to identify programs and determine eligibility, and faith as an important supportive function. 4) Facilitators to obtaining healthcare, included access to care through insurance and transportation, providers who understood the financial situation and treated them with respect, options for medication, and knowledge of diabetes. Greater attention needs to be paid to the lived experience of inner-city, food insecure, African Americans with diabetes when designing interventions to improve health in this highly vulnerable population.

Disclosure
R.J. Walker: None. E. Mosley-Johnson: None. L.E. Egede: None.

Funding
American Diabetes Association (1-19-JDF-075 to R.J.W.); National Institutes of Health (R01MD013826, K24DK093699, R01DK118038, R01DK120861)
8-LB: Emotional Impact of Hypoglycemia and Use of Glucagon: Perspectives of People with T1D and Caregivers of Minors with T1D
Authors: HUGHES ALLYSON , BISPHAM JEOFFREY , FULLER LILY , WOLF WENDY , FITCH SUSANNE A. , WEINZIMER STUART A. 
Published: June 2020

Severe hypoglycemia is a complication of insulin therapy and a continuing barrier to achieving glycemic targets at every age. Glucagon, a drug that has been on the market for several decades, is an effective treatment for severe hypoglycemia, but is underutilized. The emotional impact of severe hypoglycemia and the emergency use of glucagon is not clear. This study aimed to understand current perceptions of glucagon from both the perspective of people with T1D and people likely to aid in an emergency situation. All participants were recruited from T1D Exchange Glu (www.myglu.org), an online community for individuals living with T1D. The current study conducted interviews with people with T1D (n=9, average age 44.7 years) and caregivers (n=8, average age 37.8 years) of minors with T1D. Interviews were recorded, transcribed, and thematically analyzed. Participants described experiences and emotions surrounding severe hypoglycemia, importance of specific glucagon characteristics, and priorities during severe hypoglycemia. Participants expressed on a 1-10 scale the importance of glucagon’s time to recovery (average: 8.56), mode of administration (average: 8.56), cost (average: 5.67), and not requiring refrigeration (average: 9.56). Themes among participants with T1D included feelings of distress, fear, and helplessness; common caregiver themes included feeling intimidated by the administration of glucagon. People with T1D discussed how they make decisions during a hypoglycemic emergency and rely on others for decision-making. Participants described their ideal glucagon and emphasized how fast glucagon needs to be, the desire for minimal side effects, and different administration types. These results provide insight into the real-world impact of diabetes on both persons with T1D and their caregivers and highlight the attitudes about severe hypoglycemia and emergency treatment with glucagon.

Disclosure
A. Hughes: None. J. Bispham: None. L. Fuller: None. W. Wolf: None. S.A. Fitch: Employee; Self; Zealand Pharma A/S. S.A. Weinzimer: Consultant; Spouse/Partner; Tandem Diabetes Care. Consultant; Self; Zealand Pharma A/S. Speaker’s Bureau; Self; Insulet Corporation.
80-LB: Hypoglycemia in People with Type 2 Diabetes Using Premixed (Biphasic) Insulin
Authors: IDRIS ISKANDAR R. , ANNAMALAI NARAYAN , AUNG THEINGI , BINNIAN IAN , GIBB FRASER W. , MALIK MOHAMMED I. 
Published: June 2020

Hypoglycemia is under-reported by many patients; but the time in hypoglycemia among patients with type 2 diabetes (T2D) using pre-mixed (biphasic) insulin is not clear. This pilot study aimed to determine the amount of time in hypoglycemia in this patient cohort. The study included people with T2D, aged 18 or over, treated with pre-mixed (biphasic) insulin for at least 6 months with their most recent HbA1c &lt;7.5% (58 mmol/mol) recorded in medical notes in the last 12 months. Pregnant patients were excluded, as were patients on dialysis. A total of 43 participants (65.1% male) from 12 primary and secondary care sites in the UK enrolled in the 2-week single arm study using the FreeStyle Libre Pro Flash Glucose Monitoring SystemTM. Mean HbA1c was 6.9±0.8% (52.1±8.3 mmol/mol), age was 68.8±8.3 years, BMI was 35.0±9.2 kg/m2, average duration of pre-mixed insulin was 6.8±4.8 years with a mean daily dose of 53.4±40.7 units (mean±SD). The number of blood glucose tests performed per day (self-reported) was 1.9±1.1. Time in hypoglycemia &lt;70 mg/dL (3.9 mmol/L) was 1.35±1.56 hours per day, biological hypoglycemia was experienced by 34 patients. Approximately half of the time in hypoglycemia (&lt;70 mg/dL [3.9 mmol/L]; 0.82±1.06 hours) was during night time hours (23:00 to 06:00). Time in hyperglycemia &gt;180 mg/dL (10.0 mmol/L) was 3.55±3.07 hours per day, which mostly occurred was during daytime hours (06:00 to 23:00) (3.15±2.83 hours per day) (mean±SD). Five anticipated sensor insertion site symptoms were experienced by four participants: erythema (n=2 [1 slight pink, 1 well-defined redness]), pain (n=1), bruising (n=1) and bleeding (n=1), all were mild in severity. This population, with HbA1c in target range, have a greater amount of hypoglycemia than the International Consensus and ADA targets of &lt;1 hour per day, excursions occurred both during the day and at night. Further improvements on this level of glycemic control is challenging for this type of insulin therapy due to further escalation of the risk of nocturnal hypoglycemia.

Disclosure
I.R. Idris: None. N. Annamalai: None. T. Aung: None. I. Binnian: None. F.W. Gibb: None. M.I. Malik: None.
82-LB: Including Continuous Glucose Monitoring (CGM) to Provide Personalized Glycemic Profiles as Part of a Pilot Worksite Health Screening
Authors: KLEIN ILENE J. , CRAWFORD MARGARET , NORMAN GREGORY J. , HAMES KAZANNA C. , JUSTUS JORDAN I. , TREADWELL SABRINA , COMBEE TIFFANY M. , KINZLER SUSAN , WELSH JOHN , JOHNSON MATTHEW 
Published: June 2020

Incorporating CGM into worksite health screenings may help employees gain insight into their glycemic patterns. This observational study piloted a voluntary health screening at a large employer that included 10 days of blinded Dexcom G6 CGM wear. At enrollment, HbA1c values and participants’ reports were used to assign diabetes status. Participants and their primary care providers received summaries of their CGM-based glucose profiles. A total of 207 participants (mean (sd) age = 50.7 (10), 84% female, 15% African American, 15% Hispanic, 56% obese) enrolled in the screening from April through August 2019, and 85% (175) wore the CGM for ≥4 days. HbA1c identified 7 and 24 participants with previously undiagnosed T2D and prediabetes, respectively. The final diabetes prevalence was 61 (35%) with T2D, 5 (3%) with T1D, 35 (20%) with prediabetes, and 74 (42%) with no diabetes. Among those with T2D, 27 (44%) met consensus-based goals for TIR. The Table shows CGM-based metrics from health screening participants compared to Shah’s (2019) normative sensor glucose data of people without diabetes. Those with prediabetes had higher mean glucose and lower TIR than the normative sample. Health screenings that include blinded CGM provide personalized feedback regarding glycemic patterns, even among people without known diabetes.

Disclosure
I.J. Klein: Consultant; Self; Dexcom, Inc. M. Crawford: Employee; Self; Dexcom, Inc. G.J. Norman: Employee; Self; Dexcom, Inc. K.C. Hames: Employee; Self; Dexcom, Inc. J.I. Justus: None. S. Treadwell: Employee; Self; Dexcom, Inc. T.M. Combee: None. S. Kinzler: Research Support; Self; Dexcom, Inc. J. Welsh: Employee; Self; CSL Behring. M. Johnson: Employee; Self; Dexcom, Inc.
823-P: Diabetes Camp Experience Associated with Improved Glycemia and Treatment Satisfaction
Authors: DARUKHANAVALA AMY , DINUNNO KYLE V. , PUHR SARAH , WELSH JOHN B. , BUTLER LYNN , ALFEGO DAVID , MAGYAR KENDRA L. 
Published: June 2020

We compared glycemic metrics using continuous glucose monitoring (CGM) and quality of life between diabetes camp and the preceding home week. Insulin-treated youth (6-17 years) with T1D were enrolled at Barton Diabetes Camp and participated in 3 clinic visits: at the start of home week, where a Dexcom G6 CGM system was initialized; at the start of camp week, where the home week G6 was removed and a camp week G6 was inserted; and after camp, where the camp week G6 was removed. Problem areas in diabetes (PAID) surveys were administered at visits 2 and 3. Data from campers who did not complete all surveys were excluded. At camp, treatment decisions were informed by G6 as per FDA guidelines; interventions were prompted by daytime glucose levels ≤55 mg/dL or ≥350 mg/dL and for nighttime glucose levels ≤80 mg/dL or ≥300 mg/dL. Glycemic control and PAID scores were compared between home and camp weeks. Of 76 enrolled campers, 69 completed the study and 52 had results that qualified for analysis. Mean (SD) age was 12.5 (2.2) years. Most campers used insulin pumps (87.2%) and had experience with CGM (86.6%). Camp was associated with significant improvements in treatment satisfaction, time in range and in hyperglycemia, decreased basal insulin requirements, and improved insulin sensitivity (Table). Diabetes camp is associated with significant improvements in diabetes treatment satisfaction and glycemia compared to home care.

Disclosure
A. Darukhanavala: None. K.V. Dinunno: None. S. Puhr: Employee; Self; Dexcom, Inc. J.B. Welsh: Employee; Self; CSL Behring. L. Butler: None. D. Alfego: None. K.L. Magyar: None.

Funding
Dexcom, Inc.
83-LB: Are Activation, Behaviors, and Attitudes to Managing Care Associated with Utilization of a Remote Diabetes Monitoring Platform (RDMP) and Improvement of A1C?
Authors: PEREZ-NIEVES MAGALY , LU WEI , POON JIAT LING , FAN LUDI , JAMES ROBERTA , SHAH BIMAL 
Published: June 2020

Background: Many validated patient-reported outcome measures (PROMs) evaluate activation, behaviors, and attitudes towards managing one’s own health and care. However, their association with utilization of diabetes management technology and glycemic control has not been well studied.
Methods: People participating in Livongo’s RDMP for 12-18 months were surveyed using 3 validated PROMs that assessed activation (PAM), empowerment (DES), and distress (DDS). Pearson correlation was used to assess the relationship between PROMs and multivariable logistic regression was used to evaluate associations of PROM scores on RDMP usage and A1c improvement overall and by insulin use.
Results: PAM and DES scores were most correlated with each other (r=0.48); neither were associated with A1c improvement. People with higher DES scores were 20% more likely to have high RDMP usage (p&lt;0.05) and people with high RDMP usage were 4.4 times more likely to have A1c improvement. High distress (DDS17&gt;=3) was negatively associated with A1c improvement.
Conclusions: In this study, PAM was not associated with activation, behaviors, and attitudes influencing RDMP usage and outcomes, while the DES and DDS17 were associated with RDMP. Because of the impact of distress on outcomes, it should be monitored and RDMP interventions should focus on distress reduction.

Disclosure
M. Perez-Nieves: Employee; Self; Eli Lilly and Company. Stock/Shareholder; Self; Eli Lilly and Company. W. Lu: Employee; Self; Livongo Health. J. Poon: Employee; Self; Eli Lilly and Company. L. Fan: Employee; Self; Eli Lilly and Company. Stock/Shareholder; Self; Eli Lilly and Company. R. James: Advisory Panel; Self; AstraZeneca. Employee; Self; Livongo Health. B. Shah: Employee; Self; Livongo Health.
838-P: Air Quality and HbA1c Levels in U.S. Hispanic/Latino Immigrants with Type 2 Diabetes: An Exploratory Observation
Authors: GLANTZ NAMINO M. , DESCHENES OLIVIER , KERR DAVID 
Published: June 2020

In the U.S., Hispanic/Latino populations bear a disproportionate burden of type 2 diabetes (T2D) and its complications. Research suggests that poor air quality may have an influence on progression of T2D.
We compared HbA1c levels in Hispanic/Latino (95% Mexican-origin) adults with T2D by exposure to particulate matter &lt;2.5 micrometers in diameter (PM2.5).
HbA1c levels were measured on 101 participants (54±12 years, 65% female, 25% insulin users, 60% uninsured, 40% food insecure). A third (36%) had an HbA1c &lt;7.0% and 30% &gt;9.0%. We matched HbA1c with California Air Resource Board (CARB) air pollution records to create a regression model relating HbA1c to average ambient PM2.5 concentration with participant zip codes 14 days prior to HbA1c measurement. PM2.5 exposure was stratified as “high” or “low,” (&gt; or &lt; 12 µg/m³ annual CARB standard PM2.5 concentration), controlling for other PM2.5-correlated factors (location, year and month fixed effects).
Figure 1 shows regression-adjusted mean [95% CI] HbA1c for low (N=85) and high exposure individuals (N=16) and estimated difference between groups (2.2%, p&lt;0.05). Individuals with high PM2.5 exposure had higher HbA1c levels than those with lower exposure.
Air pollution exposure should be considered as an independent factor impacting glycemic control in Hispanic/Latino adults with T2D.

Disclosure
N.M. Glantz: Research Support; Self; Abbott, Eli Lilly and Company. O. Deschenes: None. D. Kerr: Advisory Panel; Self; Novo Nordisk A/S, Sanofi-Aventis. Research Support; Self; Eli Lilly and Company. Stock/Shareholder; Self; Glooko, Inc.

Funding
Eli Lilly and Company (2017-5864)
842-P: Analysis of Primary Care Provider (PCP) EHR Notes for Discussions of Prediabetes Using Natural Language Processing (NLP) Methods
Authors: TSENG EVA , SCHWARTZ JESSICA L. , ROUHIZADEH MASOUD , MARUTHUR NISA M. 
Published: June 2020

Background: Prior studies using structured EHR data suggest that patients with prediabetes are not receiving evidence-based care, but prediabetes may be discussed in unstructured data. We developed and validated an NLP tool to identify discussions about prediabetes in EHR notes.
Methods: We included adult patients without diabetes with an in-person office visit at any general medicine clinic at a single academic center and at least one HbA1c 5.7-6.4% between 7/1/2016 and 12/31/2018. In phase 1, we devised an initial keyword search strategy based on clinical experience. We extracted notes with at least one of the keywords and manually annotated them to determine whether they represented clinical discussions of prediabetes. We used the annotated notes to train and evaluate multiple machine learning and deep learning classifiers to replicate human annotation. In phase 2, we applied a similar annotation process and machine learning method on notes from a different group of clinic practices. We analyzed notes from phase 2 to describe the content of prediabetes discussions: labs ordered or reviewed (HbA1c or fasting glucose); lifestyle counseling; diabetes prevention program (DPP) discussion/referral; nutrition referral/discussion; and metformin discussion or ordering/continuation.
Results: We identified 269 patients with prediabetes discussions in phase 2. Most commonly, PCPs provided lifestyle counseling (80%), reviewed current labs (63%) and ordered follow-up labs (60%). PCPs rarely discussed/referred to a nutritionist (4%). We did not find any discussions/referrals to a DPP. Metformin was discussed, ordered or continued in &lt;2% of patients.
Conclusions: We developed and validated a NLP tool that identifies clinical discussions about prediabetes in the EHR. PCPs most commonly provided lifestyle counseling in the office and infrequently placed referrals to nutrition or DPPs, which have strong evidence for preventing progression to diabetes.

Disclosure
E. Tseng: None. J.L. Schwartz: None. M. Rouhizadeh: None. N.M. Maruthur: Other Relationship; Self; Johns Hopkins HealthCare Solutions.

Funding
National Institute of Diabetes and Digestive and Kidney Diseases (1K23DK118205-01A1)
853-P: Continuous Glucose Monitor Predicts Glycemic Variability in High-Risk Individuals with HbA1c &lt;5.7%
Authors: DORCELY BRENDA , SIFONTE ELIUD , DIVAKARAN ANJANA , KATZ KARIN , JAGANNATHAN RAM , GOLDBERG IRA J. , BERGMAN MICHAEL 
Published: June 2020

Objective: Glycemic variability (GV) and 1 hour plasma glucose (1-h PG) ≥ 8.6 mmol/L during a 75-gram oral glucose tolerance test (OGTT) are associated with increased risk for type 2 diabetes (T2D). GV may be overlooked in high-risk individuals. The objectives of this study are: (1) to determine if continuous glucose monitoring (CGM) using the Abbott Freestyle Libre Pro can replace the OGTT in high-risk subjects with HbA1c &lt; 5.7%; and (2) to determine if GV indices correlate with the OGTT-derived 1-h PG ≥ 8.6 mmol/L.
Methods: Subjects were recruited with a HbA1c &lt; 5.7% and at least one other risk factor including: overweight or obesity, PCOS, fatty liver, hypertension, family history of T2D, or history of gestational diabetes. The CGM, placed days prior to the OGTT, was worn up to 14 days. Anthropometric and vital signs were measured. HbA1c, fasting, 1-h and 2-h PG levels during an OGTT were obtained.
Results: The 1-h PG correlated significantly with CGM glucose levels (r=0.883, p&lt;0.001) and GV indices: mean amplitude of glucose excursions (MAGE) (r=0.665,p=0.006), lability index (LI) (r=0.601, p=0.014), and high blood glucose index (HBGI) (r=0.743, p=0.001) (Table 1).
Conclusions: The 1-h CGM glucose and elevated GV indices significantly correlate with 1-h PG (&gt; 8.6 mmol/L) in high-risk subjects with HbA1c &lt; 5.7%. CGM could potentially replace the OGTT for detecting early dysglycemia in those with HbA1c &lt; 5.7%.

Disclosure
B. Dorcely: None. E. Sifonte: None. A. Divakaran: None. K. Katz: None. R. Jagannathan: None. I.J. Goldberg: None. M. Bergman: None.

Funding
Abbott Diabetes Care; New York University Clinical and Translational Science Award (UL1 TR001445)
865-P: Influence of Glucose Measurement Interval on Glycemic Variability Values
Authors: TAKEISHI SOICHI , TSUBOI HIROKI 
Published: June 2020

We examined how glucose measurement intervals influence glycemic variability (GV) values. In this cross-sectional study, we analyzed 24-h sensor glucose levels (SG) measured during hospitalization using a continuous glucose monitor (iPro2) in 96 patients with type 2 diabetes. GV was calculated from SG values extracted every 5 min × the divisors of 288 (excluding 10, 360, 480, 720, 1440 minutes). Because mean glucose level (Mean) values are influenced more from extraction start time as extraction intervals increase, to maximumly reduce that influence, at first, the 96 patients were ranked from “1” (highest Mean) to “96” (lowest Mean) according their individual Mean values. Then, we delayed the extraction start time every 15 min in the following order: “96,” “2,” “95”⋯ “48,” “49,” from 00:00 of “1.” In the percentage of time in range (70-180 mg/dL) [TIR 70-180], Mean, standard deviation (SD), and coefficient of variation (CV), the values were numerically almost equal in every extraction. The mean absolute glucose (MAG) and glycemic variability percentage (GVP) became lower as extraction intervals increased. Extraction every 240 min showed a correlation coefficient to measurement every 5 min (r to 5 min) of about 0.9 for TIR 70-180, Mean, SD, and CV. Extraction every 60 min had an r to 5 min of about 0.9 for MAG and GVP (Table). Theoretically, for TIR 70-180, SD, and CV, measurements performed every 4 hours may maintain an r to 5 min of about 0.9.

Disclosure
S. Takeishi: None. H. Tsuboi: None.