Diabetology

Background: Managing Type 1 diabetes (T1D) aims to optimize glucose within the target range while minimizing hyperglycemia and hypoglycemia, yet exercise complicates glycemic outcomes. Despite advances, evidence is limited on how exercise relates to glycemic variability (GV) and hypoglycemia in automated insulin delivery (AID) and non-AID users, including evidence on GV’s temporal course before and after hypoglycemia, especially following long episodes. Objective: We aimed to characterize −48 to +48 h CGM trajectories around hypoglycemia, compare commercial AID and non-AID users, and assess modifiers (exercise, episode duration/severity, gender). Methods: This study analyzes the Type 1 Diabetes and Exercise Initiative (T1DEXI) dataset, assessing GV, hypoglycemia, gender, and exercise interactions in AID (n = 222) and non-AID (n = 276) users. The study examined patterns of glycemic metrics, including time below range (TBR) and glycemic variability surrounding hypoglycemia events, focusing on the 48 h before and after these events. We further assessed the impact of different hypoglycemia levels (41–50 mg/dL, 51–60 mg/dL, and 61–70 mg/dL) on post-event glucose stability. Results: Glycemic variability increased before and after hypoglycemia for up to 48 h in both AID and non-AID users, with statistically significant differences in GV metrics. TBR elevation persisted across all groups, peaking around hypoglycemic episodes. Notably, females using AID achieved significantly improved glucose stability compared to non-AID females, which is a larger within-group difference than that observed in males. Individual-level AID analyses revealed that long-duration hypoglycemia episodes (>40 min) resulted in prolonged TBR elevation, suggesting a slower recovery period despite AID intervention. Conclusions: GV trends may aid in predicting hypoglycemia over extended time periods. Integrating GV patterns into AID systems could improve glucose stability and mitigate hypoglycemia cycles, especially with the possible evaluation of hypoglycemia duration. Future research should explore hormonal influences (e.g., menstrual cycle effects) and inter-individual variability for optimized individual diabetes management.

Introduction: Advancements in diabetes technology have transformed diabetes management, yet technology implementation remains inconsistent due to barriers at both the clinician and patient levels. Team-based collaborative care offers a promising strategy to bridge these gaps. Framework: The Practical, Robust Implementation and Sustainability Model (PRISM), which incorporates the reach, effectiveness, adoption, implementation, and maintenance (RE-AIM) framework, was applied to identify clinician and patient-level barriers to technology implementation and guide development of team-based strategies for improvement. Application of this framework is illustrated through a rural primary care clinic implementing a remote patient monitoring program. Results: Analysis across RE-AIM domains identified team-based, interprofessional strategies for enhancing technology implementation and sustainability. Recommended strategies include structured onboarding and digital literacy support for both patients and clinicians, clear delineation of team roles and intentional integration of workflows, continuous quality improvement through feedback and huddles, and sustained organizational and policy support that ensures security, reimbursement, and equitable access. Conclusions: Application of the PRISM framework to improve diabetes technology implementation allows for translation of technological innovation into meaningful outcomes.

Background/Objectives: Type 2 diabetes (T2D) is a substantial health burden on foreign-born Haitian Americans (FBHAs) in the United States, who experience poorer health outcomes for T2D, in particular, cardiovascular disease and diabetes nephropathy. Understanding the factors that contribute to these disparities is essential. The purpose of this study was to examine the association between demographic, clinical, diabetes self-management, and social determinants of health (SDoH) factors with continuous glucose monitor (CGM-derived) glycemic indices in adult FBHAs with T2D. Methods: A cross-sectional exploratory correlation study was conducted in two urban health clinics, focusing on FBHAs aged 21 or older who had T2D for at least one year. Data were analyzed using SAS 6.4, employing descriptive statistics, bivariate correlations, and multiple regression models. Results: The study included 59 participants (49.2% male; mean age = 51.7 years, SD = 9.9), with an average T2D duration of 7.7 years (SD = 6.8) and an average of 1.63 (SD = 1.30) chronic diseases. A total of 29% were overweight while 21% had obesity with a mean HbA_1c of 58 mmol/mol (7.5%). A higher body weight and poorer dietary habits were associated with elevated glucose levels (standardized β ≈ 0.25 and −0.24). Greater race-related stress was correlated with greater glucose variability (β ≈ 0.46). Conclusions: These findings highlight the importance of addressing SDoH, such as race-related stress and food insecurity, to improve T2D self-management among FBHAs. Assessing and mitigating these risk factors can enhance glycemic control and health outcomes. Additionally, the findings demonstrate that CGM is feasible and acceptable for this population, showing exploratory findings and preliminary effect sizes that provide a strong basis for future, large-scale investigations.