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Objective: Patients with type 1 diabetes who do aerobic exercise often experience a drop in blood glucose concentration that can result in hypoglycemia. Current approaches to prevent exercise-induced hypoglycemia include reduction in insulin dose or ingestion of carbohydrates, but these strategies may still result in hypoglycemia or hyperglycemia. We sought to determine whether mini-dose glucagon (MDG) given subcutaneously before exercise could prevent subsequent glucose lowering and to compare the glycemic response to current approaches for mitigating exercise-associated hypoglycemia.Research Design and Methods: We conducted a four-session, randomized crossover trial involving 15 adults with type 1 diabetes treated with continuous subcutaneous insulin infusion who exercised fasting in the morning at ∼55% VO2max for 45 min under conditions of no intervention (control), 50% basal insulin reduction, 40-g oral glucose tablets, or 150-μg subcutaneous glucagon (MDG).Results: During exercise and early recovery from exercise, plasma glucose increased slightly with MDG compared with a decrease with control and insulin reduction and a greater increase with glucose tablets (P < 0.001). Insulin levels were not different among sessions, whereas glucagon increased with MDG administration (P < 0.001). Hypoglycemia (plasma glucose <70 mg/dL) was experienced by six subjects during control, five subjects during insulin reduction, and none with glucose tablets or MDG; five subjects experienced hyperglycemia (plasma glucose ≥250 mg/dL) with glucose tablets and one with MDG.Conclusions: MDG may be more effective than insulin reduction for preventing exercise-induced hypoglycemia and may result in less postintervention hyperglycemia than ingestion of carbohydrate. [ABSTRACT FROM AUTHOR]

Objective: Identify factors predictive of severe hypoglycemia (SH) and assess the clinical utility of continuous glucose monitoring (CGM) to warn of impending SH.Research Design and Methods: In a multicenter randomized clinical trial, 436 children and adults with type 1 diabetes were randomized to a treatment group that used CGM (N = 224), or a control group that used standard home blood glucose monitoring (N = 212) and completed 12 months of follow-up. After 6 months, the original control group initiated CGM while the treatment group continued use of CGM for 6 months. Baseline risk factors for SH were evaluated over 12 months of follow-up using proportional hazards regression. CGM-derived indices of hypoglycemia were used to predict episodes of SH over a 24-h time horizon.Results: The SH rate was 17.9 per 100 person-years, and a higher rate was associated with the occurrence of SH in the prior 6 months and female sex. SH frequency increased eightfold when 30% of CGM values were ≤ 70 mg/dL on the prior day (4.5 vs. 0.5%; P < 0.001), but the positive predictive value (PPV) was low (<5%). Results were similar for hypoglycemic area under the curve and the low blood glucose index calculated by CGM.Conclusions: SH in the 6 months prior to the study was the strongest predictor of SH during the study. CGM-measured hypoglycemia over a 24-h span is highly associated with SH the following day (P < 0.001), but the PPV is low. [ABSTRACT FROM AUTHOR]

Editorial. Talks about the challenges and opportunities faced during the transition of adolescents with diabetes to early adulthood. Priorities in the care of young adults with diabetes; Important factor in the transition of an older adolescent graduating from pediatric medicine to a health-care provider; Things that should be considered by the provider in formulating treatment plan and goals.

The ability to identify carbohydrate foods is an important for diabetes self-management for adults with type 2 diabetes (T2D). Until recently, diabetes education for patients with T2D mainly emphasized the fat content of foods. To assess whether T2D patients can identify carbohydrate foods (carbs), we evaluated 56 type 2 patients (age 62±13 yrs, duration 13±11 yrs, BMI 32.5±7.3, A1C 7.7±1.6%, education 15±2 yrs, 45% females). Subjects completed surveys on diabetes distress (Problem Areas in Diabetes, PAID), self-care (Self-Care inventory, SCI-R), and frustration with self-care (Self-Care Problem Areas, SPA) and identified foods containing carbs from a group of 12 food models. 55% of subjects identified at least 9/12 carbs correctly. Carb knowledge scores were correlated with frequency of self-care behaviors (r=0.32, p<0.05), specifically dietary (r=0.41, p<0.01) and general health behaviors (r=0.28, p<0.05) but not with A1C, distress, or frustration with self-care. A1C was correlated with frustration with self-care (r=0.42, p=0.001), duration (r=0.31,p<0.05), and glucose monitoring (r=0.32, p=0.02), and inversely related to frequency of following physical activity recommendations (r=-0.26, p=0.05). Of the 28 subjects with A1C≤7%, 40% take insulin, 71% reported understanding carbs, yet 11 (39%) could not correctly identify carbs. Of those with A1C>7% (n=28), 71% take insulin (p=0.02), 59% reported understanding carbs (p=ns), and 14 (50%) could not correctly identify carbs (p=ns). Among those who correctly identified carbs (>9/12), those with A1C>7 had greater frustration with treatment (38 vs 23, p<0.05) higher BMI's (36 vs 28, p<0.01), and longer duration (16 vs 9, p=0.08) than those with A1C<7%. For those with low carb knowledge, only a trend for frequency of following physical activity recommendations (41 vs 65, p=0.07) differentiated glycemic control groups (A1C>7 vs A1C≤7%). Conclusions: Our data suggest that many patients with T2D do not have working knowledge of carbohydrates. Type 2 diabetes is a progressive disease, as beta cell loss increases with duration and as insulin resistance impedes attainment of glycemic targets, working knowledge of carbohydrates is particularly important for reaching goals. Thus, nutrition counseling for patients with T2D should begin early in the course of the treatment and should emphasize the carbohydrates along with fats and other nutrition concepts. [ABSTRACT FROM AUTHOR]

The article focuses on a randomized study that evaluated the clinical effectiveness of a device which combines a smart insulin pump with real-time continuous glucose monitoring (RT-CGM). Adults and adolescents with type 1 diabetes and insulin pump wearers were the participants of this study. It found that subjects with greater sensor utilization predicted a greater improvement in A1c levels.

Context: Continuous glucose monitor (CGM) companies are beginning to market these sensors to populations without diabetes, but the range of CGM values clinicians should expect to see for this population is unclear because there have been no large studies reporting these ranges., Objective: To report the physiological range of continuous glucose monitor (CGM) time in range values observed across glycemic status, including individuals without diabetes, to serve as a reference for clinicians., Design: The Framingham Heart Study, a prospective cohort study., Setting: Community-dwelling individuals., Patients or Participants: Adults with normoglycemia (n=560), prediabetes (n=463), and diabetes (n=152)., Intervention: We conducted a cross-sectional investigation in participants who wore a Dexcom G6 Pro CGM for ≥7 complete days., Main Outcome Measures: CGM metrics including mean glucose and time spent in glucose ranges., Results: Normoglycemic participants (mean age 58.5y, 64.5% women, 93.3% non-Hispanic white) spent 87.0% time in the 70-140mg/dL CGM range, and, on average, >15min/day (1.2% time) >180mg/dL. Furthermore, normoglycemic participants spent ∼3 hours/day (12.1% time) with CGM glucose >140mg/dL. On average, participants with prediabetes and diabetes spent 77.1% and 46.2% time in 70-140mg/dL, respectively., Conclusions: Our results contribute to the understanding of the physiological CGM range in >1000 participants without diabetes. These results are also important for clinicians to reference as CGM sensors become more widely accessible to people without known diabetes., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Endocrine Society.)

Maintaining blood glucose levels in the target range during exercise can be onerous for people with type 1 diabetes (T1D). Using evidence-based research and consensus guidelines, we developed an exercise advisor app to reduce some of the burden associated with diabetes management during exercise. The app will guide the user on carbohydrate feeding strategies and insulin management strategies before, during, and after exercise and provide targeted and individualized recommendations. As a basis for the recommendations, the decision trees for the app use various factors including the type of insulin regimen, time of activity, previous insulin boluses, and current glucose level. The app is designed to meet the various needs of people with T1D for different activities to promote safe exercise practices.

Objective: To evaluate long-term effects of continuous glucose monitoring (CGM) in intensively treated adults with type 1 diabetes., Research Design and Methods: We studied 83 of 86 individuals >or=25 years of age with type 1 diabetes who used CGM as part of a 6-month randomized clinical trial in a subsequent 6-month extension study. RESULTS After 12 months, median CGM use was 6.8 days per week. Mean change in A1C level from baseline to 12 months was -0.4 +/- 0.6% (P < 0.001) in subjects with baseline A1C >or=7.0%. A1C remained stable at 6.4% in those with baseline A1C <7.0%. The incidence rate of severe hypoglycemia was 21.8 and 7.1 events per 100 person-years in the first and last 6 months, respectively. Time per day with glucose levels in the range of 71-180 mg/dl increased significantly (P = 0.02) from baseline to 12 months., Conclusions: In intensively treated adults with type 1 diabetes, CGM use and benefit can be sustained for 12 months.

Objective: To evaluate factors associated with successful use of continuous glucose monitoring (CGM) among participants with intensively treated type 1 diabetes in the Juvenile Diabetes Research Foundation Continuous Glucose Monitoring Randomized Clinical Trial., Research Design and Methods: The 232 participants randomly assigned to the CGM group (165 with baseline A1C >or=7.0% and 67 with A1C <7.0%) were asked to use CGM on a daily basis. The associations of baseline factors and early CGM use with CGM use >or=6 days/week in the 6th month and with change in A1C from baseline to 6 months were evaluated in regression models., Results: The only baseline factors found to be associated with greater CGM use in month 6 were age >or=25 years (P < 0.001) and more frequent self-reported prestudy blood glucose meter measurements per day (P < 0.001). CGM use and the percentage of CGM glucose values between 71 and 180 mg/dl during the 1st month were predictive of CGM use in month 6 (P < 0.001 and P = 0.002, respectively). More frequent CGM use was associated with a greater reduction in A1C from baseline to 6 months (P < 0.001), a finding present in all age-groups., Conclusions: After 6 months, near-daily CGM use is more frequent in intensively treated adults with type 1 diabetes than in children and adolescents, although in all age-groups near-daily CGM use is associated with a similar reduction in A1C. Frequency of blood glucose meter monitoring and initial CGM use may help predict the likelihood of long-term CGM benefit in intensively treated patients with type 1 diabetes of all ages.

OBJECTIVE The potential benefits of continuous glucose monitoring (CGM) in the management of adults and children with well-controlled type 1 diabetes have not been examined. RESEARCH DESIGN AND METHODS A total of 129 adults and children with intensively treated type 1 diabetes (age range 8-69 years) and A1C <7.0% were randomly assigned to either continuous or standard glucose monitoring for 26 weeks. The main study outcomes were time with glucose level < or =70 mg/dl, A1C level, and severe hypoglycemic events. RESULTS At 26 weeks, biochemical hypoglycemia (< or =70 mg/dl) was less frequent in the CGM group than in the control group (median 54 vs. 91 min/day), but the difference was not statistically significant (P = 0.16). Median time with a glucose level < or =60 mg/dl was 18 versus 35 min/day, respectively (P = 0.05). Time out of range (< or =70 or >180 mg/dl) was significantly lower in the CGM group than in the control group (377 vs. 491 min/day, P = 0.003). There was a significant treatment group difference favoring the CGM group in mean A1C at 26 weeks adjusted for baseline (P < 0.001). One or more severe hypoglycemic events occurred in 10 and 11% of the two groups, respectively (P = 1.0). Four outcome measures combining A1C and hypoglycemia data favored the CGM group in comparison with the control group (P < 0.001, 0.007, 0.005, and 0.003). CONCLUSIONS Most outcomes, including those combining A1C and hypoglycemia, favored the CGM group. The weight of evidence suggests that CGM is beneficial for individuals with type 1 diabetes who have already achieved excellent control with A1C <7.0%.