Author: sugaradmin

Introduction and Objective: Insulin sensitivity factor (ISF) is often considered constant in Automated Insulin Delivery systems and other insulin therapies, but ISF varies with glycemia [1]. This study assesses the impact of glycemia (G) on ISF using real-life data.Methods: Data from 11,201 T1D adults using the DBLG1 System since March 2021 was used. G peaks […]

Introduction and Objective: In 4T Study 1, youth with new-onset T1D start CGM <30 days after diagnosis, receive weekly remote CGM data review by a CDCES, and dose changes via secure portal messaging. We describe the policy CDCES used to make dose adjustments and report the safety and effectiveness of CDCESs, making incremental dose changes […]

Introduction and Objective: The failure of pancreatic β-cells is a central feature of diabetes, yet measures of β-cell function in humans, such as clamp-derived variables, are invasive and sensitive to other factors (i.e., insulin resistance, insulin clearance, etc.). Since glucose-stimulated insulin release is coupled to pancreas oxygen consumption, we tested qBOLD MRI as a non-invasive […]

Introduction and Objective: Continuous glucose monitoring (CGM) has been associated with improved glycemic outcomes in older patients with Diabetes Mellitus (DM). Older patients may face barriers to use including challenges with technology. We are not aware of any comparison between older and younger adults. We studied if older age is associated with less favorable CGM […]

Introduction and Objective: Diabetes management and outcomes often differ by sex, influenced by biological and psychobehavioral factors. Our objective was to examine sex differences in glycemic outcomes during the safety and feasibility testing of the AIDANET automated insulin delivery system (AID)Methods: Participants with T1D enrolled in a randomized crossover trial of usual care (overwhelmingly AID […]

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 […]

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 […]

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 […]

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 […]

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 […]