In This Issue of Diabetes Care

Real-world users of Medtronic’s MiniMed 780G hybrid closed-loop insulin delivery system who consistently used two specific glucose and insulin targets experienced better glycemic control than users who did not achieve the targets, according to Castañeda et al. (p. 790). Specifically, consistent use of a 100 mg/dL blood glucose target and a 2-h active insulin time were associated with elevated time in tight range (TITR) among individuals with type 1 diabetes. TITR is a relatively new continuous glucose monitoring (CGM) metric and corresponds to the glucose range (70–140 mg/dL) in which individuals without diabetes spend most of their time. The findings come from a retrospective observational study that used real-world data from the data platform linked to the MiniMed system. Users are typically signed up to the CareLink Personal platform during training and primarily use it for managing diabetes metrics over time. Analyses of the anonymized data then aimed to evaluate predictors of TITR and the relationship between TITR and time in range (a more common but broader measure of blood glucose) in a bid to start defining targets for users. Based on data from ~13,500 individuals with type 1 diabetes, the authors found that users achieved TITR in ~50% of system use over ~230–240 days. Several factors were associated with increased TITR, with the glucose target and active insulin time appearing to be the strongest factors. Users who achieved the targets of active insulin time of 2 h and blood glucose of 100 mg/dL experienced TITR of roughly 57%. Exploring potential targets, the authors found that ~45%, ~50%, and ~55% TTIR corresponded to <7.0%, <6.8%, and <6.5% glucose management indicator targets (an approximation of HbA_1c derived from CGM). Roughly 90% of individuals achieved the 45% target, with percentages dropping to just over 50% with the highest TITR of 55%.

Further analysis of the Diabetes Prevention Program (DPP) cohort and the follow-up DPP Outcomes Study (DPPOS) by Lee et al. (p. 810) suggests there is no difference in the prevalence of distal symmetrical polyneuropathy (DSPN) 21 years after randomization to the treatment groups (i.e., intensive lifestyle intervention, metformin, or placebo). Of the original cohort, 1,792 participants in the outcomes study had symptoms and signs of DSPN assessed at year 17, providing the opportunity to also evaluate whether diabetes duration and cumulative glycemic exposure were associated with DSPN. The authors report that there were no differences between the groups in terms of crude prevalence of DSPN (21.7%) or its components. However, the crude prevalence was marginally higher in individuals with diabetes (22.7%) compared with those without (19.6%) at the time of the clinical assessment. A diabetes diagnosis, greater duration of diabetes, and higher cumulative HbA_1c all presented increasing odds of DSPN. The overall prevalence of diabetes was 68.5% at the time of the analysis. Notably, the risk of DSPN associated with the DPP interventions differed by age, such that the risk for DSPN decreased with increasing age for those randomized to the intensive lifestyle intervention. The authors explain that this may have been because of the greater efficacy of the lifestyle intervention in older adults. “For participants in this study, the risk of DSPN was greater with having a higher cumulative glycemic exposure than with having a diagnosis of diabetes or a longer duration of diabetes,” said author Christine G. Lee. “Given the risk conferred by cumulative glycemic exposure and the DSPN prevalence of almost 20% among participants who just had prediabetes, future studies are needed to evaluate whether DSPN can be prevented by interventions aimed at achieving normoglycemia.” The authors also suggest that screening for DSPN is warranted in those with prediabetes, since many participants had glycemia below the threshold for diabetes and still developed DSPN.

Individuals with diabetes who live in small towns in the U.S. experienced higher rates of many complications than those who lived in cities or remote areas, according to Steiger et al. (p. 818). Specifically, in ~2.9 million adults with diabetes, those living in small towns (i.e., population 2,500–50,000) had increased hazards for 8 of 11 common complications of diabetes compared with those living in cities and increased hazards for 3 complications compared with those living in remote areas. The findings come from a retrospective cohort study that used data from the OptumLabs Data Warehouse. The authors followed adults with diabetes from 11 January 2012 to 31 December 2021 and compared hazard ratios for 11 common diabetes complications in remote areas, small towns, and cities. Complications included hypo- and hyperglycemia, end-stage renal disease, heart complications, amputations, and retinopathy, among others. As well as the headline findings, they found that the comparisons of geographic regions resulted in lower or higher hazards, leaving an overall impression of reduced hazards in cities and remote areas compared with small towns. Only hazards for retinopathy and atrial fibrillation/flutter did not differ geographically. While the study could not uncover the specific reasons for the variations in risk, the authors propose some explanations. In particular, they cite structural and socioeconomic factors for the increased risks of complications in small towns. Conversely, they suggest protective factors, and particularly fitness levels, might explain the lower rates in remote areas. For people living in rural settings, barriers to care might also be a factor. “Rural communities bear a disproportionate burden of diabetes and many of its complications, reinforcing concerns about lack of access to primary and specialty care as well as financial barriers to care and food insecurity,” said author Rozalina G. McCoy. “I hope this work leads to greater focus on preventing diabetes and better caring for people living with diabetes in rural communities.”

Exercise appears to be associated with a raised risk of overnight hypoglycemia in youth with type 1 diabetes, according to Sherr et al. (p. 849). However, achieving physical activity targets and recommendations through education and individualized plans is still feasible. The findings come from further analysis of the Type 1 Diabetes Exercise Initiative Pediatric (T1DEXIP) study, which was a real-world observational study with participants self-reporting physical activity and food intake. The authors also collected continuous glucose monitoring data, insulin use, and heart rate data. Over ~10 days, participants logged ~40 types of activities over 3,319 activity events, which equated to between 1.0 and 1.4 events per day per person. The authors found that there was a trend for lower glucose levels after exercise in individuals with shorter disease duration and lower HbA_1c. Nearly all participants were using a continuous glucose monitoring device at enrollment, and just over half were using a hybrid closed-loop insulin delivery system. However, there were no differences in glucose trends between insulin delivery methods. Larger drops in glucose during exercise were associated with lower glucose levels immediately after exercise and 12–16 h later. The authors found that hypoglycemia occurred on 14% of nights following exercise and 12% of nights after a sedentary day. Notably, more hypoglycemia occurred following exercise that was longer than 60 min. “Our realworld, observational data of a diverse set of activities conducted in a nonprescriptive fashion may help ground clinical care conversations,” said author Jennifer L. Sherr. “It also highlights the importance of counseling youth living with type 1 diabetes on the benefits of exercise and factors that may increase risk of hypoglycemia. Additionally, as our data are publicly available at the Vivli platform [https://doi.org/10.25934/PR00008429], we hope investigators will explore how decision support tools and algorithmic modulation of insulin delivery can be refined to account for physical activity.”