bluuebunny/crossref_metadata_2025 huggingface dataset:
611-P: Do Social Needs Impact Quality of Life among Adult Medicaid Beneficiaries with Type 2 Diabetes?
Authors: MCQUEEN AMY , BROWN DEREK , VERDECIAS NIKO , KREUTER MATTHEW
Published: May 2022

Treatment trials increasingly include quality of life (QoL) measures to compliment clinical outcomes. Most QoL studies focus on clinical correlates. The growing appreciation for social determinants of health warrant examining how they impact QoL. This analysis of a preliminary baseline sample of 296 Medicaid beneficiaries with type 2 diabetes from an ongoing intervention trial examined the influence of social needs on aggregate and subscale T-scores of the SF12v2 QoL measure individually and controlling for covariates. We assessed 12 social needs (e.g., food, housing, utilities) and receipt of 9 resources (e.g., food stamps, WIC) . Participants rated having 22 chronic conditions and their impact (when applicable) on daily activity (1=not at all; 5=a lot) . Participants were female (76.7%) , White (29.1%) , Black (65.9%) , age M=51.8 (SD=9.3) , had M=2.7 social needs (SD=1.7) and M=1.3 (SD=1.2) resources. Including diabetes, participants reported M=7.4 chronic conditions (SD=3.0) with moderate impact M=23.0 (SD=14.4) . Mean QoL T-scores were all below the norm (50) except vitality (M=51.9, SD=11.4) . Sum needs were associated with aggregate mental health (r= -.13, p=.032) and 3 of 4 subscales: vitality (r= .16, p=.007) , role emotional (r= -.18, p=.002) , and social functioning (r= -.23, <.001) . For physical health, social needs were only associated with the pain subscale (r= -.17, p=.004) . Although the influence of social needs remained statistically significant for some subscales when controlling for chronic conditions, needs were most consistently associated with social functioning even when controlling for comorbidity impact, age, race, sex, and resources. We found few strong associations between social needs and SF12 scores, which may be due in part to limitations in how QoL is defined and measured and the distal causal pathway between social needs and functioning. Future analyses will examine changes in QoL over time and differences by treatment group and social needs.

Disclosure

A.Mcqueen: None. D.Brown: None. N.Verdecias: None. M.Kreuter: None.

Funding

National Institute of Diabetes and Digestive and Kidney Diseases (1R01DK115916-01)
63-LB: Correlates of CGM Uptake among Adults with Type 2 Diabetes in Primary Care
Authors: MAYBERRY LINDSAY S. , RODDY MCKENZIE K. , JASER SARAH S. , ELASY TOM A.
Published: May 2022

Clinical trials indicate continuous glucose monitor (CGM) use in type 2 diabetes (T2D) can be beneficial across medication regimens and outpatient settings. CGM use in care for T2D is increasing rapidly, but little is known about predictors of CGM use in T2D. Adults (age 18-75) with T2D receiving primary care at an academic medical center enrolled in a RCT evaluating a self-management support intervention. The intervention did not address CGM use. At enrollment, patients completed an A1c test, self-reported demographic, clinical characteristics and individual (diabetes distress, diabetes self-efficacy, health literacy) , social (family/friend involvement, shared illness perception) , and behavioral (self-care behaviors) factors. The 15-month assessment queried CGM use in prior 12 months (current use/used and quit vs. no use) . We explored potential correlates of CGM use with unadjusted non-parametric tests of difference. Patients (N=109) completed 15-month assessments from July 2021 to March 2022. Mean age was 58±10 years; 57% female; 54% non-Hispanic white, 31% non-Hispanic black, 7% Hispanic; mean baseline A1c was 8.8%±1.8%. One-third (n=36) used CGM during the prior 15 months (including n=3 who quit) . CGM users were younger (median [IQR]: age 55 [47, 62] vs. 60 [53, 68], p=.031) , had higher baseline A1c (9.1% [8.1, 10.4] vs. 8.3% [7.5, 9.5], p=.048) and more were using insulin (69% vs. 36%, p=.002) as compared to non-users. CGM users also had higher baseline diabetes distress (45 [25, 55] vs. 30 [15, 50], p=.09) . CGM use was not related to gender, diabetes duration, race, ethnicity, health literacy, diabetes self-efficacy, family/friend involvement, perceiving diabetes as a shared illness, nor self-care behaviors. In a prospective study of adults with T2D from primary care clinics, younger age, insulin use, higher A1c and higher diabetes distress were associated with starting CGM. Two-thirds of CGM users were taking insulin. We did not find gender, race, ethnicity nor health literacy disparities in CGM use in our diverse sample.

Disclosure

L. S. Mayberry: Consultant; Abbott Diabetes, Cecelia Health. M. K. Roddy: None. S. S. Jaser: None. T. A. Elasy: None.

Funding

National Institutes of Health (R01DK119282)
634-P: Transition Readiness Variables Predict Transfer to Adult Care among Youth with Type 1 Diabetes
Authors: SHAPIRO JENNA , WEISSBERG-BENCHELL JILL
Published: May 2022

The transfer from pediatric to adult care for adolescents and young adults (AYA) with T1D is a challenging process during which AYAs are vulnerable to worsening metabolic outcomes, missed clinic visits, and increased ED and hospital admissions. This study investigated which modifiable individual and family-specific transition readiness variables may lead to improved transfer of care outcomes. Two-hundred fifty-four individuals with T1D ages 16 to 25 years (Mage=20.9+2.7) completed an online survey. Multiple regression in SPSS assessed relations between (a) individual (diabetes-specific resilience, diabetes distress, self-care behaviors, problem solving) and (b) family (diabetes-related conflict, communication, miscarried helping, support) transition readiness variables and transfer of care outcomes. Variables were entered simultaneously, above and beyond covariates, and significant predictors were indicated by p < .05. With respect to individual factors, greater problem solving was associated with seeing an adult (versus pediatric) provider, less hospital admissions, less severe low blood sugars, and more clinic visits one-year post-transfer. Resilience was associated with increased readiness to transfer. Self-care behaviors were associated with fewer severe low blood sugars. Diabetes distress was associated with lower likelihood of seeing an adult provider and more ED and clinic visits. With respect to family factors, higher conflict was associated with a higher rate of ED visits, fewer clinic visits, and fewer episodes of severe low blood sugars post-transfer. Miscarried helping was associated with a greater likelihood of seeing an adult provider. Modifiable individual and family-specific transition readiness variables are uniquely associated with key transfer of care outcomes. Interventions that reduce family conflict and diabetes distress, and improve diabetes resilience and problem solving, are likely to improve these outcomes.

Disclosure

J.Shapiro: None. J.Weissberg-benchell: None.

Funding

Dixon Family Foundation
638-P: Differences in Perceived Stress between Genders among People with Diabetes during COVID Lockdown in Argentina
Authors: POMARES MARIA L. , MARTIN CAROLINA GOMEZ , APOLONI SUSANA , MURATORE CAROLINA M. , AVILA PABLO J. , FORLINO MARIANO A. , RIVERA FRANCISCO , CASTAGNINO LUISINA , PIEDIMONTE BARBARA ,   COVID-GRAD STUDY GROUP,   SOCIETY ARGENTINE DIABETES
Published: May 2022

Many studies suggest that there is a difference in perceived stress (PS) among genders in general population. Gender differences in patients with diabetes are uncertain. Descriptions of gender differences in PS during Covid lockdown in people with diabetes are lacking.

Objectives: To assess the differences regarding perceived stress and anxiety between genders among persons with diabetes during COVID-pandemic lockdown. Secondary: To describe the association between PS with metabolic control and other co-variables.

Methods: Multicenter, cross-sectional observational study of data collection through an online survey. Adults with T1D and T2D in 37 Argentine Diabetes Centers were included, from April to May, 2020. Degree of stress was evaluated by the Perceived Stress Scale (PSS) , and anxiety by the Beck Anxiety Inventory (BAI) .

Results: 2273 patients were included. 1194 (52.5%) were female. Age in woman 48.6 years and 52.1 in men. The proportion of patients with T2D was higher in male (58.6% vs. 48.9%) . Diabetes duration was around 14 years, similar in both genders. A1c levels were higher in female patients (7.7% vs. 7.5%, p < 0.05) . BAI and PPS scales resulted significantly correlated (r=0.58; p <0.001) . In the univariate analysis BAI and PPS scores were significantly higher in women with both T1D and T2D vs. men (BAI 8.9 vs. 6.6, p<0.001, PSS 14.3 vs. 11.8, p<0.001) . Using a logistic model as a discriminant function, female gender was significantly associated with BAI and PPS scores after adjustment for type of diabetes, age, A1c, educational level, living alone condition and the presence of comorbidities or complications (p<0.001) . Using multiple linear regression, BAI and PSS scores were significantly associated with female gender, after adjustment by the same covariates (BAI p<0.00 and PSS p<0.0013) .

Conclusion: In the study sample, female gender was associated with higher scores of anxiety and PS, in a context of isolation due to COVID pandemic in Argentina.

Disclosure

M.L.Pomares: None. Study group covid-grad, argentine diabetes society: n/a. C.Gomez martin: None. S.Apoloni: None. C.M.Muratore: None. P.J.Avila: None. M.A.Forlino: Speaker's Bureau; Novo Nordisk. F.Rivera: None. L.Castagnino: None. B.Piedimonte: None.
642-P: Physicians' Knowledge and Attitudes of Disordered Eating Behaviors among Patients with Diabetes
Authors: KHATCHADOURIAN NAYIRI , SCHMELTZ LOWELL , UHLEY VIRGINIA , BRENNAN MICHAEL R.
Published: May 2022

Patients diagnosed with type 1 and type 2 Diabetes Mellitus (DM) are at increased risk for developing clinical disordered eating behaviors (DEBs) . Although research supports this higher incidence and the impact on health outcomes, few studies have assessed physicians’ knowledg,attitudes and training to identify and treat DEB. The American Diabetes Associations’ 2021 Standards of Care included a new section aboutDEB, further highlighting the importance of addressing this issue. Our goal was to assess physicians’ level of training, comfort and attitudes towards providing clinical care to patients diagnosed with DM and their experience in assessing, identifying, and treating DEBs in this patient population.

The cross-sectional study, a 17-question online survey through Qualtrics, was developed by modifying questionnaires from the Michigan Diabetes Research Center and was emailed to participants. The response size was 34 physicians or medical residents that provide care for patients diagnosed with DM.

97% of the physicians were endocrinologists with years of experience ranging from 6-35 years. 58.8% reported not having received any education about identifying or assessing for DEB among patients diagnosed with DM during or after their professional training. 67.6% identified that they did not believe they have the resources available to assist a patient with DEB; requested suggestions included an online learning course, screening questionnaires and specialty training.

These research results highlight possible gaps in medical education programs regarding training around DEB. Our future plans are to address this by creating continuing medical education training modules for endocrinologists and endocrinology residents focused on the evaluation, diagnosis, and treatment of DEB in patients diagnosed with DM. We anticipate that this will help to enhance the knowledge and skills of physicians and residents in the clinical care and support of patients diagnosed with DM.

Disclosure

L. Schmeltz: Research Support; Abbott Diabetes. Speaker's Bureau; Abbott Diabetes, Dexcom, Inc., Lilly, Novo Nordisk, Xeris Pharmaceuticals, Inc. V. Uhley: None. M.R. Brennan: Advisory Panel; Insulet Corporation. Speaker's Bureau; Novo Nordisk. Other Relationship; Bayer AG.
647-P: Improved Glycemic Control and Continuous Glucose Monitoring (CGM) Utilization: A Comparison of Real-Time CGM and Intermittent Scanning CGM
Authors: HANNAH KATIA , NEMLEKAR POORVA , PRICE DAVID A. , NORMAN GREGORY J.
Published: May 2022

Evolution of CGM technology has equipped the market with different systems. This study compared two types of CGM devices, real-time (rt) CGM and intermittently scanned (is) CGM on clinical outcomes among persons with diabetes using intensive insulin therapy. A retrospective analysis was performed using Optum Clinformatics® Database comprised of administrative claims data. CGM naïve patients with type 1 or type 2 diabetes initiated rtCGM (Dexcom G6®) or isCGM (FreeStyle Libre®) between 8/1/2018 through 3/31/2020 (index date = earliest observed pharmacy claim) . Patients with continuous health plan enrollment 12-months pre and post index date, age ≥18 years, with ≥1 sensor pharmacy claim, with A1C lab values during baseline and follow up were included in the study. Outcomes were the proportion reaching a target A1C of < 7% and the change in number of severe hypoglycemia (SH) inpatient/ER visits. A total of 272 rtCGM (average age = 47.3 (sd = 13.1) years, 46.7% female) and 467 isCGM (average age = 50.9 (sd = 12.7) years, 37.5% female) patients on intensive insulin therapy met inclusion criteria. After adjusting for baseline, rtCGM users were nearly twice as likely, compared to isCGM users, to reach an A1C of < 7% (OR = 1.97, 95% CI, 1.32 to 2.95, p<0.01) . A significant reduction was found in SH events from 40 to 13 after rtCGM initiation (baseline mean = 0.15, sd=0.49; and follow up mean = 0.05, sd=0.23, p<0.01) . For isCGM users SH events reduced from 42 to 32 (mean = 0.09, sd=0.44; and follow up mean 0.07, sd=0.35, p=0.239) . Findings suggest CGM naïve patients benefit from rtCGM compared to isCGM through significantly greater numbers achieving A1C < 7%. Improved access to rtCGM should help more patients achieve optimal glycemic control and reduce health care encounters due to SH.

Disclosure

K.Hannah: Employee; Dexcom, Inc. P.Nemlekar: None. D.A.Price: Employee; Dexcom, Inc. G.J.Norman: Employee; Dexcom, Inc.
648-P: Lag Times in a Seventh-Generation Continuous Glucose Monitoring System
Authors: ZHANG XIAOHE , REID JENNIFER L. , WALKER TOMAS C. , WELSH JOHN , BALO ANDREW
Published: May 2022

Background: Glucose transport from blood to interstitial fluid impacts performance of interstitially-placed continuous glucose monitoring (CGM) sensors. We examined time series offsets (“lag times”) of the G7 CGM system (Dexcom) .

Methods: In a pivotal accuracy study conducted in the US, 316 adults with diabetes wearing 6sensors participated in clinic sessions that included glucose manipulations and frequent venous plasma glucose (YSI) determinations. G7 values were obtained every 5 min and interpolated to provide values at 1-min intervals. Each YSI value was associated with 21 G7 values obtained from min before to min after. The absolute relative difference (ARD) was calculated for each YSI:G7 pair and each sensor’s lag was estimated as the time with the lowest mean ARD.

Results: A lag time of 2 minutes provided the lowest mean ARD of 8.6% and the highest %20/20 agreement rate of 94.4%. The Figure shows summary statistics for the distribution of sensor-specific lag times. Lag times of ≤0 min (where interstitial glucose leads blood glucose) were observed for 2 (33.0%) of the sensors.

Conclusions: The distribution of G7 time series offsets suggests that CGM values may most accurately reflect previous or upcoming blood glucose values. This finding is likely due to technological innovations in G7’s hardware and algorithm. The minimal lag time observed should provide users with confidence in using CGM to manage their diabetes.

Disclosure

X.Zhang: Employee; Dexcom, Inc. J.L.Reid: Employee; Dexcom, Inc., GenMark Diagnostics. T.C.Walker: Employee; Dexcom, Inc., Stock/Shareholder; Dexcom, Inc. J.Welsh: Employee; Dexcom, Inc. A.Balo: Employee; Dexcom, Inc.

Funding

Dexcom, Inc.
650-P: Artificial Intelligence and Individualized Optimal Glycemic Target in ICU Patients
Authors: YUN JAE-SEUNG , LEE GARAM , KIM JAESIK , KO SEUNG-HYUN , AHN YU-BAE , KIM DOKYOON , SONG KI-HO
Published: May 2022

Introduction: Deep learning methods, commonly called artificial intelligence (AI) , have been widely adopted in medical research. Reinforcement learning is a particularly promising AI tool that can generate optimal strategies based on non-optimized training data. The aim of the currentstudy was to develop and validate a reinforcement learning algorithm for determining optimal glycemic targets for sepsis patients in the ICU.

Methods: We developed and validated a clinical decision support model that provided an individualized daily glycemic target for each critically ill patient based on the retrospective analysis of two independent ICU databases, Medical Information for Mart for Intensive Care III (MIMIC-III) and the eICU Collaborative Research Database (eICU-CRD) . We used a Markov decision process (MDP) to formulate sequential decision-making. The discrete state was generated by quantizing all patients’ longitudinal health records using a k-means clustering algorithm. To evaluate clinician policy, we used the temporal-difference (TD) learning method. To learn AI policy, we generated a random action policy, updated the value function, and used the value function to update the policy.

Results: Average return per patient was significantly higher in survivors than non-survivors, and a significant inverse relationship was observed between AI performance return and estimated 90-day mortality. Contrary to the current guidelines that recommend maintaining a glycemic range of 140-180 mg during ICU admission, AI most often recommended a glycemic range of 120-139 mg/dL for ICU patients. Analysis of mortality rate according to mean glucose level during ICU admission revealed that the greater the difference between AI recommendation and real glycemic control range, the higher the mortality rate.

Conclusion: These results suggest that tighter glycemic control, guided by a similar AI policy for daily individualized optimal glycemic target, may help improve ICU patient survival.

Disclosure

J.Yun: None. G.Lee: None. J.Kim: None. S.Ko: None. Y.Ahn: None. D.Kim: n/a. K.Song: n/a.
658-P: Gaps Remain for Achieving Guideline-Recommended and Individualized HbA1c Targets for People with Type 1 and Type 2 Diabetes Using Mealtime Insulin or Basal-Only Insulin
Authors: HANKOSKY EMILY R. , SCHAPIRO DAVID , GUNN KARLI B. , LUBELCZYK ELIZABETH , MITROI JESSICA , NELSON DAVID R.
Published: May 2022

Background: HbA1c is a primary measure of glycemic control and managing HbA1c may help reduce the risk of complications. This study aimed to describe trends in HbA1c by insulin regimen.

Methods: This was a retrospective analysis of cross-sectional surveys collected from the National Health and Nutrition Examination Survey between 2009-2018. Mean HbA1c and proportion achieving guideline- and HCP-recommended (i.e. personalized) HbA1c targets were evaluated in aggregate and over time in adults (18-64 years) with type 1 (T1DM) or type 2 (T2DM) diabetes using mealtime insulin (MTI) or basal insulin only. Trends over time between 2009-2018 were evaluated after adjusting for age, gender, race/ethnicity. The analysis included the strata, clusters, and weighting of the complex survey design.

Results: From 2009-2018, 26.1% of people with T1DM (weighted n=891,194; mean HbA1c [SE] 7.9% [0.2]) , 24.8% with T2DM MTI (weighted n=1,591,183; mean HbA1c [SE] 8.6% [0.2]) , and 11.2% with T2DM basal only (weighted n=1,087,895; mean HbA1c [SE] 8.6% [0.2]) achieved the ADA recommended HbA1c goal of <7%. Among those who reported personalized HbA1c goals, 28.7% (T1DM) , 9.5% (T2DM MTI) , and 17.1% (T2DM basal only) achieved their goals. After adjustment, the proportion of people achieving HbA1c <7% in the basal only group increased significantly over time (2009-2018; p=0.04) , driven by an increase in 2017-2018. Adjusted mean HbA1c for T2DM MTI significantly decreased during the 2009-2018 timeframe (p=0.003) , whereas no significant differences were seen in the other subgroups.

Conclusions: Across all insulin regimens based off the most recent NHANES data, ∼75-90% of individuals are not achieving ADA-recommended or personalized HbA1c goals. Emerging treatment tools (e.g. new technologies, advanced insulins, and time in range metrics) may facilitate improved diabetes outcomes.

Disclosure

E.R.Hankosky: Employee; Eli Lilly and Company, Stock/Shareholder; Eli Lilly and Company. D.Schapiro: Employee; Eli Lilly and Company. K.B.Gunn: Employee; Eli Lilly and Company. E.Lubelczyk: Employee; Eli Lilly and Company. J.Mitroi: None. D.R.Nelson: Employee; Eli Lilly and Company.

Funding

Eli Lilly and Company
661-P: Use of a Sequential Continuous Glucose Monitoring with or without Exercise Tracker on Glycaemic Control in Middle-Aged Patients with Diabetes Mellitus
Authors: KHOO CHIN MENG , HTIKE KYU , DAN YOCK YOUNG
Published: May 2022

This study examined if a sequential continuous glucose monitoring (CGM) program using a Freestyle Libre would improve glycaemic control with or without an exercise tracker among middle-aged (50 to 65 years) patients with type 2 diabetes. We randomized 94 subjects (mean 57±4 years and HbA1c 10.1±1.6%) into a group wearing CGM alone (CGM-alone, n=52) and another group wearing CGM and an exercise tracker (CGM-Fit, n=42) . We measured HbA1c at pre-randomization, at 4 months and 6 months from randomization. All subjects wore the CGM every 2 weekly sequentially for the first 6 weeks and received diabetes counselling and professional dietary advice based on the CGM profile. Diabetes treatment was adjusted by the diabetes educator as appropriately. Those in the CGM-Fit group received a Fitbit watch with app-based guidance on an exercise regime. At baseline (pre-randomization) , there was no between-group difference in the HbA1c levels. At 4-month post-randomization, the HbA1c improved by 1.6±1.5% in CGM-alone (p<0.05) and 1.9±1.7% in CGM-Fit group (p<0.05) . Compared to baseline, at 6-month post-randomization, the HbA1c improved by 0.8±1.7% in CGM-alone (p<0.05) and 1.6±1.6% in CGM-Fit group (p<0.05) group) . Between the 4-month and 6-month post-randomization, the HbA1c had increased by 0.8±1.1% in CGM-alone (P <0.05) but only 0.2±0.8% in CGM-fit group (P >0.05) . Overall, 42.4% of subjects had an increase and 39.4% a decrease in diabetes medication when reviewed by the diabetes nurse educator.

In summary, the use of sequential CGM (for 6 weeks) with DM counselling and dietary advice improved HbA1c significantly by a mean of 1.7%. However, this does not appear sustainable at 6 months of follow up. The use of an exercise tracker might be helpful to sustain the improvement in glycaemic control. The use of CGM can guide management in titrating diabetes medication to improve glycaemia.

Disclosure

C.Khoo: None. K.Htike: None. Y.Dan: None.

Funding

NUHS AHS Mission Fund
663-P: Improving Knowledge, Competence, and Confidence of Diabetologists and Endocrinologists and Primary Care Providers Related to CGM Use with Curriculum-Based Online Education
Authors: LARKIN AMY , SCHRAND JULIE , LE ANNE
Published: May 2022

Purpose: We sought to determine if a curriculum of online continuing medical education (CME) activities could improve the clinical knowledge, competence, and confidence of diabetologists and endocrinologists (D/Es) and primary care providers (PCPs) related to rtCGM.

Methods: The curriculum consisted of 5 online activities, all of which used repeated pairs pre-/post-assessment study design and McNemar’s test (P <.is considered significant) to assess educational effect. The activities launched from April 30, 20through March 16, 2020 and data were collected for up to 12 weeks for each activity.

Results: The education reached over 15,500 physicians, including 4,187 D/Es and 3,196 PCPs. Overall, knowledge improved by 15% among D/Es (N=598, P<.01) and 22% among PCPs (N=829, P<.01) and competence improved by 40% among D/Es (N=228, P<.01) and 21% among PCPs (N=307, P<.01) . 29% relative increase in knowledge among D/Es (P=.059) and 36% relative increase in knowledge among PCPs (P<.01) related to the role of CGM in type 2 diabetes (T2D) . 7% relative increase in knowledge among D/Es (P<.01) and 14% relative increase in knowledge among PCPs (P<.01) related to fundamentals of rtCGM. 40% relative increase in competence among D/Es (P<.01) and 21% relative increase in competence among PCPs (P<.01) related to optimal use of CGM in pregnancy. 37% of D/Es and 42% of PCPs had a measurable increase in confidence (both P<.01) , and among those the average level of confidence increased 52% for D/Es and 73% for PCPs.

Conclusion: While this curriculum demonstrated success in educating on this topic, some gaps still remain after education. 37% (D/Es) and 40% (PCPs) of the questions assessing knowledge on the role of CGM in T2D and 21% (D/Es) and 37% (PCPs) of questions on fundamentals of CGM were still incorrectly answered after education, demonstrating a need for more education.

Disclosure

A.Larkin: None. J.Schrand: None. A.Le: None.

Funding

Developed through an independent educational grant from Dexcom
664-P: Success of Interactive, Online Education Related to Interpretation and Application of AGP Data
Authors: LARKIN AMY , LACOUTURE MICHAEL , LE ANNE
Published: May 2022

Objective: We sought to determine if interactive, case-based, online continuing medical education (CME) could improve the competence and confidence of diabetologists/endocrinologists (D/Es) and primary care physicians (PCPs) related to interpreting and applying ambulatory glucose profile (AGP) data to patient management regimens for T2D.

Methods: Educational design included a “test, then teach” approach to elicit cognitive dissonance, with evidence-based feedback provided following each learner response. A repeated pairs pre-/post-assessment study design and chi-square test (P <.is considered significant) assessed educational effect, with Cramer’s V being used to assess educational impact (0.06-0.15 is a noticeable effect, 0.16-0.26 considerable, and >0.26 extensive) . The activity launched May 11, 2021 and data were collected through August 12, 2021.

Results: In total, 94 D/Es and 576 PCPs were included in the analysis. Matched learner data indicate that overall, 29% D/Es learners’ responses and 36% of PCPs learners’ responses improved from pre-to-post (both P<.with extensive overall impacts 0.267-0.293) . On a question-level: 34% of D/Es (P<.01, V=.343) and 46% of PCPs (P<.01, V=.402) improved at selecting the medication adjustment most appropriate based on a patient’s AGP data. 24% of D/Es (P<.01, V=.19) and 26% of PCPs (P<.01, V=.183) improved at currently interpreting the AGP. Overall, 23% of D/Es and 37% of PCPs reported increased confidence in iCGM in patients with T2D.

Conclusion: This study demonstrates the success of interactive, case-based, online CME on improving competence and confidence of D/Es and PCPs related to interpretation and application of AGP data. Case-based education with interactive polling questions and detailed explanations related to best choices should be employed more often to help clinicians apply knowledge/data into practice to improve patient management and care.

Disclosure

A.Larkin: None. M.Lacouture: None. A.Le: None.

Funding

Developed through an independent educational grant from Abbott Diabetes Care
676-P: Difference in CGM Estimated Hemoglobin A1c in Adults with Type 1 and Type 2 Diabetes
Authors: SALAM MAAMOUN , BAILEY RYAN , CALHOUN PETER , MCGILL JANET B. , BECK ROY , PRICE DAVID A.
Published: May 2022

The relationship between mean glucose measured using a continuous glucose monitor (CGM) and hemoglobin A1c (A1C) was evaluated in adults with type 1 diabetes (T1D) or type 2 diabetes (T2D) . Data from participants enrolled in the MOBILE, DIAMOND, and WISDM trials and randomized to the CGM arm were used in the analysis. Follow-up visits collected A1C measured by a central laboratory at 8 months post-randomization in the MOBILE study and 6 months post-randomization in DIAMOND and WISDM studies. CGM data collected in the 91 days prior to the follow-up visit, when glucose control was thought to be relatively stable, was used to compute mean glucose. A least squares linear regression model estimated A1C using mean glucose as a predictor, and models were fit separately by diabetes type. 199 participants with T1D and 175 participants with T2D were included in the analysis. Mean age was 57±15 years among those with T1D and 58±years among those with T2D. Estimated A1C was similar but slightly higher for participants with T2D vs. T1D for the same mean glucose (Table) . Analyses restricting to White non-Hispanic cohort yielded similar results. Spearman partial correlation coefficients for mean glucose vs. A1C were 0.76 for T1D and 0.84 for T2D. Estimates of A1C based on CGM measured mean glucose were slightly higher for those with T2D compared with T1D.

Disclosure

M.Salam: Advisory Panel; Lilly Diabetes, Consultant; Neurocrine Biosciences, Inc., Research Support; Mylan N.V., Neurocrine Biosciences, Inc. R.Bailey: None. P.Calhoun: None. J.B.Mcgill: Advisory Panel; Gilead Sciences, Inc., Lilly Diabetes, MannKind Corporation, Novo Nordisk A/S, Provention Bio, Inc., Salix Pharmaceuticals, Consultant; Bayer AG, Boehringer Ingelheim International GmbH, Research Support; Dexcom, Inc., Novo Nordisk. R.Beck: Consultant; Diasome, Eli Lilly and Company, Insulet Corporation, Novo Nordisk, Research Support; Ascensia Diabetes Care, Beta Bionics, Inc., Bigfoot Biomedical, Inc., Dexcom, Inc., Eli Lilly and Company, Medtronic, Novo Nordisk, Roche Diabetes Care, Tandem Diabetes Care, Inc. D.A.Price: Employee; Dexcom, Inc.
684-P: Tracking Type 2 Diabetes Progression Using CGM Systems
Authors: SCHIAVON MICHELE , DALLA MAN CHIARA
Published: May 2022

Disposition index (DI) is an index quantifying the quality of glucose control, usable to track disease progression. It is usually calculated as the product of beta-cell function and insulin sensitivity, assessed, in hospitalized setting, either from clamp data, surrogate indices or model-based methods, like the Oral Minimal Model (OMM) . The increasing use of continuous glucose monitoring (CGM) systems, even in individuals with type 2 diabetes (T2D) , opens the door to the use of such devices to monitor glucose control in outpatients. Here, we propose a method to assess DI from CGM data, validated it against OMM and proved its usability to track disease progression. We studied 100 early stage (ES) and 100 advanced stage (AS) subjects with T2D of the Padova T2D simulator, matched for age (54 [42,75] y) and different BMI (33 [29,37] vs. 31 [28,34] kg/m2; p=0.016) , which underwent a mixed meal challenge (75g of carbohydrates) while wearing CGM.

Plasma glucose, insulin and C-peptide concentrations were measured for 6 hours after the meal and used for the estimation of the DI with the OMM (DIMM) , while CGM sensor data were used to calculate DI with the sensor-based method (DISB) .

DISB well correlated with DIMM (ρES = 0.81 and ρAS = 0.77; p<0.001) and both were significantly lower in AD than ES (p<0.001, Fig. 1) .

We conclude that DISB is usable to assess DI in subjects with different stage of T2D wearing CGM and thus, potentially, to track disease progression in noninvasive way.

Disclosure

M.Schiavon: None. C.Dalla man: Research Support; Becton, Dickinson and Company, Sanofi-Aventis Deutschland GmbH.

Funding

MIUR (Italian Minister for Education) under the initiative "Departments of Excellence" (Law 232/2016)
687-P: Changes in HbA1c after Initiating Real-Time Continuous Glucose Monitoring (rtCGM) for Primary Care Patients with Type 2 Diabetes
Authors: SHIELDS STEPHEN , NORMAN GREGORY J. , CIEMINS ELIZABETH L.
Published: May 2022

Background: Many patients with type 2 diabetes (T2D) have suboptimal control and are not meeting their glycemic targets. Use of CGM devices has increased substantially for patients with T2D. However, the effects of rtCGM on glycemia in T2D primary care patients, particularly those not on intensive insulin therapy, in real world settings has not been well studied.

Materials and Methods: This retrospective observational study examined data from 13 U.S. health systems and multispecialty medical groups. Personal rtCGM use was determined from prescription codes. The cohort included patients with a diagnosis for T2D and ≥1 outpatient visit with a primary care provider (PCP) in the 18 months prior to rtCGM use. The outcome was change in hemoglobin A1c (A1c) from baseline to 3-9 months after rtCGM initiation. The cohort was stratified into two groups based on baseline A1c (A1c >7.5 and A1c ≤7.5) .

Results: Between August 1, 2015, and September 30, 2020, 458 T2D patients initiated rtCGM (mean age 61, 50% female, 84% white, 50% commercial insurance, and a mean of 3.7 PCP visits in the prior year) . Of the 458 patients, 64 (14%) were prescribed antidiabetes drugs but not insulin (NIT) , 51 (11%) were prescribed basal but not bolus insulin (NIIT) , and 343 (75%) were prescribed bolus insulin, with or without basal insulin (IIT) . Univariate analysis of change in A1c showed for those with a baseline A1c >7.5 (n=306, 67%) , A1c changed an average of -0.9% (95% CI -0.7, -1.1, p<.001) and varied by diabetes management regimen: NIT -1.13% (SD=2.3%) , p<.01; NIIT -1.59% (SD=2.3%) , p<.001; IIT -0.76% (SD=1.6%) , p<.001. For those with a baseline A1c ≤7.5 (n = 152, 33%) , change in A1c was not statistically significant (0.12%, p=.123) .

Conclusions: These findings suggest, for poorly controlled patients with T2D, regardless of therapy regimen, rtCGM use improved glycemic control. This real-world evidence supports further studies of the benefits of rtCGM in the broader T2D population.

Disclosure

S.Shields: None. G.J.Norman: Employee; Dexcom, Inc. E.L.Ciemins: None.
690-P: Deterioration in Glycemic Control on School Days among School-Aged Children with Type 1 Diabetes: A Continuous Glucose Monitoring–Based Study
Authors: WU XIUMEI , ZHANG WEN HAO , DING YU , ZHENG XUEYING , WENG JIANPING , LUO SIHUI
Published: May 2022

Background: Children with type 1 diabetes (T1D) spend more time in school when they turn school age. The impact of such transition on glycemic control remains unclear. We aimed to investigate the impact of school life by comparing the glycemic control between holidays and schooldays in school-aged children with T1D.

Methods: This observational study collected data from school aged T1D children with continuous glucose monitoring (CGM) data from September 20to July 2021. Eligible datasets should include CGM records for at least 3 schooldays and 3 holidays. Data providers’ demographic and lifestyle-related information were collected via questionnaires. We compared the CGM metrics between schooldays and holidays using paired T-test.

Results: A total of 78 school aged children with T1D were included (40 boys, median age 9.75 years, median diabetes duration 2.20 years) . 142,945 hours of CGM data were analyzed. Overall, time in range (3.9-7.8 mmol/L, TIR) was better on holidays than that during schooldays [57.0% (SD 15.0%) vs. 55.9% (SD 15.1%) , p = 0.039] and time above range (>7.8mmol/L, TAR) was lower on holidays [35.8% (SD 15.5%) vs. 36.9% (SD 15.5%) , p = 0.085]. No significant difference was observed in time spent <3.9mmol/L or numbers of hypoglycemia events per week. Nocturnal glycemic deterioration could be attributed to a significantly longer nighttime (0am to 6am) TIR [60.4% (SD 17.1%) vs. 56.9% (SD 18.1%) , p = 0.001] and a shorter nighttime TAR [31.8% (SD 17.5%) vs. 35.6% (SD 18.5%) , p = 0.001] on holidays compared with those on schooldays, with no difference in daytime metrics. Stratified analysis revealed the nocturnal difference was more prone to children aged 6 to years, girls, and insulin pump users, while bedtime and midnight snacks had no impact.

Conclusion: Among school-aged children with T1D, deterioration in nocturnal glycemic control was found in schooldays and active adjustment in treatment is needed to improve schooldays glycemia.

Disclosure

X.Wu: None. W.Zhang: None. Y.Ding: None. X.Zheng: None. J.Weng: None. S.Luo: None.
696-P: Increasing CGM Use through Standardized Documentation
Authors: DELACEY SEAN E. , SULLIVAN NAOMI J. , FOGEL NAOMI R.
Published: May 2022

Continuous glucose monitor (CGM) use is known to improve glycemic outcomes for patients with Type 1 Diabetes, but uptake is not universal in the pediatric population. We hypothesized that requiring standardized documentation of CGM use and identification of barriers would increase awareness and identify potential targets for future interventions, ultimately increasing CGM use in our population. We designed standard documentation within the electronic medical record for outpatient visits to assess CGM use and barriers to use. The documentation collects data on CGM possession, %time in use, prescriptions, and barriers to use in patients with Type 1 Diabetes. Our intervention involved integrating the standard CGM documentation into diabetes note template thus automating completion by providers. Data was pulled from clinic days two weeks prior to intervention (100 patients) and another days, two months after intervention (74 patients) . Before intervention 83% of patients had a CGM compared to 87% of patients after intervention (p=0.51) . While 63% used a CGM >70% of the time before intervention, 73% of patients had >70% use post intervention (p=0.19) . Provider documentation was not universal with 12% and 4% of encounters with no documentation of time in use before and after intervention respectively. After standardization 7/patients without a CGM were prescribed one during the visit compared to 5/17 of patients prior. Barriers identified included (n) : insurance coverage (4) , skin adhesion/issues (3) , self-image (2) , lack of education /distrust (1) , technological issues (1) , resistance to wearables (1) , and other (3) . Our patient population had a high rate of CGM use. Two months after the intervention, both use of CGM and new prescriptions increased. The improvement may be related to increased awareness and addressal of CGM barriers among providers. The intervention provided insight on barriers to CGM use, such as skin/adhesion issues, that will be targeted for future improvement.

Disclosure

S.E.Delacey: None. N.J.Sullivan: None. N.R.Fogel: None.

Funding

National Institute of Diabetes and Digestive and Kidney Diseases Ruth L. Kirschstein National Research Service Award T32 DK007169 and T1D Exchange
704-P: Time in Range and Time Below Range in Insulin-Treated Older Adults with Type 2 Diabetes
Authors: LEITE SILMARA A.O. , SILVA MICHAEL , LAVALLE ANA C.R. , BASTOS MURILO , BERTOGY MARIA C. , VIEIRA SUELEN C. , UMPIERREZ GUILLERMO E.
Published: May 2022

Hypoglycemia is the key limiting step for optimizing glycemic control in older adults. Continuous glucose monitoring (CGM) technology has not been well-evaluated in insulin treated older patients with type 2 diabetes (T2D) .

Methods: This prospective observational cohort study assessed of glycemic control using the FreeStyle Libre Flash CGM in insulin treated older adult patients with T2D. Subjects >65 years with T2DM on insulin therapy and HbA1c between 7% and 9%, with or without oral agents, were identified from a public hospital and a private diabetes clinic and invited by phone to participate (n= 462) . Patients treated with GLP1 agonists; eGFR <30 ml/min; Hb <11g/dL; ALT> 3x ULN; glucocorticoid use in the previous 3 months, and active malignancy were excluded. Participants worn the CGM continuously during a 6-weeks study period. They returned to clinic every 2 weeks for CGM data downloaded and new CGM placement, assessment of glycemic control and hypoglycemia. The investigators adjusted insulin treatment at each visit as needed. The first 2 weeks of CGM was considered baseline point and the last 2 weeks was the endpoint. The differences on time in range (TIR 70-180, mg/dl) and time below range (TBR, < 70 mg/dl) was tested using the Wilcoxon Signed-rank test with p <0.05.

Results: A total of 125 patients were randomized and 49 patients completed the 6 weeks follow-up (women=53.9%; age=72.8 ± 5.0 years; BMI=28.3±3.6 Kg/m2; eGFR=62.4 ± 16.6; ml/min A1c=8.0 ± 0.57%; GMI=7.1 ± 0.8%. The patients had a median TIR of 65% (min= 7%, max= 94%) at the baseline and 68% (min= 4%; max= 97%) at the endpoint. The median TBR was 3% (min= 0%, max= 23%) at the baseline and 2% (min= 0%; max= 18%) at the end of study. The TBR was significantly reduced after 6 weeks of CGM (p<0.01) .

Conclusions: An individualized approach may be possible using FreeStyle Libre Flash CGM to avoid overtreatment and undertreatment of older adults with T2D. CGM is a useful tool to reduce hypoglycemia in insulin older adults with T2D.

Disclosure

S.A.O.Leite: None. M.Silva: None. A.C.R.Lavalle: None. M.Bastos: None. M.C.Bertogy: None. S.C.Vieira: None. G.E.Umpierrez: Research Support; AstraZeneca, Dexcom, Inc., Novo Nordisk.

Funding

Abbott DiabetesCare (ADC-OUS-IIS-19-47)
708-P: Hypertension Control among People with Diabetes Using a Self-Management Multicondition Digital Platform
Authors: HERSHCOVITZ YIFAT , TAMIR MICHAL , MANEJWALA OMAR
Published: May 2022

Introduction: Digital multicondition platforms seek to assist persons with diabetes in management of their diabetes and comorbidities. Hypertension is reported in over two-thirds of patients with type 2 diabetes. Both are major risk factors for cardiac, stroke, and kidney disorders. Dario’s digital therapeutics platform for chronic conditions supports self-management of diabetes and high blood pressure. The platform enables digital evaluation of blood glucose and blood pressure levels in real time and supports interventions based on clinical indicators.

Method: A retrospective data evaluation was performed on the Dario data base since 2019. A population of active users who started with hypertension stage 1 as baseline was identified. Blood glucose and blood pressure readings were assessed at first month and 6th month of use. A subgroup of users who started at hypertension stage 2 was evaluated as well. Systolic, diastolic pressures and average blood glucose were evaluated along of the study.

Results: For the 2554 users identified with diabetes and hypertension, more than two thirds improved their systolic blood pressure by 13 mmHg (P<0.001; 144±14 to 131±13) . A group of 38.7% (N=990) moved to a lower hypertensive stage (P<0.001) . The subset of 1367 users with stage 2 hypertension improved their systolic blood pressure from 150±12.4 to 141±15.2 mmHg on average and 43.9% (N=600) improved their blood pressure by more than mmHg over six months (P<0.001) . A subgroup of 3users who started at high-risk blood glucose levels significantly reduced their blood glucose average by 15% over 6 months (232.4±46 to 198±65 mg/dL) (P<0.001) .

Conclusion: A multicondition digital therapeutic platform may promote behavioral modifications and result in sustainable improvements in both glycemic control and blood pressure levels. The study demonstrates an improvement in multiple chronic conditions (diabetes and Hypertension) for people using one digital platform.

Disclosure

Y.Hershcovitz: None. M.Tamir: None. O.Manejwala: Employee; DarioHealth Corp., Stock/Shareholder; DarioHealth Corp.
712-P: Suhoor Timing in T1DM Patients Fasting during Ramadan: A Randomized Crossover Trial
Authors: ALAMOUDI REEM , ALASSIRI MISHARY A. , ALJAWHRJI ABDULRHMAN , ALMAGHRABI MAZIN M. , BASULAYMAN DALIA S. , RAMADAN MAJED
Published: May 2022

IDF-DaR guidelines recommend late Suhoor (pre-dawn meal) , this does not give much time for correction and can lead to breaking the fast in the early hours.

Objective: To estimate Hypoglycemia risk in T1D fasting Ramadan when eating Suhoor 90-120 minutes before dawn versus 30 minutes before dawn.

Methods: Prospective randomized cross-over design. T1D insisting to fast recruited. Data collected using pre/post-Ramadan questionnaires, and FCGM - Freestyle Libre.

Results: 44 T1D patients randomized to early vs. late Suhoor regimens for a week then crossed to the other regimen the second week. 42 MDI and 2 CSII. Mean age 25 ±5.9 years (range 15-39) , DM duration 13.7 ±6.6 years, 73.5% female. Pre-Ramadan A1c ≤7 30.2%, and >9 20.9%. (22.7%) reported frequent hypoglycemia (≥3/week) , and 4 (9.1%) reported hypoglycemia unawareness.

During the early vs. late regimen self-reported hypoglycemia leading to breaking of fast 64.5% vs. 58.1%, p=0.18; occurring most commonly in: Morning (38.5%) vs. 14 (60.9%) , and noon 11 (42.3%) vs. 5 (21.7%) p=0.09. Mean days fast broken 2.5±1.6 vs. 2.05±1.4, p=0.7. One severe hypoglycemia, and one admission reported with the late regimen. No DKA admission during either regimen.

FCGM detected mean hypoglycemia events per patient per week of early vs. late regimen was 5.5 vs. 5.4, p=0.65; for post Suhoor (6 -11am) 0.94 vs. 1.07, p=0.25. Overall hypoglycemic events were significantly higher during morning/noon compared to pre-sunset 1.9 vs. 0.43, p<0.001.

AGP report: GMI 7.58 ±1.vs. 7.49 ±0.9, p=0.36, Time in range (70-180 mg/dl) 46.9 ±17.3% vs. 47.9 ±17.3%, p=0.99, Time below range (<70mg/dl) 8.6 ±14.3% vs. 7.8±7.6%, p=0.15, Time above range (>180mg/dl) 45.8 ±22.03% vs. 44.5 ±20.1%, p=0.6, and Glucose variability 39.3 ±10.5% vs. 40.6 ±6.5%, p=0.005.

Conclusion: Managing T1D who fast Ramadan is challenging. Adjusting Suhoor meal and insulin dose time to allow post meal correction provides flexibility. Larger studies needed to demonstrate effectiveness of this approach.

ClinicalTrials.gov: NCT04864483

Disclosure

R. Alamoudi: None. M.A. Alassiri: None. M.M. Almaghrabi: None. D.S. Basulayman: None.

Funding

KAIMRC