To assess the effect of metabolic bariatric surgery (MBS) in people living with type 1 diabetes (T1D) and obesity. From retrospective multicenter data, total weight loss, daily insulin requirement, HbA1c, and cardiometabolic parameters were assessed before and after surgery. Longitudinal models were used to identify response determinants. This study included 162 people living with T1D and obesity. One year after surgery, mean total weight loss percentage was 29.7% (interquartile range [IQR] = 29.4, 30.3). Insulin requirements dropped from 0.75 (IQR = 0.58, 1.00) units/kg/day to 0.32 (IQR = 0.23, 0.43) units/kg/day (P < 0.001), and HbA1c dropped from 64.0 (IQR = 57.0, 74.0) mmol/mol to 60.0 (IQR = 53.4, 68.0) mmol/mol (P < 0.001). LDL, HDL, total cholesterol, and triglyceride levels significantly improved after surgery (P < 0.001). Greater total weight loss was associated with reduced insulin requirements, and higher baseline HbA1c was associated with poorer postsurgery glycemic control. MBS was associated with substantial metabolic improvement in people with T1D and obesity, in particular in those with high HbA1c and insulin need at baseline.

As care for type 1 diabetes (T1D) advances, the number of adults with T1D living into older adulthood (ages ≥65 years) continues to grow. The population of older adults with T1D is highly heterogeneous, and over the life span, various factors may change over time while others may not, necessitating an individualized approach to management. A key care consideration for people with T1D is the ongoing need for exogenous insulin replacement intensive self-monitoring for effective management. At the same time, growing older may bring changes such as increased risk of misdiagnosis of T1D as type 2 diabetes, greater vulnerability to hypoglycemia, accumulating comorbidities and complications, declining independence due to geriatric syndromes, and a growing need for support in using diabetes technologies and navigating complex care transitions. Given the unique clinical and management needs of this population, we sought to present key care challenges in this population and suggest strategies to optimize quality of care in older adults with T1D, including 1) integrating geriatric screenings, age-friendly care frameworks, and regular reassessments into routine T1D management; 2) developing tailored care approaches for cognitive impairment; 3) establishing support systems for diabetes technology use in primary and long-term care settings; and 4) ensuring insurance coverage and access to diabetes technologies and therapies. Forward-thinking strategies to optimize care include individualized glycemic goal setting, the development and adoption of care models that support continuity of diabetes technology use, and individualized management strategies that consider of the goals and capabilities of the person living with T1D and care partners.

Although continuous glucose monitors (CGMs) are increasingly used to detect and manage postbariatric hypoglycemia (PBH) and associated glucose variability, data on their accuracy in this population remain scarce. We retrospectively assessed the accuracy of the Dexcom G6 CGM system in adults with PBH after Roux-en-Y gastric bypass (RYGB) surgery (n = 70). Glucose excursions were induced using a standardized solid mixed-meal test, and reference blood glucose (BG) values were obtained through repeated venous whole-blood sampling. CGM accuracy was analyzed separately during stable and dynamic postmeal glucose periods, with dynamic phases stratified according to magnitude and direction of the rate of change (RoC). We further estimated the lag time for each sensor and examined predictive factors affecting CGM accuracy. A total of 1,822 CGM-BG pairs obtained with 70 individuals were included in the analysis. Mean absolute relative differences at stable and dynamic levels were 9.6% and 16.4%, respectively. After the meal test, 67.6% of pairs had CGM values within 15%, or 15 mg/dL of the reference BG; 78.0% within 20%, or 20 mg/dL; and 90.8% within 30%, or 30 mg/dL. Performance was worse at rapid plasma glucose decline (>1.5 mg/dL/min), and CGM values at the time of plasma glucose nadir were systematically higher (bias, 8.2 mg/dL). Plasma-interstitium time delay was estimated at 9.8 min. No participant or sensor characteristic had a significant impact on CGM accuracy. Meal-induced glucose dynamics, particularly rapid declines, challenge CGM accuracy in people with PBH and must be carefully considered when diagnosing or managing the condition.

To investigate the short-term association between ambient temperature and risk of hypoglycemia in adults with type 1 diabetes mellitus (T1DM). We hypothesized that higher ambient temperature would increase the odds of hypoglycemia developing. We applied a case time series design to assess the longitudinal association between ambient temperature and hypoglycemia measured using routine continuous glucose monitoring data from individuals with T1DM. A quasi-binomial fixed-effect regression with distributed lag nonlinear models was used to estimate potentially nonlinear and lagged risks of nonoptimal temperature on hypoglycemic episodes, defined as ≥15 min of glucose concentration <3.9 mmol/L. The model was adjusted for long-term trends, seasonality, day of the week, and public holidays. A secondary outcome was change in daily mean glucose concentration. We analyzed 32,966,282 glucose readings from 679 adults with T1DM attending two National Health Service clinics in Sussex, England, between 2017 and 2024. Higher ambient temperatures were associated with an increased risk of hypoglycemia. The risk increased nonlinearly for temperatures above 13°C, with the odds ratio reaching 1.26 (95% CI 1.13-1.26) at 25°C. The strongest effect was observed on the same day of the exposure, and it diminished over subsequent days. In the secondary analysis, higher temperatures were associated with lower mean glucose levels. Elevated ambient temperature significantly increases the short-term risk of hypoglycemia in adults with T1DM. These findings are specific to the U.K. population and climate, which may limit generalizability. Our results support anticipatory insulin adjustments during hot weather and consideration of ambient temperature in hybrid closed-loop insulin algorithms.