bluuebunny/crossref_metadata_2025 huggingface dataset:
1823-LB: DiaLOG—A Personalized and Interactive Diabetes Education Platform Empowered with Risk Assessment AI Algorithms and ChatGPT
Authors: LU JIQIAO , LU SHUYA , ZHAO YUBO , TSANG HILDA , HE DAIHAI , LI XIANG , YANG LIN
Published: June 2024

Introduction & Objective: The latest breakthrough of large language models offers a great opportunity to create personalized and interactive education tools for self-management of chronic conditions.

Methods: In this study, we developed an individualized and interactive diabetes education platform for Chinese populations with prediabetes, which consists of three key components: 1) a dashboard with individual records; 2) the AI algorithms for individualized risk prediction of type 2 diabetes mellitus (T2DM) incidence that were constructed and validated with 17-year territory-wide electronic health records (EHR) in Hong Kong; 2) a Chatbot empowered by chatGPT.

Results: We developed the clinically explainable prediction models using machine learning (ML) and deep learning (DL) techniques, for two-, five- and ten-year risk predictions in the sub-cohorts of 187,785, 99,853 and 17,301 patients, respectively. We found the Dense Layer Neural Networks (DNN) models achieved the best performance, with the area under receiver-operating curve (AUC) of 81.1%, 79.9%, 75.03% for two-, five- and ten-year risk prediction, respectively. The most significant predictors were fasting glucose and HbA1c, followed by creatinine, age at baseline, sex, potassium, triglyceride, and HDL-C. The DNN models achieved satisfactory performance in external validation. The developed models were then integrated into a web-based prediabetes self-management platform, named DiaLOG, as part of prompt engineering for interaction with ChatGPT.

Conclusion: Validated risk prediction models based on EHR data could be integrated into an AI-powered diabetes self-management platform, together with a ChatGPT-powered chatbot, to facilitate clinical decision and empower patients with self-risk assessments and individualized self-management advice.

Disclosure

J. Lu: None. S. Lu: None. Y. Zhao: None. H. Tsang: None. D. He: None. X. Li: None. L. Yang: None.
1829-LB: Cardiorenal-Metabolic Educational Program for Family Medicine Residents (CARE ME)
Authors: PESQUEIRA JUAN P. , SINGH PRABHPREET , VELEZ-DALLA TOR MAILI
Published: June 2024

Introduction and Objective: Cardio-renal-metabolic (CRM) diseases are prevalent among patients in family practice, yet primary care residents lack a specific curriculum on this new emerging topic. Addressing this gap and preventing practice inertia is crucial.

Methods: A prospective study compared two cohorts from family medicine residency programs with similar demographics, focusing on the effect of 25 one-hour CRM-focused lectures versus a standard curriculum. Lectures included Q&A sessions and case studies, delivered by specialists and residents. Using pre and post-questionnaires, the study primary endpoint aimed to determine the impact of an educational intervention on resident’s knowledge and patient care. The secondary endpoint aimed to determine the acceptance of the curriculum to drive future curricular changes and implementation.

Results: Analysis using a score-based model showed the intervention group improved significantly. Fisher's exact method was used in performing statistical analysis. The intervention group had a Total Pre-Score of 941 and a Total Post Score of 1258, an increase of 317 points. Important improvement scores rose by 25.2% (p-value 0.000), and overall positive response shifted by 33.4% (p-value 0.000) with 91.4% of respondents. Acceptance of the new curriculum was nearly 100%, indicating achievement of primary and secondary endpoints.

Conclusions: The study successfully met the primary and secondary endpoints. The curriculum significantly enhanced residents’ knowledge and confidence in managing CRM conditions, showing a preference for the new curriculum. This suggests potential benefits for patient outcomes and supports future curriculum implementation. The collaboration between programs promises to enhance education and patient care in primary care residents.

Disclosure

J.P. Pesqueira: None. P. Singh: None. M. Velez-Dalla Tor: None.
1843-LB: Prioritizing Representativeness—Recruiting before “Lost to Follow-up” Youth Living with Type 1 Diabetes (T1D) for a Virtual Family-Based Transition Readiness Intervention
Authors: SUHS MADELEINE C. , O'DONNELL ALEX , ELLIS JULIA , WEISSBERG-BENCHELL JILL , HARRIS MICHAEL A. , PAPADAKIS JACLYN L.
Published: June 2024

Introduction & Objective: Transition-aged youth with T1D represent a vulnerable population. Recruiting representative samples of these youth for psychosocial interventions is challenging and requires strategic efforts. Behavioral Family Systems Therapy for Diabetes Transition (BFST-DT) is an adapted, virtual, family-based intervention for improving transition readiness, and is currently being evaluated through a pilot intervention trial. The objective of this study is to (1) evaluate the representativeness of the recruited sample, and (2) compare recruitment strategies between those who consented and declined.

Methods: Thirty adolescents (16-18 years) with T1D and their parent(s) were recruited from a large urban hospital. Differences in demographic and health-related variables were assessed between the patient population and those who enrolled, declined, or were unresponsive.

Results: There were no differences between those enrolled, were unresponsive, and the patient population in age, gender, race, ethnicity, zip code-based income, A1c, CGM use, insulin delivery method, or comorbidities. Patients who declined were more likely to live in the city (versus suburban/rural areas) [X2 (1, N=41) = 5.8, p=.02]. Those who enrolled did so via phone (57.1%), email (23.8%), mailings (9.5%), and patient portal (4.8%). Those who declined did so via phone (85.4%), email (9.8%), and patient portal (4.9%), commonly citing no interest (41.5%) and lack of time (19.5%).

Conclusion: Recruitment strategies were effective in recruiting a representative sample of transition-aged youth with T1D. Findings have implications for recruiting and retaining populations that are challenging to engage in intervention research. Future research should prioritize the stratification of historically underrepresented groups during recruitment.

Disclosure

A. O'Donnell: None. J. Ellis: None. J. Weissberg-Benchell: Consultant; Beta Bionics, Inc. Advisory Panel; American Diabetes Association. Research Support; Juvenile Diabetes Research Foundation (JDRF), National Institute of Diabetes and Digestive and Kidney Diseases. J.L. Papadakis: None.

Funding

JDRF (4-SRA-2023-1287-M-B)
1844-LB: Community Engaged Research—Lessons Learned from a Pediatric Type 1 Diabetes Study
Authors: YANG CHIA-LUN , THOMAS COURTNEY , PRICE JULIA
Published: June 2024

Introduction and Objectives: Community engaged research (CER) involves partnering with community stakeholders (e.g., patients, families, providers) who are experts on their “lived experience” rather than only considering the researchers’ perspectives. However, pediatric type 1 diabetes (T1D) studies with a CER approach are limited. The current study employs CER to develop strategies to increase engagement of underrepresented families in T1D research. This abstract focuses on the lessons learned about the process of engaging with community partners on research.

Methods: Four CER expert consultants guided the recruitment of community partners, as well as development of partner meeting agendas and execution of meetings. Five adolescents with T1D and their caregivers and four T1D providers (1 endocrinologist, 2 advanced practice nurses, 1 pediatric psychologist) agreed to partner in this research project. During separate monthly meetings, family and provider partners provided feedback on research recruitment and data collection strategies.

Results: CER requires unique skills and ongoing support from experts across five areas, (1) recruitment of partners (clarity on time demand, nature of partner role), (2) planning meetings (creating clear, accessible meeting materials), (3) conducting meetings (supporting inclusive and respectful environment), (4) incorporating partner feedback in research strategy (interpreting partner comments, balancing feedback with science), and (5) maintaining partner engagement (responding to partner requests, sharing how feedback is or is not used).

Conclusion: Keys to successfully engaging and maintaining relationships with community partners in pediatric T1D research include consulting with CER experts, clearly sharing the purpose and intentions of partnerships, and highlighting how feedback is improving the project. Employing a CER approach is critical to increase the inclusivity and relevance of pediatric T1D research.

Disclosure

C. Yang: None. C. Thomas: None. J. Price: None.

Funding

National Institute of General Medical Sciences (P20GM144270)
1879-LB: Automated Self-Adjusting Subcutaneous Insulin Algorithm (SQIA) Improves Glycemic Control in Hospitalized Patients—Three-Year Experience
Authors: LEE GWENDOLYN , KOHN MICHAEL A. , ROV-IKPAH ESTHER , MEHTA PARAS , SAN LUIS CRAIG , JOHNSON CRAIG , KOLIWAD SUNEIL K. , RUSHAKOFF ROBERT J.
Published: June 2024

Introduction: Achieving inpatient glycemic control remains challenging. To meet this challenge, 3 years ago we implemented system wide use of our SQIA for patients who were NPO, on continuous tube feeds (TF), or on total parenteral nutrition (TPN). We previously showed in year 1, the number of orders a physician had to place while a patient was on the SQIA was reduced by a factor of more than 12, when compared with while a patient was on conventional insulin (CI) dosing. We now report the glycemic results from the first 3 years.

Methods: Our retrospective cross-sectional analysis at UCSF from 9/3/2020 to 9/2/2023 compares glucose measurements in adult, non-OB inpatients who were NPO, on TF, or on TPN and ordered for SQIA versus conventional physician-driven insulin adjustments. The 3-year study interval was divided into 3 periods defined by the dates of major optimization updates to the algorithm and programming. The ordering physicians were free to assign patients to SQIA or conventional insulin orders. We used Poisson regression with number of glucose measurements as the offset.

Results: Table 1

Conclusion: Selected now for 80% of eligible hospitalizations, SQIA, compared to CI, was associated with decreased hypoglycemia without an increase in hyperglycemia. With the SQIA, glucose improvements have continued while dramatically reducing burden for rewriting orders.

Disclosure

G. Lee: None. M.A. Kohn: None. E. Rov-Ikpah: None. P. Mehta: None. C. San Luis: None. C. Johnson: None. S.K. Koliwad: Other Relationship; National Institutes of Health. Advisory Panel; Signos. Stock/Shareholder; Signos. R.J. Rushakoff: None.
1884-LB: Real-World Impact of Once-Weekly Injectable Semaglutide (sema OW) vs. Sodium–Glucose Cotransporter 2 Inhibitors (SGLT2i) on HbA1c, Weight, and Health Care Resource Utilization (HCRU) Outcomes in Type 2 Diabetes (T2D)—An Observational Study (PAUSE)
Authors: AMAMOO JAMES , DOSHI RIDDHI P. , NOONE JOSHUA , XIE LIN , GAMBLE CORY L. , GUEVARRA MICO , DIVINO VICTORIA , CHEN JUSTIN , KING AARON A.
Published: June 2024

Introduction & Objective: This study aimed to assess the real-world impact of sema OW vs SGLT2i on HbA1c, weight and HCRU outcomes among patients (pts) with T2D in the US.

Methods: This observational study of adults with uncontrolled T2D (HbA1c ≥7%) initiating sema OW or SGLT2i (Jan 2018—Feb 2022; first prescription = index) used data from IQVIA PharMetrics® Plus and Ambulatory Electronic Medical Records databases. Changes in HbA1c, weight, BMI and all-cause medical HCRU outcomes after 1 year were compared among inverse probability of treatment weighting (IPTW) adjusted cohorts.

Results: Post-IPTW (sema OW: n=416; SGLT2i: n=1093) a significantly higher proportion of pts in the sema OW cohort had combined reductions in HbA1c/weight outcomes vs SGLT2i (Figure). The sema OW cohort had significantly greater mean decreases in HbA1c (-1.6 vs -1.2%, p<0.0001), weight (-4.4 vs -3.4 kg, p<0.0001) and BMI (-1.5 vs -1.1 kg/m2, p=0.013) vs SGLT2i. Over 1-yr follow-up, all-cause HCRU was similar between both cohorts (≥1 hospitalization: 6.0 vs 5.7%, p=0.8190; ≥1 ER visit: 15.2 vs 17.6%, p=0.2658; ≥1 physician office visit: 99.7 vs 99.1%, p=0.2134).

Conclusion: Sema OW was associated with greater improvements in HbA1c and weight vs SGLT2i, but with similar HCRU after 1 year.

Disclosure

J. Amamoo: None. R.P. Doshi: None. J. Noone: Employee; Novo Nordisk. L. Xie: None. C.L. Gamble: Employee; Novo Nordisk. M. Guevarra: Stock/Shareholder; Novo Nordisk. V. Divino: Employee; IQVIA Inc. J. Chen: None. A.A. King: Speaker's Bureau; Abbott, MannKind Corporation, Novo Nordisk. Advisory Panel; Novo Nordisk. Speaker's Bureau; Lilly Diabetes. Advisory Panel; Lilly Diabetes. Speaker's Bureau; Dexcom, Inc. Advisory Panel; Dexcom, Inc. Speaker's Bureau; Astellas Pharma Inc.

Funding

Novo Nordisk
1890-LB: Assessment of Clinical Practice Gaps Resulting in Clinical Inertia When Managing Type 2 Diabetes
Authors: LARKIN AMY
Published: June 2024

Introduction: Half of people with T2D meet treatment goals of A1c <7%. Understanding physician knowledge gaps and barriers to overcome clinical inertia with T2D is critical to improve training. Methods: A 25 multiple choice, knowledge- and case-based survey allowed participants to assess their clinical knowledge and performance. The survey was available online to physicians without monetary compensation or charge. Respondent confidentiality was maintained and responses were de-identified and aggregated prior to analyses. Data was collected October 2023 to February 2023. Results: In total, 771 PCPs, 386 NPs, and 210 PAs completed the assessment. These treaters were mostly in private practice (20%-32%) or in a multi-provider clinic (22%-34%) and estimate 26%-50% of their patients are currently meeting glycemic and weight management goals (27%-33%). Conclusion: This assessment of T2D treaters clinical knowledge and competence yielded important insights into gaps related to T2D treatment intensification. This activity was the 1st component of a larger initiative aimed at improving T2D treatment among first line (primary care) providers and ultimately improve patient outcomes, which will be measured with longitudinal knowledge, competence and performance assessments, and finally a real-world outcomes analysis of claims data for learners of the curriculum, which will be reported later in 2024 or early 2025.

Disclosure

A. Larkin: None.

Funding

Developed through independent educational grant from Lilly.
190-OR: Development and Validation of a Social Risk Screening Tool for Adults with Type 2 Diabetes
Authors: WILLIAMS JONI S. , WALKER REBEKAH J. , EGEDE LEONARD E.
Published: June 2024

Introduction & Objective: Social risk factors are the adverse social conditions associated with poor health including poor diabetes outcomes. Despite being important for assessing social needs and integrating social care into medical care, most measures that assess social determinants of health and social risk factors are lengthy and difficult to administer in clinical settings. Therefore, the objective of this study was to develop and validate a screening tool useful for identifying social risk factors and social needs among adults with type 2 diabetes.

Methods: Cross-sectional data from the comprehensive assessments of 615 adults with diabetes recruited from two primary care clinics were used for the analyses. The Kaiser Family Foundation Social Determinants of Health Framework was used as the theoretical basis for identifying and aligning measures across social risk domains of economic stability, neighborhood and physical environment, education, food, community and social context, and health care system. Each social risk factor was dichotomized in high and low risk. Factor analysis with orthogonal varimax rotation was used to identify latent variables underlying the social risk domains. Eigenvalue of 1 was used to identify number of factors. Factors loading at 0.5 and higher were included in the factor structure. Stata v16 was used for analyses.

Results: Twelve items were retained and loaded onto three domains that explained 100% of the variance: neighborhood factors (4 items: violence, crime, neighborhood rating, social isolation); psychosocial factors (5 items: food insecurity, depression, diabetes distress, psychological stress, perceived stress); and economic factors (3 items: financial hardship, high school education, literacy). Cronbach’s alpha of 0.7 indicated high reliability of the tool.

Conclusion: This screening tool will facilitate the identification of adults with diabetes, likely to have high social risks, to facilitate targeted interventions.

Disclosure

J.S. Williams: None. R.J. Walker: None. L.E. Egede: None.

Funding

NIH/NIDDK (R21DK123720, R01DK135838, R01DK118038, R01DK120861); NIH/NIMHD (R01MD013826, R01MD018012, R01MD017574)
1908-LB: A Machine-Learning Framework to Quantify Postprandial Glucose Responses in Gestational Diabetes
Authors: BARUA SOUPTIK , UPADHYAY DHAIRYA A. , SANGMO TENZIN , KHAN ARSALA , BERUBE LAUREN , LI LING-JUN , WILLIAMS SHAUNA , ROSEN TODD , RAWAL SHRISTI
Published: June 2024

Objective: Continuous glucose monitoring (CGM) provides a novel approach to monitor postprandial glucose responses (PPGR) in persons with gestational diabetes mellitus (GDM). We sought to develop a machine learning (ML) framework to identify PPGRs automatically from CGM data to address challenges of manual meal logging.

Methods: Adults 18+ years diagnosed with GDM were enrolled at 24-32 gestational weeks and wore a blinded Freestyle Libre CGM and logged meals for up to 14 days each over 3 visits. A random forest ML algorithm was trained to identify the first meal of the day from raw daily CGM profiles. Comparing self-recorded and ML-predicted PPGRs, the primary outcome was difference in start time of PPGR while the secondary outcomes were the ratio of the corresponding 2-hr and 3-hr area under the PPGR curves.

Results: We analyzed data from 19 participants with CGM and self-recorded meal logs (35 ± 6 years, 47% Asian or Black/African-American, 37% Hispanic/Latino). The ML algorithm predicted start time of PPGRs to within a median 30 [19,45] minutes of self-logged meal time (Fig 1). The median ratio of the corresponding 2-hr PPGR AUCs was 1.0 [0.98,1.03] and 3-hr AUCs was 1.0 [1.00,1.01].

Conclusion: An ML algorithm showed promising performance in identifying PPGRs accurately from CGM data in persons with GDM, enabling a new automated approach to meal logging and analyzing postprandial glucose patterns.

Disclosure

S. Barua: None. T. Sangmo: None. A. Khan: None. L. Berube: None. L. Li: None. S. Williams: None. T. Rosen: None. S. Rawal: Stock/Shareholder; Merck & Co., Inc., LabCorp, Pfizer Inc. Research Support; National Institutes of Health. Stock/Shareholder; Bristol-Myers Squibb Company.

Funding

Rutgers SHP Dean's Intramural Grant
1923-LB: FRONTIER—Flash Glucose Monitoring System Use in Ontario among Patients with DM in the ICES Database—Evidence from Real-World Practice
Authors: HARRIS STEWART B. , RABASA-LHORET RÉMI P. , RATZKI-LEEWING ALEXANDRIA , POON YEESHA
Published: June 2024

Introduction & Objective: Sensor-based glucose monitoring technology may reduce risks of hypoglycemia and DKA by providing people with DM key insights into their glucose variability and trends. This study investigated HbA1c and healthcare resource utilization (HCRU) before and after adoption of flash glucose monitoring in people with DM.

Methods: This longitudinal retrospective cohort study used the IC/ES database of publicly funded administrative health data in Ontario, Canada. The analysis cohort comprised 45,523 people with DM in groups aged < 66 or ≥ 66 years who had a first flash glucose monitoring claim between 16 Sep 2019 and 10 Apr 2021 (index date) and remained active on flash glucose monitoring for 24 months’ follow-up after the index date. ED visits and hospitalization were measured for 12 months before the index date and the last 12 months of follow-up. HbA1c data were taken from the last tests in each period.

Results: Mean HbA1c was significantly improved in both age cohorts (both p <.0001; Table); reductions were seen for both T1DM and T2DM, regardless of treatment used. Mean ED visits and hospitalization rates (overall, for DKA, and for hypoglycemia) improved significantly in both age cohorts, with no change in mean resource intensity weight.

Conclusions: HbA1c levels and HCRU were reduced 12-24 months after sensor-based technology initiation in patients with DM.

Disclosure

S.B. Harris: Consultant; Abbott. Research Support; Boehringer-Ingelheim. Consultant; Dexcom, Inc. Advisory Panel; Eli Lilly and Company. Consultant; Eli Lilly and Company, Novo Nordisk, Sanofi. Research Support; Novartis AG. Consultant; Bayer Inc. R.P. Rabasa-Lhoret: Other Relationship; Abbott, AstraZeneca, Bayer Inc., Boehringer-Ingelheim, Dexcom, Inc. Research Support; Diabetes Canada. Other Relationship; Eli Lilly and Company. Research Support; Cystic Fibrosis Canada, Canadian Institutes of Health Research, FFRD - Fondation Francophone pour la Recherche du Diabète. Other Relationship; Janssen Pharmaceuticals, Inc. Research Support; Juvenile Diabetes Research Foundation (JDRF). Other Relationship; Novo Nordisk, GlaxoSmithKline plc. Consultant; HLS Therapeutics Inc., Insulet Corporation. Speaker's Bureau; CPD Networks. Other Relationship; Medtronic. Consultant; Pfizer Inc. Speaker's Bureau; Tandem Diabetes Care, Inc. Other Relationship; Sanofi. Speaker's Bureau; Vertex Pharmaceuticals Incorporated. Research Support; SFD - Société Francophone du Diabète. A. Ratzki-Leewing: Research Support; Sanofi. Advisory Panel; Dexcom, Inc. Consultant; Abbott. Advisory Panel; Sanofi-Aventis U.S. Other Relationship; American Diabetes Association. Consultant; Novo Nordisk, Eli Lilly and Company. Y. Poon: Employee; Abbott.
1925-LB: Sustained Reduction in Blood Glucose Levels Reflecting Diabetes Remission in People with Type 2 Diabetes Using a Digital Health Platform
Authors: FUNDOIANO-HERSHCOVITZ YIFAT , BREUER ASHER INBAR , MANEJWALA OMAR
Published: June 2024

Attainment of remission from type 2 diabetes (T2D) is increasingly perceived as a treatment goal. Improvement in glycemic control can be attained through lifestyle intervention, potentially resulting in diabetes remission. Dario Health, a digital therapeutic platform, may assist in promoting lifestyle changes and support patients trying to achieve remission. A retrospective data analysis was performed on users with T2D who have reported not using insulin and were active on Dario platform >6 months during 2018-2024, measured their BG in the first month and >3 measurements in the last month. Monthly average blood glucose (AvgBG) and percentage of high readings (>180 mg/dL) versus baseline (first month) were evaluated Paired sample t-test was used for testing differences in AvgBG. A linear mixed-effects model was applied to evaluate the changes in AvgBG and high-readings percentage over time. Finally, a simple slope analysis was used for the interpretation of the interaction of AvgBG and high-readings percentage with lifestyle activities. A group of 7240 users was evaluated (Age 53.8 (SD ±24.6); 41% females). A ratio of 44% (3169/7240) reduced their last monthly AvgBG to <140 mg/dL (equivalent to estimated A1c of 6.5). A sustained AvgBG of <140 mg/dL for at least three consecutive months was observed in 70% (2223/3169) of the users reflecting diabetes remission. The AvgBG was reduced by 15% vs. baseline (P<.001) in this group. In addition, users at high-risk with a baseline AvgBG ≥183 mg/dL demonstrated significant reductions in AvgBG and high-readings percentage in their last month moderated by the number of monthly lifestyle activities (logging carbs, meals and physical activities) as revealed by the model (B=-.00, P=.02 and B=-.00, P=.002 respectively). This study exhibits the potential role of digital health technology to change individuals' behaviors during management of T2D and support patients to achieve remission.

Disclosure

Y. Fundoiano-Hershcovitz: Employee; DarioHealth Corp. I. Breuer Asher: None. O. Manejwala: Employee; DarioHealth Corp. Stock/Shareholder; DarioHealth Corp.
1952-LB: Impact of Automated Insulin Delivery Systems by Baseline HbA1c in Emerging Adults with Type 1 Diabetes
Authors: WATERMAN LAUREN A. , ALONSO GUY T. , SAKAMOTO CASEY , PYLE LAURA , FORLENZA GREGORY P. , SHAH VIRAL N. , COBRY ERIN C.
Published: June 2024

Introduction & Objectives:Use of automated insulin delivery (AID) systems can improve HbA1c in people with type 1 diabetes (T1D). Data are limited on the impact in emerging adults with higher baseline HbA1cs.

Methods:Retrospective chart review performed on 14-30 year olds with T1D ≥ 1 year duration, started on advanced AID systems (Control IQ, Medtronic 770G, Omnipod 5) after 2018. HbA1c at baseline and at 3 month intervals (max 24 months) following AID initiation were collected. Mixed model was fit for HbA1c values and time, adjusting for age, sex, diabetes duration, race/ethnicity, and insurance. Contrasts generated to compare HbA1cs at each time point. Participants were categorized by baseline HbA1c (<7%, 7-9% and >9%).

Results:HbA1c values (N=3137) were collected from 613 emerging adults with T1D (mean age 21.1±4.2 years, diabetes duration 10.8±6.0 years, male 44.5%, non-Hispanic White 76.8%). Mean HbA1c changed from 11.2% to 9.2% (baseline and 24 months) for HbA1c >9% (N=190); 8.3% to 7.9% for HbA1c 7-9% (N=314); and 6.5% to 6.8% for HbA1c <7% (N=109) (all p<0.001). The percent with HbA1c <7% improved from 17.9% at baseline to 32.2% and 34.2% (3 and 24 months).

Conclusion:AID initiation is associated with sustained improvements for those not initially meeting glycemic targets, particularly those with the highest HbA1cs. As most remained above target, additional strategies for improvement are required.

Disclosure

L.A. Waterman: None. G.T. Alonso: Advisory Panel; MannKind Corporation. C. Sakamoto: None. L. Pyle: None. G.P. Forlenza: Research Support; Abbott, Dexcom, Inc. Consultant; Dexcom, Inc. Research Support; Insulet Corporation. Consultant; Insulet Corporation. Research Support; Medtronic. Advisory Panel; Medtronic. Research Support; Tandem Diabetes Care, Inc. Consultant; Tandem Diabetes Care, Inc. V.N. Shah: Consultant; Dexcom, Inc., Insulet Corporation. Research Support; Insulet Corporation. Advisory Panel; Novo Nordisk. Research Support; Novo Nordisk. Advisory Panel; Sanofi, Medscape. Consultant; embecta, Tandem Diabetes Care, Inc. E.C. Cobry: Advisory Panel; Dexcom, Inc. Other Relationship; Dexcom, Inc.

Funding

National Institutes of Health (5T32DK063687)
1956-LB: Altered Gut Microbiota and Short-Chain Fatty Acids in Children with Diabetic Ketoacidosis at Onset of Type 1 Diabetes
Authors: NI YAN , LIU YARU , LIN HU , DONG GUANPING , FU JUNFEN
Published: June 2024

Objective: Diabetic ketoacidosis (DKA) stands as the most common acute hyperglycaemic complication with relatively high mortality rate among children diagnosed with type 1 diabetes (T1D). Previous studies have shed light on gut dysbiosis in newly-onset T1D children, but research specifically targeting the gut microbiota and microbial metabolites in patients with DKA remains scarce.

Methods: Shotgun metagenomic analysis was conducted on fecal samples of 90 healthy children (HC) and 96 newly diagnosed T1D children, including 32 patients who presented with DKA upon admission. Additionally, short-chain fatty acids (SCFAs) were quantified using GC/MS.

Results: Gut microbiome indicated evident differences between T1D and healthy controls. At baseline, the phylum Bacteroidetes exhibited predominance in the DKA subgroup, while Firmicutes prevailed in the children without DKA. Compositional analysis unveiled increased levels of enteroviruses in the DKA group, encompassing Staphylococcus aureus and Streptococcus viridans, among others. Concurrently, various SCFA-producing microbiota (Anaerobutyricum, Dialister, Ruminococcus, Roseburia, Dorea, and Butyricicoccus) were significantly reduced in the DKA group. Correspondingly, targeted metabolomics analysis further corroborated significant reductions in the concentrations of SCFAs in children with DKA. Subsequent Spearman correlation analysis revealed the significant correlations between clinical parameters indicative of disease severity (bicarbonate, pH, urinary ketone, HbA1c), SCFAs, and SCFA-producing microbiota.

Conclusions: We reported a reduction of SCFAs and SCFA-producing bacteria in the fecal samples of T1D children experiencing DKA at onset. Our findings suggest a potential therapeutic avenue involving the modulation of gut microbiota and associated SCFA metabolism in the pathogenesis of T1D and onset DKA.

Disclosure

Y. Ni: None. H. Lin: None. G. Dong: None. J. Fu: None.

Funding

This study is funded by the National Key Research and Development Program of China (2021YFC2701901 and 2021YFC2701904) and Zhejiang Provincial Key Science and Technology Project (LGF21H070004).
1962-LB: Intrauterine Exposure to Gestational Diabetes and the Developing Brain
Authors: CHAKRAVARTTI SANDHYA P. , GAO XING , XIANG ANNY , PAGE KATHLEEN A.
Published: June 2024

Intrauterine exposure to gestational diabetes mellitus (GDM) is associated with an increased risk for adverse metabolic and cognitive outcomes, but the mechanisms are not clear. We tested the hypothesis that exposure to GDM is associated with changes in adiposity and brain trajectories during childhood to adolescence. Participants were 204 children (110 GDM exposed; 94 unexposed; 61% female; age 7-11 at baseline). Children underwent brain MRIs up to 4 times over 6 years. Adiposity measurements were obtained yearly over 6 years. Adiposity measures and FreeSurfer-derived brain volumes were compared between GDM-exposed and unexposed groups using mixed-effect models. We observed significant non-linear trajectories of BMI, body fat %, and waist circumference by age (all adjusted for sex and pubertal stage, p<0.0001) across all children. BMI (p=.058), body fat% (p<.049), and waist circumference (p<.015) trajectories varied by GDM exposure, with higher adiposity markers for GDM exposed vs unexposed. Compared to unexposed children, children exposed to GDM before 26 weeks had increased growth of total cortex (p<.009) and grey matter volume (p<.009), adjusted for age, sex, and pubertal stage, and multiple comparisons. Intrauterine exposure to GDM affects both adiposity and brain trajectories in transitioning from childhood to adolescence. These findings suggest a mechanistic link between GDM exposure and risk for adverse metabolic and neural outcomes.

Disclosure

S.P. Chakravartti: None. X. Gao: None. A. Xiang: None. K.A. Page: None.

Funding

American Diabetes Association (1-14-ACE 36); 1F31DK137584-01A1, R01DK116858, R01DK134079
1965-LB: Metabolomic and Transcriptomic Signatures of Gestational Diabetes Mellitus (GDM) Suggest Nutritional and Inflammatory Pathways in Intergenerational Transfer of Risk
Authors: THAKER VIDHU V. , FIRESTEIN MORGAN , MASSON CYNTHIA , LIU ZHONGHUA , REDDY UMA , GALLAGHER DYMPNA , LEDUC CHARLES A.
Published: June 2024

Introduction & Objective: GDM impacts intergenerational transfer of metabolic risk. The underlying mechanisms could inform intervention strategies. The placenta nourishes the developing fetus and is influenced by the maternal milieu. We assessed placental transcriptome and cord blood metabolites to determine pathways perturbed by GDM.

Methods: Placental tissue and cord blood from 39 mother-baby dyads of gravidas with BMI < 25 kg/m2 (controls, n= 13), obesity (BMI > 30 kg/m2, n=14) and GDM (n=12) were used. RNA sequencing of placenta tissue and metabolite profiling of cord plasma were performed (LC-MS, HILIC-positive and C18 negative modes). Cord blood c-peptide and fructosamine concentrations were measured by ELISA.

Results: Pregnancy age was similar across the groups (34.0 [5.7] years, p =0.35); pre-gravida BMI (p < 0.01) and gravidity (p = 0.01) were higher for obesity/GDM; but not offspring birthweight (p = 0.76). The GDM and obesity placental transcriptomic showed upregulation of intracellular protein transport, steroid hormone signaling, cellular cycle processing, histone modification and methylation, DNA alkylation and methylation compared to controls (FDR < 0.05). Metabolite pathways related to biopterin, arachidonic acid, amino acids (tyrosine, histidine, alanine, aspartate, tryptophan), urea cycle and vitamins (B6, B1, B2 and biotin) were upregulated with obesity and GDM (FDR < 0.05). Cord plasma fructosamine was elevated (p <0.01); c-peptide was higher in obesity/GDM, but not statistically significant (p =0.17). INSR expression was higher in obesity/GDM.

Conclusions: Placental transcriptomic changes, nutrient transport abnormalities, and inflammatory processes, potentially driven by maternal hormones, may significantly impact methylation and other epigenetic changes. These changes provide a mechanistic hypothesis for the intergenerational inheritance of metabolic risk.

Disclosure

V.V. Thaker: None. M. Firestein: None. C. Masson: None. Z. Liu: None. U. Reddy: None. D. Gallagher: None. C.A. LeDuc: None.

Funding

Naomi Berrie Diabetes Research Center Pre-Translational Research Award, Columbia University to VVT and CAL
198-OR: Should We Improve or Replace the Antenatal Oral Glucose Tolerance Test for Diagnosis of Gestational Diabetes?
Authors: KUSINSKI LAURA C. , JONES DANIELLE , BARKER PETER , BURLING KEITH , HALSALL IAN , MEEK CLAIRE L.
Published: June 2024

Introduction: Gestational diabetes, the most common medical complication of pregnancy, is diagnosed using an oral glucose tolerance test (OGTT), which has limited accuracy, reproducibility and practicality. Pre-analytical processing of glucose influences diagnosis rates, but the effect of this on a population level is unknown. We assessed how many cases of gestational diabetes were missed through suboptimal specimen processing, and if replacing the OGTT with a 28-week HbA1c was a suitable alternative for identification of hyperglycemia pregnancies.

Methods: We used data from a prospective cohort, the observational study of pregnancy hyperglycemia, endocrine causes, lipids, insulin and autoimmunity (OPHELIA), which included pregnant participants from nine UK centres recruited at the time of a 75g antenatal OGTT (criteria of the National Institute of Health and Care Excellence). Standard glucose processing (local procedures) was compared to enhanced glucose processing (storage on ice, rapid centrifugation, aliquoting and freezing <2.5 hrs).

Results: We recruited 1308 participants of mean age 31.5 years (SD 5.0) and BMI 33.0kg/m2 (6.8) of 82.5% white ethnicity, representative of the UK population. Enhanced glucose processing resulted in glucose levels ~0.6 mmol/L (10.9 mg/dL) higher than standard processing, associated with an increase in gestational diabetes diagnosis from 9% to 22%. The 13% of women who had a missed diagnosis due to standard specimen processing were not representative of the whole cohort: they were more likely to be of white ethnicity with BMI >30 kg/m2. HbA1c was not associated with most relevant pregnancy outcomes and receiver operator curves (ROC) demonstrated that the HbA1c was not a strong predictor of gestational diabetes diagnosis (AUROC 0.74; 95%CI 0.68 to 0.79).

Conclusions: Neither an oral glucose tolerance test with standard glucose processing nor 28-week HbA1c offers consistently accurate diagnosis of gestational diabetes.

Disclosure

L.C. Kusinski: None. D. Jones: None. P. Barker: None. K. Burling: None. I. Halsall: None. C.L. Meek: Research Support; Dexcom, Inc.

Funding

NIHR Cambridge BRC; Diabetes UK Harry Keen Intermediate Clinical Fellowship (17/0005712); EFSD-Novo Nordisk Foundation Future Leader's Award (NNF19SA058974)
1998-LB: Previously Frozen Beta-Cell Transcriptional Response to Cytokine Treatment Mirrors That of Fresh Beta Cells
Authors: ORCHARD PETER , WANG XIAOOU , YAN TINGFEN , NARISU NARISU , ROBERTSON CASSIE , ERDOS MICHAEL , MENG JERRY , COLLINS FRANCIS S. , CHEN SHUIBING , PARKER STEPHEN C.
Published: June 2024

Introduction & Objective: Proinflammatory cytokines contribute to pancreatic beta cell death and dysfunction underlying Type I Diabetes (T1D) pathogenesis. We previously used 10X Genomics single-nucleus RNA-seq (snRNA-seq) and multiome sequencing (snRNA-seq and snATAC-seq from the same nucleus) to profile the transcriptional response of pancreatic islet cell types to cytokine treatment (IL-1B and TNF-a; N=6 treated and 6 untreated). Fresh islets were used; however, it would be convenient to use frozen islets to examine beta cell response to cytokines. In the current study, we sought to determine whether beta cells of frozen islets showed a similar transcriptional response to cytokines as those from fresh islets.

Methods: We selected frozen islet samples from three donors. After thawing, one sample from each donor was treated with cytokines as in our previous study and one sample from each donor was left untreated; samples were then re-frozen and underwent single-nucleus multiome profiling using a pooled design to minimize batch effects. We used Seurat to cluster nuclei and identify beta cells, and performed a differential gene expression analysis (DESeq2) on pseudobulk expression between the treated and untreated beta cells from each donor.

Results: 3,758 of 5,228 pass-QC nuclei were beta cell nuclei. 3,693 of 18,436 tested genes were differentially expressed (DE) between the conditions (5% FDR). There was significant overlap between DE genes in the current study and in the fresh islet study (two-sided Fisher’s Exact test p = 2.6x10-250, odds ratio = 14.5). Of 827 DE genes in the fresh islet study that were also tested in the current study, 794 (96.0%) showed the same direction-of-effect in the current study (regardless of significance; two-sided Fisher’s Exact test p = 3.4x10-173, odds ratio = 647.8).

Conclusion: Frozen islets show a similar transcriptional response to cytokines as fresh islets, suggesting they are appropriate to use in future research studies on this topic.

Disclosure

P. Orchard: None. X. Wang: None. T. Yan: None. N. Narisu: None. C. Robertson: None. M. Erdos: None. J. Meng: None. F.S. Collins: None. S. Chen: None. S.C. Parker: Research Support; Pfizer Inc.

Funding

National Institute of Diabetes and Digestive and Kidney Diseases (U01DK127777)
2002-LB: New Model for Type 1 Diabetes Differential Screening
Authors: MENDIZABAL LEIRE , SASO-JIMÉNEZ LAURA , APAOLAZA NAIARA , MARTÍNEZ ROSA , ZULUETA MIRELLA , URRUTIA INÉS M. , SIMON LAUREANO , CASTANO LUIS
Published: June 2024

Introduction & Objective: Determining whether a patient has type 1 (T1D), type 2 (T2D) or monogenic diabetes is an important diagnostic and therapeutic concern. Recent successes in T1D disease-modifying therapies to impact the course of early-stage T1D have ignited the consideration of the need for and feasibility of population screening to identify those at increased risk of T1D. Our objective was to develop a non-invasive method for early differential screening of individuals with increased susceptibility to T1D based on a Polygenic Risk Score (PRS).

Methods: We analyzed a retrospective cohort of 1,911 individuals (475 controls, 486 T1D, 464 T2D, 486 MODY) from Hospital Cruces (Bilbao, Spain). Training (70%) and validation (30%) sets were established. A total of 306 SNPs were selected after exhaustive exploration of databases published to date of SNPs associated with T1D and T2D. Chi square test and Pearson correlation analysis preceded development of a multinomial logistic regression model and a combination of binomial models. Models’ performance was assessed by receiver operating characteristic (ROC) curve in training and validation data sets.

Results: We developed a Multinomial PRS Model that differentially discerns T1D susceptibility from susceptibility to other diabetes types and controls with an AUC of 0.87, 81% sensitivity and 83% specificity.

Conclusions: This new tool for T1D differential screening shows the possibility to discriminate susceptibility to T1D versus no susceptibility and susceptibility to other diabetes types. It may aid in management of clinical and population strategies to best assist those at increased T1D susceptibility.

Disclosure

L. Saso-Jiménez: None. N. Apaolaza: None. R. Martínez: None. M. Zulueta: None. L. Simon: None.

Funding

This study was supported by grants from the Department of Health of the Basque Government (GV2019111064) and the University of the Basque Country UPV/EHU (IT1739-22). Laura Saso is the recipient of a predoctoral grant from the Education Department of Basque Government (PRE_2023_2_0084).
2037-LB: Fumarate Hydrataseorchestrates Hepatic Steatosis via ULK1-Mediated Lipophagy
Authors: JIANG HAOWEN
Published: June 2024

Hepatic lipid homeostasis is coordinated by various metabolic pathways, such as lipogenesis, lipid uptake, storage, and oxidation. However, the underlying mechanism that orchestrates metabolic crosstalk remains unclarified. Herein, we demonstrated that fumarate hydratase (FH) functioned as an indispensable adaptor governing mitochondria metabolism and lipid droplets (LDs) degradation. Hepatic FH overexpression prevented hepatic steatosis in normal mice and ob/ob mice without interfering mitochondrial lipid oxidation and lipogenesis. Strikingly, we found that FH selectively activated lipophagy-mediated LDs lipidolysis. Mechanistically, FH interacted with ULK1 and stabilized ULK1 through preventing its ubiquitination and degradation, resulting in lipophagy activation and the elimination of hepatic lipid accumulation. Meanwhile, hepatic ULK1 deficiency abrogated the protective effects in FH-overexpressing mice. Also, we clarified that the interaction between FH and ULK1 occurred in cytoplasm, but not in mitochondria. Cytoplasmic FH was sensitive to lipids and downregulated without affecting mitochondrial FH in vivo. Moreover, the FH-ULK1 axis was identified closely associated with hepatic steatosis in human patients. Taken together, our research demonstrates a “two-side” insight of FH on hepatic lipid metabolism and provides a promising strategy for fatty liver treatment.

Disclosure

H. Jiang: None.

Funding

This work was supported by grants from the National Natural Science Foundation of China grants (82273983, 82130099, and 92253306), National Key R&D Program of China (2022YFA1303800), Science and Technology Commission of Shanghai Municipality (23ZR1474700).
205-OR: Association of Geographic Factors with Use of Metabolic Disease Specialty Care among Adults with Type 2 Diabetes and ASCVD
Authors: BAUER JESSICA , ROTHENBERGER SCOTT D. , JOHNSON AMBER E. , ROSLAND ANN-MARIE , KINNEE ELLEN , ZUPA MARGARET
Published: June 2024

Metabolic disease specialty care (endocrinology or cardiology) for T2D and ASCVD may improve quality of care and clinical outcomes. However, little is known about the associations of patient demographics and geographic, transportation, and technological barriers with use of specialty care.

In this retrospective cohort study, we linked geospatial and patient-level data for adults with T2D and ASCVD who had ongoing primary care in a large health system from 1/2018 to 6/2022. Patients were mapped to their residential ZIP Code centroids. Multivariate logistic regression assessed associations between baseline community predictors (public transit access, walkability, cellular data access) which were converted to within-cohort percentile rank, and patient predictors (distance from specialty clinic, demographics) with any specialty care visit.

Our cohort included 9,546 adults: 89% white, 83% urban residents. Greater neighborhood walkability was associated with increased specialty care use (AOR = 1.08, 95% CI (1.05-1.11) per 10th percentile increase, p<0.001), while higher public transit stop density was associated with decreased use (AOR = 0.84 (0.72 - 0.98) 4th vs 1st quartile, p<0.001). Increased access to cellular data was associated with increased use (AOR=1.06 (1.03-1.09) per 10th percentile, p<0.001). Distance to nearest clinic of either specialty was not significantly associated with overall care use (endocrinology AOR=0.986 (0.97 - 1.01) per 10 miles; cardiology AOR=1.01 (0.99-1.03)). Age (AOR 0.87 (0.84-0.91) per 10 years, p<0.001), race (AOR 0.78 (0.66-0.91) for Black vs white, p<0.001), and local area deprivation (AOR 0.94 (0.90-0.97) per 10th percentile, p<0.001) were associated with less specialty care use.

Community and patient factors are independently associated with use of specialty care for adults with T2D and ASCVD. Differential utilization of specialty care may contribute to disparities in health outcomes for under-resourced populations.

Disclosure

J. Bauer: None. S.D. Rothenberger: None. A.E. Johnson: Speaker's Bureau; Sanofi. Consultant; Edwards Lifesciences. Other Relationship; Women As One. A. Rosland: None. E. Kinnee: None. M. Zupa: None.

Funding

University of Pittsburgh CTSI Exploring Existing Data Resources Pilot Award; National Center for Advancing Translational Sciences KL2-TR001856
2054-LB: Mitigating Adipose Tissue Dysfunction and Insulin Resistance in Obesity via SVEP1 Peptide-Mediated Suppression of Adipose Tissue Macrophage-Induced Inflammation
Authors: KISLEV NADAV , KAVIN NACHUM , IZGILOV ROZA , BENAYAHU DAFNA
Published: June 2024

Introduction: Adipose tissue dysfunction in obesity poses a critical threat, causing metabolic impairment and systemic inflammation. This study explores the therapeutic potential of a peptide from SVEP1, targeting its integrin α9β1 receptor, to alleviate obesity-induced adipose dysfunction and insulin resistance by reducing pro-inflammatory macrophage activity.

Methods: We comprehensively examined the peptide's effect on adipose tissue dysfunction using in silico predictive binding, LPS-activated mono and co-culture cell systems, and diet-induced obese mice.

Results: Analysis of integrin α9β1 revealed specific expression in myeloid cells, particularly dysfunctional adipose tissue macrophages. In silico predictions confirmed the peptide's integrin affinity and ability to block ligand interactions. Peptide-treated LPS-activated BMDM exhibited reduced adhesion and mobility on decellularized matrices from adipocytes. The peptide suppressed pro-inflammatory activation, by inhibiting the MAPK and NF-κB pathways, altered transcriptomics, and reduced cytokine production in ex vivo isolated adipose tissue macrophages. Epididymal adipose tissue peptide administration in diet-induced obese mice reduced body and tissue weight, improved glucose sensitivity, hepatic function, and lessened adipose inflammation through modulated macrophage phenotype. Bulk and single-cell transcriptomics indicated decreased pro-inflammatory responses, improving adipocyte status, insulin sensitivity, and thermogenic capacity due to the anti-inflammatory state of tissue macrophages and upregulated mitochondrial activity.

Conclusions: The SVEP1-derived peptide emerges as a regulator of macrophages in obesity, effectively mitigating inflammation and restoring glucose homeostasis. This study offers insights into potential therapeutic avenues for addressing adipose tissue dysfunction.

Disclosure

N. Kislev: None. N. Kavin: None. R. Izgilov: None. D. Benayahu: None.