Introduction and Objective: Patients with diabetes benefit from regular exercise. However, the benefit of exercise in patients with diabetes and myocardial infarction (MI) is less clear. Therefore, we sought to evaluate the differences in mortality risk in patients with diabetes and MI (DMI) at various physical activity levels.Methods: Using data from the 2001 to 2014 […]
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918-P: Fully Closed Loop (FCL) System Improves Glycemic Control through Personalized Adaptation of Individual Insulin Needs in Adults, Young Adults, and Adolescents with Type 1 Diabetes (T1D)
Introduction and Objective: The Automated Insulin Delivery as Adaptive NETwork (AIDANET) FCL adjusts its aggressiveness based on glycemic metrics computed from the last 14-days of CGM records, to adapt to the different insulin requirements that individuals may have. The system was tested in a broad cohort of people with T1D. We report changes in glycemic […]
Read More281-OR: Time-Restricted Feeding Prevents Deleterious Effects of Diet-Induced Obesity on Circadian Regulation of β-Cell Function and Transcription
Introduction and Objective: Disruptions in circadian fasting/feeding cycles contribute to β-cell dysfunction in diabetes. Diet-induced obesity (DIO) (modeled by a high-fat diet) adversely affects circadian glucose homeostasis partly through dysregulation of fasting/feeding cycles. However, its impact on circadian β-cell function and gene expression remains unknown.Methods: To address this, we exposed male/female C57BL/6 mice to chow […]
Read More917-P: Real-World Impact of Open Source Automated Insulin Delivery (OS AID) on Glycemic Variability Reduction
Introduction and Objective: Glycemic variability, a key determinant of diabetes-related complications, remains a challenge in diabetes management. Time with rapid glucose change (TRC) has recently been proposed as a metric for assessing glycemic variability. There are no published data addressing the potential for AID to reduce TRC. BCDiabetes has a high volume of clients using […]
Read More1581-P: Comparison of Digital Biomarkers for Insulin Resistance and Fatty Liver Scores in Predicting Incident Fatty Liver and Type 2 Diabetes
Introduction and Objective: Insulin resistance (IR) is a major factor in developing fatty liver disease (FLD) and type 2 diabetes mellitus (T2DM). This study evaluates the predictive performance of an Artificial Intelligence based IR index (AI-IR) as a digital biomarker for fatty liver (FL) and T2DM, comparing it with established tools like the Fatty Liver […]
Read More916-P: Real-World Use of Sodium–Glucose Transporter 2 Inhibitors among Youth with Type 2 Diabetes
Introduction and Objective: Clinical trials of sodium-glucose transporter 2 inhibitors (SGLT2i) in youth with type 2 diabetes (T2D) showed significant improvement in HbA1c% and fasting plasma glucose, yet there is limited real-world data on their use. This study sought to assess real-world use and effectiveness of SGLT2i medications in management of T2D in a diverse […]
Read More2099-LB: Relationship between COVID-19 Variants and Diabetes Incidence
Introduction and Objective: Studies assessing diabetes mellitus (DM) risk after COVID-19 infection have typically examined narrow periods of the pandemic or did not incorporate advanced causal inference methods. This study assessed the association of COVID-19 infection with incident DM 1-year post-infection, stratified by viral variant periods, among adults aged 20-80y.Methods: We analyzed electronic health record […]
Read More915-P: Risk of Severe Lower Extremity Arterial Disease in Elderly Japanese Patients with Type 2 Diabetes—A Propensity Score-Matched Model Analysis of Sodium–Glucose Cotransporter 2 Inhibitors vs. Metformin
Introduction and Objective: This study examines the impact of Sodium-glucose cotransporter 2 inhibitors (SGLT2is) and metformin on severe Lower extremity arterial disease (LEAD) progression in elderly patients with type 2 diabetes (T2D). Using propensity score matching, a three-year analysis compares their distinct effects on risk using a real-world claims database.Methods: This retrospective cohort study analyzed […]
Read More2124-LB: Characteristics of People with Monogenic Diabetes in the Rare and Atypical Diabetes Network (RADIANT) Cohort
Introduction and Objective: Monogenic diabetes (MD) accounts for 0.4% of all cases of diabetes and 1-5% of youth-onset diabetes. Diagnosis allows for improved care with targeted therapy and identification of affected relatives. However, several barriers currently prevent patients from receiving diagnoses. We aimed to elucidate the proportion of individuals with undiagnosed MD within the Rare […]
Read More580-P: Engagement across DiabetesWise—A Platform for Support around Diabetes Technology and Exercise
Introduction and Objective: To gain feedback from users and assess engagement with the DiabetesWISER (DWer) community forum and DiabetesWise (DW) website – a neutral and unbiased platform for diabetes technology and exercise resources.Methods: User testing was conducted to understand needs and utilization patterns of people with diabetes and healthcare providers (HCPs) using these platforms.Results: During […]
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