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Introduction Continuous glucose monitoring (CGM) can guide treatment for people with type 1 (T1D) and type 2 diabetes (T2D). The ANSHIN study assessed the impact of non‐adjunctive CGM use in adults with diabetes using intensive insulin therapy (IIT). Materials and Methods This single‐arm, prospective, interventional study enrolled adults with T1D or T2D who had not used CGM in the prior 6 months. Participants wore blinded CGMs (Dexcom G6) during a 20‐day run‐in phase, with treatment based on fingerstick glucose values, followed by a 16‐week intervention phase and then a randomized 12‐week extension phase with treatment based on CGM values. The primary outcome was change in HbA1c. Secondary outcomes were CGM metrics. Safety endpoints were the number of severe hypoglycaemic (SH) and diabetic ketoacidosis (DKA) events. Results Of the 77 adults enrolled, 63 completed the study. Those enrolled had mean (SD) baseline HbA1c of 9.8% (1.9%), 36% had T1D, and 44% were ≥65 years old. Mean HbA1c decreased by 1.3, 1.0 and 1.0 percentage points for participants with T1D, T2D or age ≥65, respectively (p < .001 for each). CGM‐based metrics including time in range also improved significantly. SH events decreased from the run‐in period (67.3 per 100 person‐years) to the intervention period (17.0 per 100 person‐years). Three DKA events unrelated to CGM use occurred during the total intervention period. Conclusions Non‐adjunctive use of the Dexcom G6 CGM system improved glycaemic control and was safe for adults using IIT. ANSHIN is a single‐arm, prospective, interventional study that assessed the impact of non‐adjunctive Dexcom G6 continuous glucose monitoring (CGM) in adults with diabetes using intensive insulin therapy. After initiating CGM use, severe hypoglycemic events decreased and mean HbA1c decreased by 1.3, 1.0, and 1.0 percentage points for participants with type 1 diabetes (T1D), type 2 diabetes (T2D), or age ≥65, respectively (p<.001 for each) after 16 weeks. Non‐adjunctive use of CGM improved glycemic control and may help those with T1D or T2D make safe treatment decisions.

Regular physical activity and exercise are fundamental components of a healthy lifestyle for youth living with type 1 diabetes (T1D). Yet, few youth living with T1D achieve the daily minimum recommended levels of physical activity. For all youth, regardless of their disease status, minutes of physical activity compete with other daily activities, including digital gaming. There is an emerging area of research exploring whether digital games could be displacing other physical activities and exercise among youth, though, to date, no studies have examined this question in the context of youth living with T1D. We examined characteristics of digital gaming versus nondigital gaming (other exercise) sessions and whether youth with T1D who play digital games (gamers) engaged in less other exercise than youth who do not (nongamers), using data from the Type 1 Diabetes Exercise Initiative Pediatric study. During a 10-day observation period, youth self-reported exercise sessions, digital gaming sessions, and insulin use. We also collected data from activity wearables, continuous glucose monitors, and insulin pumps (if available). The sample included 251 youths with T1D (age: mean 14, SD 2 y; self-reported glycated hemoglobin A1c level: mean 7.1%, SD 1.3%), of whom 105 (41.8%) were female. Youth logged 123 digital gaming sessions and 3658 other exercise (nondigital gaming) sessions during the 10-day observation period. Digital gaming sessions lasted longer, and youth had less changes in glucose and lower mean heart rates during these sessions than during other exercise sessions. Youth described a greater percentage of digital gaming sessions as low intensity (82/123, 66.7%) when compared to other exercise sessions (1104/3658, 30.2%). We had 31 youths with T1D who reported at least 1 digital gaming session (gamers) and 220 youths who reported no digital gaming (nongamers). Notably, gamers engaged in a mean of 86 (SD 43) minutes of other exercise per day, which was similar to the minutes of other exercise per day reported by nongamers (mean 80, SD 47 min). Digital gaming sessions were longer in duration, and youth had less changes in glucose and lower mean heart rates during these sessions when compared to other exercise sessions. Nevertheless, gamers reported similar levels of other exercise per day as nongamers, suggesting that digital gaming may not fully displace other exercise among youth with T1D.

This trial randomly assigned pregnant women with type 1 diabetes to standard insulin therapy with continuous glucose monitoring or to hybrid closed-loop therapy. The latter significantly improved maternal glycemic control.

To the Editor: In their article on the results of the Automated Insulin Delivery among Pregnant Women with Type 1 Diabetes (AiDAPT) trial, Lee et al. (Oct. 26 issue) 1 describe the use of hybrid closed-loop therapy as compared with standard insulin therapy in pregnant women with type 1 diabetes in the United Kingdom. They report that women in the closed-loop group had a significantly higher percentage of time in the target glucose range than those in the standard-therapy group, without any substantial increase in hypoglycemia. In this regard, improving the treatment of pregnant women with type 1 diabetes is a . . .

Abstract Context A whole food plant-based diet (WFPBD), minimally processed foods with limited consumption of animal products, is associated with improved health outcomes. The benefits of WFPBD are underexplored in individuals with type 1 diabetes (T1D). Objective The primary objective of this analysis is to evaluate the association between WFPBD on glycemia in individuals with T1D. Methods Utilizing prospectively collected meal events from the Type 1 Diabetes Exercise Initiative, we examined the effect of WFPBD intake on glycemia, determined by the plant-based diet index (PDI). The PDI calculates overall, healthful (hPDI), and unhealthy PDI (uPDI) to evaluate for degree of processed foods and animal products (ie, WFPBD). Mixed effects linear regression model assessed time in range (TIR), time above range, and time below range. Results We analyzed 7938 meals from 367 participants. TIR improved with increasing hPDI scores, conferring a 4% improvement in TIR between highest and lowest hPDI scores (high hPDI: 75%, low hPDI: 71%; P < .001). Compared with meals with low hPDI, meals with high hPDI had lower glucose excursion (high hPDI: 53 mg/dL, low hPDI: 62 mg/dL; P < .001) and less time >250 mg/dL (high hPDI: 8%, low hPDI: 14%; P < .001). These effects were present but less pronounced by PDI (high PDI: 74%, low PDI: 71%; P = .01). No differences in time below 70 mg/dL and 54 mg/dL were observed by PDI or hPDI. Conclusion Meal events with higher hPDI were associated with 4% postprandial TIR improvement. These benefits were seen primarily in WFPBD meals (captured by hPDI) and less pronounced plant-based meals (captured by PDI), emphasizing the benefit of increasing unprocessed food intake over limiting animal products alone.

We explored the association between macronutrient intake and postprandial glucose variability in a large sample of youth living with T1D and consuming free-living meals. In the Type 1 Diabetes Exercise Initiative Pediatric (T1DEXIP) Study, youth took photographs before and after their meals on 3 days during a 10 day observation period. We used the remote food photograph method to obtain the macronutrient content of youth’s meals. We also collected physical activity, continuous glucose monitoring, and insulin use data. We measured glycemic variability using standard deviation (SD) and coefficient of variation (CV) of glucose for up to 3 h after meals. Our sample included 208 youth with T1D (mean age: 14 ± 2 years, mean HbA1c: 54 ± 14.2 mmol/mol [7.1 ± 1.3%]; 40% female). We observed greater postprandial glycemic variability (SD and CV) following meals with more carbohydrates. In contrast, we observed less postprandial variability following meals with more fat (SD and CV) and protein (SD only) after adjusting for carbohydrates. Insulin modality, exercise after meals, and exercise intensity did not influence associations between macronutrients and postprandial glycemic variability. To reduce postprandial glycemic variability in youth with T1D, clinicians should encourage diversified macronutrient meal content, with a goal to approximate dietary guidelines for suggested carbohydrate intake.