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The physical and psychological benefits of exercise are particularly pertinent to people with type 1 diabetes (T1D). The variability in subcutaneous insulin absorption and the delay in offset and onset in glucose lowering action impose limitations, given the rapidly varying insulin requirements with exercise. Simultaneously, there are challenges to glucose monitoring. Consequently, those with T1D are less likely to exercise because of concerns regarding glucose instability. While glucose control with exercise can be enhanced using automated insulin delivery (AID), all commercially available AID systems remain limited by the pharmacokinetics of subcutaneous insulin delivery. Although glycemic responses may vary with exercises of differing intensities and durations, the principles providing the foundation for guidelines include minimization of insulin on board before exercise commencement, judicious and timely carbohydrate supplementation, and when possible, a reduction in insulin delivered in anticipation of planned exercise. There is an increasing body of evidence in support of superior glucose control with AID over manual insulin dosing in people in T1D who wish to exercise. The MiniMed™ 780G AID system varies basal insulin delivery with superimposed automated correction boluses. It incorporates a temporary (elevated glucose) target of 8.3 mmol/L (150 mg/dL) and when it is functioning, the autocorrection boluses are stopped. As the device has recently become commercially available, there are limited data assessing glucose control with the MiniMed™ 780G under exercise conditions. Importantly, when exercise was planned and implemented within consensus guidelines, %time in range and %time below range targets were met. A practical approach to exercising with the device is provided with illustrative case studies. While there are limitations to spontaneity imposed on any AID device due to the pharmacokinetics associated with the subcutaneous delivery of current insulin formulations, the MiniMed™ 780G system provides people with T1D an excellent option for exercising safely if the appropriate strategies are implemented. [ABSTRACT FROM AUTHOR]

Introduction: Diabetic ketoacidosis (DKA) at diagnosis is associated with short- and long-term complications. We assessed the relationship between DKA status and hemoglobin A1c (A1c) levels in the first year following type 1 diabetes (T1D) diagnosis. Research Design and Methods: The Pilot Teamwork, Targets, Technology, and Tight Control (4T) study offered continuous glucose monitoring to youth with T1D within 1 month of diagnosis. A1c levels were compared between historical (n = 271) and Pilot 4T (n = 135) cohorts stratified by DKA status at diagnosis (DKA: historical = 94, 4T = 67 versus without DKA: historical = 177, 4T = 68). A1c was evaluated using locally estimated scatter plot smoothing. Change in A1c from 4 to 12 months postdiagnosis was evaluated using a linear mixed model. Results: Median age was 9.7 (interquartile range [IQR]: 6.6, 12.7) versus 9.7 (IQR: 6.8, 12.7) years, 49% versus 47% female, 44% versus 39% non-Hispanic White in historical versus Pilot 4T. In historical and 4T cohorts, DKA at diagnosis demonstrated higher A1c at 6 (0.5% [95% confidence interval (CI): 0.21–0.79; P < 0.01] and 0.38% [95% CI: 0.02–0.74; P = 0.04], respectively), and 12 months (0.62% [95% CI: −0.06 to 1.29; P = 0.07] and 0.39% [95% CI: −0.32 to 1.10; P = 0.29], respectively). The highest % time in range (TIR; 70–180 mg/dL) was seen between weeks 15–20 (69%) versus 25–30 (75%) postdiagnosis for youth with versus without DKA in Pilot 4T, respectively. Conclusions: Pilot 4T improved A1c outcomes versus the historical cohort, but those with DKA at diagnosis had persistently elevated A1c throughout the study and intensive diabetes management did not mitigate this difference. DKA prevention at diagnosis may translate into better glycemic outcomes in the first-year postdiagnosis. Clinical Trial Registration: clinicaltrials.gov: NCT04336969. [ABSTRACT FROM AUTHOR]

Conclusion For a high fat (40 g), high protein (50 g) meal that also contains carbohydrate (30 g), giving 125% of the usual ICR as aspart insulin 30 minutes before the meal improves postprandial glycemia significantly more than giving the usual aspart insulin dose (100Asp). A higher glucose target (temporary target, 8.3 mmol/L) was set 2 hours before exercise for all exercise conditions, and supplemental carbohydrate (15 g), without an insulin bolus, was administered 15 minutes before exercise if the glucose level was <7.0 mmol/L. For all exercise interventions, the temporary glucose target was ceased immediately after exercise with reversion to the usual target of 5.6 mmol/L. The primary outcome was continuous glucose monitoring (CGM) time-in-range (TIR, 3.9-10.0 mmol/L) for 24 hours after exercise. The CGM median TIR 24 hours after exercise was >81%, percent time below range (<3.9 mmol/L) was <4%, and percent time above range (>10.0 mmol/L) was <17% for both exercise conditions (MIE vs HIE) and insulin formations, with no significant differences between insulins ( I P i >.05). HYPOGLYCEMIA PREVENTION STRATEGIES AND INTERACTIONS WITH INSULIN Anticipated Basal Insulin Reduction To Prevent Exercise-Induced Hypoglycemia in Adults and Ad... I Tagougui S SP 1,2,3 sp , Legault L SP 1,4 sp , Heyman E SP 3 sp , Messier V SP 1 sp , Suppere C SP 1 sp , Potter KJ SP 1 sp , Pigny P SP 5 sp , Berthoin S SP 3 sp , Taleb N SP 1,6,7 sp , Rabasa-Lhoret R SP 1,2,7 sp i I SP 1 sp Montreal Clinical Research Institute (IRCM), Montreal, Canada; SP 2 sp Département de nutrition, Université de Montréal, Montreal, Canada; SP 3 sp Univ. Lille, Univ. Artois, Univ. [Extracted from the article]

Aim: Initiating continuous glucose monitoring (CGM) shortly after Type 1 diabetes diagnosis has glycaemic and quality of life benefits for youth with Type 1 diabetes and their families. The SARS‐CoV‐2 pandemic led to a rapid shift to virtual delivery of CGM initiation visits. We aimed to understand parents' experiences receiving virtual care to initiate CGM within 30 days of diagnosis. Methods: We held focus groups and interviews using a semi‐structured interview guide with parents of youth who initiated CGM over telehealth within 30 days of diagnosis during the SARS‐CoV‐2 pandemic. Questions aimed to explore experiences of starting CGM virtually. Groups and interviews were audio‐recorded, transcribed and analysed using thematic analysis. Results: Participants were 16 English‐speaking parents (age 43 ± 6 years; 63% female) of 15 youth (age 9 ± 4 years; 47% female; 47% non‐Hispanic White, 20% Hispanic, 13% Asian, 7% Black, 13% other). They described multiple benefits of the virtual visit including convenient access to high‐quality care; integrating Type 1 diabetes care into daily life; and being in the comfort of home. A minority experienced challenges with virtual care delivery; most preferred the virtual format. Participants expressed that clinics should offer a choice of virtual or in‐person to families initiating CGM in the future. Conclusion: Most parents appreciated receiving CGM initiation education via telehealth and felt it should be an option offered to all families. Further efforts can continue to enhance CGM initiation teaching virtually to address identified barriers. [ABSTRACT FROM AUTHOR]

Extent and Prevalence of Post-Exercise and Nocturnal Hypoglycemia Following Peri-Exercise Bol... I McCarthy O SP 1 sp , Deere R SP 4 sp , Churm R SP 1 sp , Dunseath GJ SP 2 sp , Jones C SP 2 sp , Eckstein ML SP 3 sp , Williams DM SP 2 sp , Hayes J SP 2 sp , Pitt J SP 1 sp , Bain SC SP 2 sp , Moser O SP 3 sp , Bracken RM SP 1 sp i I SP 1 sp Applied Sport, Technology, Exercise and Medicine Research Centre (A-STEM), College of Engineering, Swansea University, Swansea, UK; SP 2 sp Diabetes Research Group, Medical School, Swansea University, Swansea, UK; SP 3 sp Cardiovascular Diabetology Research Group, Division of Endocrinology and Diabetology, Department of Internal Medicine, Medical University of Graz, Graz, Austria; SP 4 sp Department for Health, University of Bath, Bath, UK i I Nutr Metab Cardiovasc Dis 2021; i B I 31 i b I : 227-236 i Background For individuals with type 1 diabetes (T1D), many factors can impact blood glucose management, such as physical activity, food consumption, and the timing of insulin delivery. Several papers were published this year on carbohydrate intake strategies to limit exercise-related hypoglycemia, including one by our team looking at a fast-acting carbohydrate dose of 0.3 g/kg body mass for 2 hours of fasted exercise ([35]) and another by Goulet-Gélinas and colleagues ([36]) who used the 0.5 g/kg body mass per hour of exercise prescription, given either in one dose or in a more distributed fashion. Results Fructose ingestion 30 minutes before exercise was well tolerated, did not promote hyperglycemia before exercise, and promoted an 88% risk reduction in the incidence of exercise-associated hypoglycemia, as compared to water ingestion (one event of hypoglycemia with fructose intake vs six events in the water only protocol). [Extracted from the article]

Background: This study compared glucose control with fast-acting insulin aspart (FiAsp) versus insulin aspart following moderate-intensity exercise (MIE) and high-intensity exercise (HIE) using a second-generation closed-loop (CL) system in people with type 1 diabetes. Materials and Methods: This randomized crossover study compared FiAsp versus insulin aspart over four sessions during MIE and HIE with CL insulin delivery by the MiniMed™ Advanced hybrid CL system. Participants were randomly assigned FiAsp and insulin aspart each for 6 weeks and within each period performed, in random order, 40 min MIE (∼50% VO2max) and HIE (6 × 2 min ∼80% VO2max; 5 min recovery). The primary outcome was continuous glucose monitoring (CGM) time in range (TIR, 3.9-10.0 mM) for 24 h following exercise. Results: Sixteen adults (9 male; age 48 [37, 57] years; hemoglobin A1c (HbA1c) 7.0 [6.4, 7.2] %; duration diabetes 30 [17, 41] years) were recruited. In the 24 h postexercise, median TIR was >81%, time in hypoglycemia (<3.9 mM) was <4%, and time in hyperglycemia (>10 mM) was <17% for both exercise conditions and insulin formations, with no significant differences between insulins (P > 0.05). In the 2 h postexercise and overnight, the TIR approached 100% for all conditions. Conclusions: There were no differences in TIR during and 24 h after MIE or HIE when comparing insulin aspart with FiAsp delivered by a second-generation CL system. Insulin formulations with an offset in action greater than FiAsp are needed to provide a meaningful improvement in CL glucose control with exercise. Clinical Trial Registration number: ACTRN12619000469112. [ABSTRACT FROM AUTHOR]

Anticipation of Historical Exercise Patterns by a Novel Artificial Pancreas System Reduces Hy... I Garcia-Tirado J SP 1 sp , Brown SA SP 1,2 sp , Laichuthai N SP 1,3 sp , Colmegna P SP 1 sp , Koravi CLK SP 1 sp , Ozaslan B SP 1 sp , Corbett JP SP 1 sp , Barnett CL SP 1 sp , Pajewski M SP 1 sp , Oliveri MC SP 1 sp , Myers H SP 1 sp , Breton MD SP 1 sp i I SP 1 sp Center for Diabetes Technology, University of Virginia, Charlottesville, VA; SP 2 sp Division of Endocrinology and Metabolism, Department of Medicine, University of Virginia, Charlottesville, VA; SP 3 sp Excellence Center in Diabetes, Hormone, and Metabolism, King Chulalongkorn Memorial Hospital, Thai Red Cross Society, and Division of Endocrinology and Metabolism, Department of Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand i Diabetes Technol Ther 2021; 23: 277-285 This manuscript is also discussed in article on Decision Support Systems and Closed-Loop, page XX Background Maintaining tight glycemic control during and after exercise is often a major challenge for individuals with type 1 diabetes. Results Fructose ingestion 30 minutes before exercise was well tolerated, did not promote hyperglycemia before exercise, and promoted an 88% risk reduction in the incidence of exercise-associated hypoglycemia, as compared to water ingestion (one event of hypoglycemia with fructose intake vs six events in the water only protocol). Several papers were published this year on carbohydrate intake strategies to limit exercise-related hypoglycemia, including one by our team looking at a fast-acting carbohydrate dose of 0.3 g/kg body mass for 2 hours of fasted exercise ([35]) and another by Goulet-Gélinas and colleagues ([36]) who used the 0.5 g/kg body mass per hour of exercise prescription, given either in one dose or in a more distributed fashion. [Extracted from the article]

Aim: This study aimed to capture the experience of parents of youth with recent onset Type 1 diabetes who initiated use of continuous glucose monitoring (CGM) technology soon after diagnosis, which is a new practice. Methods: Focus groups and individual interviews were conducted with parents of youth with Type 1 diabetes who had early initiation of CGM as part of a new clinical protocol. Interviewers used a semi‐structured interview guide to elicit feedback and experiences with starting CGM within 30 days of diagnosis, and the benefits and barriers they experienced when adjusting to this technology. Groups and interviews were audio recorded, transcribed and analysed using content analysis. Results: Participants were 16 parents (age 44.13 ± 8.43 years; 75% female; 56.25% non‐Hispanic White) of youth (age 12.38 ± 4.15 years; 50% female; 50% non‐Hispanic White; diabetes duration 10.35 ± 3.89 months) who initiated CGM 11.31 ± 7.33 days after diabetes diagnosis. Overall, parents reported high levels of satisfaction with starting CGM within a month of diagnosis and described a high level of reliance on the technology to help manage their child's diabetes. All participants recommended early CGM initiation for future families and were committed to continue using the technology for the foreseeable future, provided that insurance covered it. Conclusion: Parents experienced CGM initiation shortly after their child's Type 1 diabetes diagnosis as a highly beneficial and essential part of adjusting to living with diabetes. [ABSTRACT FROM AUTHOR]

Objective: Exercising while fasted with type 1 diabetes facilitates weight loss; however, the best strategy to maintain glucose stability remains unclear.Research Design and Methods: Fifteen adults on continuous subcutaneous insulin infusion completed three sessions of fasted walking (120 min at 45% VO2max) in a randomized crossover design: 50% basal rate reduction, set 90 min pre-exercise (-90min50%BRR); usual basal rate with carbohydrate intake of 0.3 g/kg/h (CHO-only); and combined 50% basal rate reduction set at exercise onset with carbohydrate intake of 0.3 g/kg/h (Combo).Results: Combo had a smaller change in glucose (5 ± 47 mg/dL) versus CHO-only (-49 ± 61 mg/dL, P = 0.03) or -90min50%BRR (-34 ± 45 mg/dL). The -90min50%BRR strategy produced higher β-hydroxybutyrate levels (0.4 ± 0.3 vs. 0.1 ± 0.1 mmol/L) and greater fat oxidation (0.51 ± 0.2 vs. 0.39 ± 0.1 g/min) than CHO-only (both P < 0.05).Conclusions: All strategies examined produced stable glycemia for fasted exercise, but a 50% basal rate reduction, set 90 min pre-exercise, eliminates carbohydrate needs and enhances fat oxidation better than carbohydrate feeding with or without a basal rate reduction set at exercise onset. [ABSTRACT FROM AUTHOR]

Background: Gestational diabetes mellitus (GDM) management using self-monitoring blood glucose (SMBG) does not normalize pregnancy outcomes. Objective: We aimed to conduct an observational study to explore if continuous glucose monitoring (CGM) could identify elevated glucose levels not apparent in women with GDM managed using SMBG. Study Design: A 7-day masked-CGM (iPro; Medtronic) was performed within 2 weeks of GDM diagnosis, immediately post-GDM education, but before insulin commencement as determined by SMBG. CGM data regarding hyperglycemia (sensor glucose >126 mg/dL [06:00-00:00 h] and >99 mg/dL [00:00-06:00 h] for >10% of time), time with health care professionals, treatment, and pregnancy outcome were collected. Comparisons (Mann-Whitney test) were performed between subjects subsequently commenced on insulin versus those continued with diet and lifestyle measures alone. Results: Ninety women of mean (standard deviation) gestational age weeks 27(1) were studied. Those prescribed insulin (n = 34) compared with those managed with diet and lifestyle alone (n = 56) had a greater time in hyperglycemia (P = 0.0001). Of those not prescribed insulin, 35/56 (61%) breached CGM cutoffs between 00:00 and 06:00 h; 11/56 (20%) breached 6.00-00.00 h CGM cutoffs for >10% of the time; and 21/45 (47%) with optimal CGM glucose levels during the daytime spent >10% time in hyperglycemia between 00.00 and 06:00 h. In contrast, SMBG measurements exceeded the clinical targets of <120 mg/dL postdinner in 5.4% and <100 mg/dL fasting in 0% of the subjects. Conclusions: CGM provides a more comprehensive assessment of nocturnal hyperglycemia than SMBG and could improve targeting of interventions in GDM. Larger studies to better define CGM targets are required, which once established will inform studies aimed at targeting nocturnal glucose levels. [ABSTRACT FROM AUTHOR]

This year, we screened more than 750 potentially eligible titles on PubMed and other common search engines for manuscripts on "exercise and diabetes" published between July 1, 2018, and June 30, 2019. Although hypoglycemia was not eliminated entirely during exercise, MAAP could maintain glucose levels safely and minimize the prevalence of hypoglycemia independent of the exercise type, despite requiring the system to detect exercise onset and predict a glucose decline before measures could be taken to prevent hypoglycemia. Pump suspension at the onset of exercise resulted in more episodes of hypoglycemia during exercise than did either 50% or 80% BRR 90 minutes prior to exercise (7 vs 1 vs 1; I P i <0.05). Overall, a 50%-80% BRR applied 90 minutes preexercise did not cause preexercise hyperglycemia and attenuated the glucose drop during moderate intensity exercise. [Extracted from the article]

Background: Real-time continuous glucose monitoring (CGM) devices help detect glycemic excursions associated with exercise, meals, and insulin dosing in patients with type 1 diabetes (T1D). However, the delay between interstitial and blood glucose may result in CGM underestimating the true change in glycemia during activity. The purpose of this study was to examine CGM discrepancies during exercise and the meal postexercise versus self-monitoring of blood glucose (SMBG). Methods: Seventeen adults with T1D using insulin pump therapy and CGM completed 60 min of aerobic exercise on three occasions. A standardized meal was given 30 min postexercise. SMBG was measured during exercise and in recovery using OmniPod® Personal Diabetes Manager (PDM; Insulet, Billerica, MA) with built-in glucose meter (FreeStyle; Abbott Laboratories, Abbott Park, IL), while CGM was measured with Dexcom G4® with 505 algorithm (n = 4) or G5® (n = 13), which were calibrated with subjects' own PDM. Results: SMBG showed a large drop in glycemia during exercise, while CGM showed a lag of 12 ± 11 (mean ± standard deviation) minutes and bias of -7 ± 19 mg/dL/min during activity. Mean absolute relative difference (MARD) for CGM versus SMBG was 13 (6-22)% [median (interquartile range)] during exercise and 8 (5-14)% during mealtime. Clarke error grids showed CGM values were in zones A and B 94%-99% of the time for SMBG. Conclusion: In summary, the drop in CGM lags behind the drop in blood glucose during prolonged aerobic exercise by 12 ± 11 min, and MARD increases to 13 (6-22)% during exercise as well. Therefore, if hypoglycemia is suspected during exercise, individuals should confirm glucose levels with a capillary glucose measurement. [ABSTRACT FROM AUTHOR]

Objective: To reduce exercise-associated hypoglycemia, individuals with type 1 diabetes on continuous subcutaneous insulin infusion typically perform basal rate reductions (BRRs) and/or carbohydrate feeding, although the timing and amount of BRRs necessary to prevent hypoglycemia are unclear. The goal of this study was to determine if BRRs set 90 min pre-exercise better attenuate hypoglycemia versus pump suspension (PS) at exercise onset.Research Design and Methods: Seventeen individuals completed three 60-min treadmill exercise (∼50% of VO2peak) visits in a randomized crossover design. The insulin strategies included 1) PS at exercise onset, 2) 80% BRR set 90 min pre-exercise, and 3) 50% BRR set 90 min pre-exercise.Results: Blood glucose level at exercise onset was higher with 50% BRR (191 ± 49 mg/dL) vs. 80% BRR (164 ± 41 mg/dL; P < 0.001) and PS (164 ± 45 mg/dL; P < 0.001). By exercise end, 80% BRR showed the smallest drop (-31 ± 58 mg/dL) vs. 50% BRR (-47 ± 50 mg/dL; P = 0.04) and PS (-67 ± 41 mg/dL; P < 0.001). With PS, 7 out of 17 participants developed hypoglycemia versus 1 out of 17 in both BRR conditions (P < 0.05). Following a standardized meal postexercise, glucose rose with PS and 50% BRR (both P < 0.05), but failed to rise with 80% BRR (P = 0.16). Based on interstitial glucose, overnight mean percent time in range was 83%, 83%, and 78%, and time in hypoglycemia was 2%, 1%, and 5% with 80% BRR, 50% BRR, and PS, respectively (all P > 0.05).Conclusions: Overall, a 50-80% BRR set 90 min pre-exercise improves glucose control and decreases hypoglycemia risk during exercise better than PS at exercise onset, while not compromising the postexercise meal glucose control. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the pattern of change in blood glucose concentrations and hypoglycemia risk in response to prolonged aerobic exercise in adolescents with type 1 diabetes (T1D) that had a wide range in pre‐exercise blood glucose concentrations. Methods: Individual blood glucose responses to prolonged (~60 minutes) moderate‐intensity exercise were profiled in 120 youth with T1D. Results: The mean pre‐exercise blood glucose concentration was 178 ± 66 mg/dL, ranging from 69 to 396 mg/dL, while the mean change in glucose during exercise was −76 ± 55 mg/dL (mean ± SD), ranging from +83 to −257 mg/dL. Only 4 of 120 youth (3%) had stable glucose levels during exercise (ie, ± ≤10 mg/dL), while 4 (3%) had a rise in glucose >10 mg/dL, and the remaining (93%) had a clinically significant drop (ie, >10 mg/dL). A total of 53 youth (44%) developed hypoglycemia (≤70 mg/dL) during exercise. The change in glucose was negatively correlated with the pre‐exercise glucose concentration (R2 = 0.44, P < 0.001), and tended to be greater in those on multiple daily insulin injections (MDI) vs continuous subcutaneous insulin infusion (CSII) (−98 ± 15 vs −65 ± 7 mg/dL, P = 0.05). No other collected variables appeared to predict the change in glucose including age, weight, height, body mass index, disease duration, daily insulin dose, HbA1c, or sex. Conclusion: Youth with T1D have variable glycemic responses to prolonged aerobic exercise, but this variability is partially explained by their pre‐exercise blood glucose levels. When no implementation strategies are in place to limit the drop in glycemia, the incidence of exercise‐associated hypoglycemia is ~44% and having a high pre‐exercise blood glucose concentration is only marginally protective. [ABSTRACT FROM AUTHOR]

The article offers information on an effective strategy for type 2 diabetes prevention and for the overall health and well-being of people already diagnosed with all forms of diabetes mellitus. It mentions regular exercise helps patients to achieve their target HbA1c, lipid, and body composition goals, and also allows patients to derive all of the other benefits of being physically active; and also mentions various forms of physical activity improve insulin action and glucose control.

Caffeine is a substance that has been used in our society for generations, primarily for its effects on the central nervous system that causes wakefulness. Caffeine supplementation has become increasingly more popular as an ergogenic aid for athletes and considerable scientific evidence supports its effectiveness. Because of their potential to alter energy metabolism, the effects of coffee and caffeine on glucose metabolism in diabetes have also been studied both epidemiologically and experimentally. Predominantly targeting the adenosine receptors, caffeine causes alterations in glucose homeostasis by decreasing glucose uptake into skeletal muscle, thereby causing elevations in blood glucose concentration. Caffeine intake has also been proposed to increase symptomatic warning signs of hypoglycemia in patients with type 1 diabetes and elevate blood glucose levels in patients with type 2 diabetes. Other effects include potential increases in glucose counterregulatory hormones such as epinephrine, which can also decrease peripheral glucose disposal. Despite these established physiological effects, increased coffee intake has been associated with reduced risk of developing type 2 diabetes in large-scale epidemiological studies. This review paper highlights the known effects of caffeine on glucose homeostasis and diabetes metabolism during rest and exercise. [ABSTRACT FROM AUTHOR]

The article presents the discussion on progress being made in the field of diabetes management and physical activity (PA). Topics include guideline incorporating a new theme focused on strategies for glucose management for athletes living with T1D based in part on a randomized controlled trial (RCT); and optimizing time in range and preventing hypoglycemia during and after exercise in all children and adolescents with diabetes.

Aim: To compare evening and overnight hypoglycemia risk after late afternoon exercise with a nonexercise control day in adults with type 1 diabetes using automated insulin delivery (AID). Methods: Thirty adults with type 1 diabetes using AID (Minimed 670G) performed in random order 40 min high intensity interval aerobic exercise (HIE), resistance (RE), and moderate intensity aerobic exercise (MIE) exercise each separated by >1 week. The closed-loop set-point was temporarily increased 2 h pre-exercise and a snack eaten if plasma glucose was ≤126 mg/dL pre-exercise. Exercise commenced at ∼16:00. A standardized meal was eaten at ∼20:40. Hypoglycemic events were defined as a continuous glucose monitor (CGM) reading <70 mg/dL for ≥15 min. Four-hour postevening meal and overnight (00:00-06:00) CGM metrics for exercise were compared with the prior nonexercise day. Results: There was no severe hypoglycemia. Between 00:00 and 06:00, the proportion of nights with hypoglycemia did not differ postexercise versus control for HIE (18% vs. 11%; P = 0.688), RE (4% vs. 14%; P = 0.375), and MIE (7% vs. 14%; P = 0.625). Time in range (TIR) (70-180 mg/dL), >75% for all nights, did not differ between exercise conditions and control. Hypoglycemia episodes postmeal after exercise versus control did not differ for HIE (22% vs. 7%; P = 0.219) and MIE (10% vs. 14%; P > 0.999), but were greater post-RE (39% vs. 10%; P = 0.012). Conclusions: Overnight TIR was excellent with AID without increased hypoglycemia postexercise between 00:00 and 06:00 compared with nonexercise days. In contrast, hypoglycemia risk was increased after the first meal post-RE, suggesting the importance of greater vigilance and specific guidelines for meal-time dosing, particularly with vigorous RE. ACTRN12618000905268. [ABSTRACT FROM AUTHOR]

Aims/Hypothesis: In diabetes haptoglobin (Hp) 2 vs Hp 1 allelic product is associated with cardiac and renal complications. Few studies report both Hp phenotype and Hp levels. In a Fenofibrate Intervention and Event Lowering in Diabetes (FIELD) trial substudy we evaluated the Hp phenotype, Hp levels, and fenofibrate effects. Materials and Methods: In 480 adults with type 2 diabetes (T2D) the Hp phenotype was assessed and the Hp level quantified (both using ELISAs assays) in plasma from baseline, after 6 weeks of fenofibrate, and (in n = 200) at 2 years post‐randomization to fenofibrate or placebo. Results: The Hp phenotypes 1‐1, 2‐1, and 2‐2 frequencies were 15%, 49%, and 36%, respectively. Baseline Hp levels differed by phenotype (P < 0.0001) and decreased (median 21%) after 6 weeks fenofibrate in all phenotypes (adjusted mean (95% CI): −0.27 (−0.32, −0.23) mg/mL in Hp 1‐1, −0.29 (−0.31, −0.27) mg/mL in Hp 2‐1 and −0.05 (−0.07, −0.02) mg/mL in Hp 2‐2 (P = 0.005 and P = 0.055 vs Hp 1‐1 and Hp 2‐1, respectively)). At 2 years post‐randomization the Hp levels in the placebo group had returned to baseline, whilst the fenofibrate‐group levels remained similar to the 6 week levels. Conclusions: In type 2 diabetes, Hp levels differ by Hp phenotype and are decreased by fenofibrate in all phenotypes, but the effect is diminished in Hp 2‐2. [ABSTRACT FROM AUTHOR]

This pilot and feasibility study aimed to identify dietary strategies to optimize glycemic control and weight management in overweight or obese young adults with T1D. In a sequential multiple assignment randomized trial, participants were randomized to a hypocaloric low-carbohydrate (CHO; 20-25% CHO), hypocaloric moderately low fat (30% energy fat), or Mediterranean (not calorie restricted) diet, with advice to maintain usual physical activity (PA). PA data were collected in a convenience sample of participants from 06/20 to 02/21. Young adults with T1D (n=27, age 25±3 years, 78% female, A1c 7.3±1.2%, BMI 30.7±3.4) wore PA trackers for 2-week periods during diet assignments. Median (IQR) daily steps were 4,931 (3,443-7,363), 5,562 (4,191-9,931), 6,457 (4,394-9,655) for Low CHO, Look AHEAD, and Mediterranean diets, respectively and daily moderate-to-vigorous PA (MVPA) mins were 16 (4-31), 18 (5-31), and 22 (6-32), respectively. Daily steps, active time, or MVPA did not differ by diet (p>0.05). We demonstrate that in a pilot study emphasizing diet and weight loss in young adults with T1D, PA was often below the recommended target of 30 mins MVPA/day (or 150 mins/week). Thus, a larger, adaptive weight management intervention will need to incorporate diet as well as safe and effective PA strategies for overweight and obese young adults with T1D. Disclosure: D. P. Zaharieva: None. D. M. Maahs: Advisory Panel; Self; Abbott Diabetes, Dompe, Eli Lilly and Company, Medtronic, Novo Nordisk, Consultant; Self; aditxt. For the act1on study: n/a. F. R. Muntis: None. N. Arrizon- ruiz: None. J. Thomas: None. E. J. Mayer-davis: None. A. Addala: None. M. A. Clements: Consultant; Self; Eli Lilly and Company, Employee; Self; Glooko, Inc., Research Support; Self; Abbott Diabetes, Dexcom, Inc. A. Kollu: None. M. Riddell: Advisory Panel; Self; Zealand Pharma A/S, Consultant; Self; Lilly Diabetes, Research Support; Self; Dexcom, Inc., Insulet Corporation, Speaker's Bureau; Self; Novo Nordisk Inc., Sanofi, Stock/Shareholder; Self; Zucara Therapeutics Inc. Funding: National Institute of Diabetes and Digestive and Kidney Diseases (1DP3DK113358) [ABSTRACT FROM AUTHOR]

Aims: Continuous glucose monitoring (CGM) systems are standard of care for youth with type 1 diabetes with the goal of spending >70% time in range (TIR; 70–180 mg/dL, 3.9–10 mmol/L). We aimed to understand paediatric CGM user experiences with TIR metrics considering recent discussion of shifting to time in tight range (TITR; >50% time between 70 and 140 mg/dL, 3.9 and 7.8 mmol/L). Methods: Semi‐structured interviews and focus groups with adolescents with type 1 diabetes and parents of youth with type 1 diabetes focused on experiences with TIR goals and reactions to TITR. Groups and interviews were audio‐recorded, transcribed and analysed using content analysis. Results: Thirty participants (N = 19 parents: age 43.6 ± 5.3 years, 79% female, 47% non‐Hispanic White, 20 ± 5 months since child's diagnosis; N = 11 adolescents: age 15.3 ± 2 years, 55% female, 55% non‐Hispanic White, 16 ± 3 months since diagnosis) attended. Participants had varying levels of understanding of TIR. Some developed personally preferred glucose ranges. Parents often aimed to surpass 70% TIR. Many described feelings of stress and disappointment when they did not meet a TIR goal. Concerns about TITR included increased stress and burden; risk of hypoglycaemia; and family conflict. Some participants said TITR would not change their daily lives; others said it would improve their diabetes management. Families requested care team support and a clear scientific rationale for TITR. Conclusions: The wealth of CGM data creates frequent opportunities for assessing diabetes management and carries implications for management burden. Input from people with type 1 diabetes and their families will be critical in considering a shift in glycaemic goals and targets. [ABSTRACT FROM AUTHOR]

Objective: To compare glucose control with hybrid closed-loop (HCL) when challenged by high intensity exercise (HIE), moderate intensity exercise (MIE), and resistance exercise (RE) while profiling counterregulatory hormones, lactate, ketones, and kinetic data in adults with type 1 diabetes.Research Design and Methods: This study was an open-label multisite randomized crossover trial. Adults with type 1 diabetes undertook 40 min of HIE, MIE, and RE in random order while using HCL (Medtronic MiniMed 670G) with a temporary target set 2 h prior to and during exercise and 15 g carbohydrates if pre-exercise glucose was <126 mg/dL to prevent hypoglycemia. Primary outcome was median (interquartile range) continuous glucose monitoring time-in-range (TIR; 70-180 mg/dL) for 14 h post-exercise commencement. Accelerometer data and venous glucose, ketones, lactate, and counterregulatory hormones were measured for 280 min post-exercise commencement.Results: Median TIR was 81% (67, 93%), 91% (80, 94%), and 80% (73, 89%) for 0-14 h post-exercise commencement for HIE, MIE, and RE, respectively (n = 30), with no difference between exercise types (MIE vs. HIE; P = 0.11, MIE vs. RE, P = 0.11; and HIE vs. RE, P = 0.90). Time-below-range was 0% for all exercise bouts. For HIE and RE compared with MIE, there were greater increases, respectively, in noradrenaline (P = 0.01 and P = 0.004), cortisol (P < 0.001 and P = 0.001), lactate (P ≤ 0.001 and P ≤ 0.001), and heart rate (P = 0.007 and P = 0.015). During HIE compared with MIE, there were greater increases in growth hormone (P = 0.024).Conclusions: Under controlled conditions, HCL provided satisfactory glucose control with no difference between exercise type. Lactate, counterregulatory hormones, and kinetic data differentiate type and intensity of exercise, and their measurement may help inform insulin needs during exercise. However, their potential utility as modulators of insulin dosing will be limited by the pharmacokinetics of subcutaneous insulin delivery. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the use of faster acting (FIA) and standard insulin aspart (SIA) with hybrid automated insulin delivery (AID) in active youth with type 1 diabetes. Research Design and Methods: In this double-blind multinational randomized crossover trial, 30 children and adolescents with type 1 diabetes (16 females; aged 15.0 ± 1.7 years; baseline HbA1c 7.5% ± 0.9% [58 ± 9.8 mmol/mol]) underwent two unrestricted 4-week periods using hybrid AID with either FIA or SIA in random order. During both interventions, participants were using the hybrid AID (investigational version of MiniMed™ 780G; Medtronic). Participants were encouraged to exercise as frequently as possible, capturing physical activity with an activity monitor. The primary outcome was the percentage of sensor glucose time above range (180 mg/dL [10.0 mmol/L]) measured by continuous glucose monitoring. Results: In an intention-to-treat analysis, mean time above range was 31% ± 15% at baseline, 19% ± 6% during FIA use, and 20% ± 6% during SIA use with no difference between treatments: mean difference = −0.9%; 95% CI: −2.4% to 0.6%; P = 0.23. Similarly, there was no difference in mean time in range (TIR) (78% and 77%) or median time below range (2.5% and 2.8%). Glycemic outcomes during exercise or postprandial periods were comparable for the two treatment arms. No severe hypoglycemia or diabetic ketoacidosis events occurred. Conclusions: FIA was not superior to SIA with hybrid AID system use in physically active children and adolescents with type 1 diabetes. Nonetheless, both insulin formulations enabled high overall TIR and low time above and below ranges, even during and after documented exercise. Trial Registration Clinicaltrials.gov: NCT04853030. [ABSTRACT FROM AUTHOR]

To conduct an Australian community-led survey of adults with type 1 diabetes (T1D), identifying priorities for, and barriers to, optimal use of advanced glucose management technologies. A 30-question online survey of current or past users of insulin pump therapy (IPT), real-time continuous glucose monitoring (RT-CGM), or intermittently scanned CGM (isCGM) explored perceptions regarding device design, access, education, outcomes, and support. Between November 2021 and January 2022, surveys were completed by 3,380 participants (age [mean ± SD] 45 ± 16 years; 62% female; 20 ± 14 years diabetes), with 55%, 82%, and 55% reporting experience with IPT, RT-CGM, and isCGM, respectively. Overall, most considered diabetes technology '(extremely) important' for maintaining target glucose levels (98%) and reducing hypoglycaemia severity and frequency (93%). For most, technology contributed positively to emotional well-being (IPT 89%; RT-CGM 91%; isCGM 87%), which was associated with device effectiveness in maintaining glucose in range, comfort, and convenience. Barriers included affordability (IPT 68%; RT-CGM 81%; isCGM 69%) and insufficient information for informed choices about device suitability (IPT 39%; RT-CGM 41%; isCGM 36%). Technology is perceived by adults with T1D as important for managing glycaemia and emotional well-being. Modifiable barriers to use include affordability, and information regarding device suitability. [ABSTRACT FROM AUTHOR]

Background. Managing glycemia around exercise is challenging for individuals with type 1 diabetes (T1D) and their healthcare professionals (HCP). We investigated HCP knowledge and confidence around exercise counseling for youth with T1D worldwide. Objective. To assess HCP familiarity with ISPAD Clinical Practice Consensus Guidelines and confidence to deliver recommendations about T1D and exercise. Methods. A new online survey was developed on strategies and competencies about exercise for youth with T1D, comprising of 64 questions, divided into eight different categories, assessing HCPs perceived exercise knowledge, confidence, training, and barriers to exercise counseling. Results. A total of 125 HCPs mean ± SD age 42 ± 8.2 years (74% female, 73% physicians) completed the survey. The ISPAD exercise guidelines were considered familiar to 68/125 (54%) of responders. Overall, 91/125 (73%) felt confident with giving recommendations about exercise with 47/125 (38%) recommending 45–60 mins/day of physical activity, while 16/125 (13%) recommended >60 mins/day. Several topics related to self-management around exercise were covered by most, but not all responders, and differences were observed in exercise content "confidence" and/or "competence" based on geographic location (p = 0.048). No differences in exercise recommendation dose, confidence, or familiarity with ISPAD guidelines were observed for age, sex, type of HCP, years in practice, or healthcare type. Conclusions. Exercise counseling for youth with T1D remains a challenge in most healthcare settings, globally. In general, the number of physically active minutes per week is under-prescribed for youth with T1D and many HCPs in various settings around the world feel that more professional education is needed to boost confidence around the education of several exercise-related topics. [ABSTRACT FROM AUTHOR]

Aims: Co‐management of weight and glycaemia is critical yet challenging in type 1 diabetes (T1D). We evaluated the effect of a hypocaloric low carbohydrate, hypocaloric moderate low fat, and Mediterranean diet without calorie restriction on weight and glycaemia in young adults with T1D and overweight or obesity. Materials and Methods: We implemented a 9‐month Sequential, Multiple Assignment, Randomized Trial pilot among adults aged 19‐30 years with T1D for ≥1 year and body mass index 27‐39.9 kg/m2. Re‐randomization occurred at 3 and 6 months if the assigned diet was not acceptable or not effective. We report results from the initial 3‐month diet period and re‐randomization statistics before shutdowns due to COVID‐19 for primary [weight, haemoglobin A1c (HbA1c), percentage of time below range <70 mg/dl] and secondary outcomes [body fat percentage, percentage of time in range (70‐180 mg/dl), and percentage of time below range <54 mg/dl]. Models adjusted for design, demographic and clinical covariates tested changes in outcomes and diet differences. Results: Adjusted weight and HbA1c (n = 38) changed by −2.7 kg (95% CI −3.8, −1.5, P <.0001) and −0.91 percentage points (95% CI −1.5, −0.30, P =.005), respectively, while adjusted body fat percentage remained stable, on average (P =.21). Hypoglycaemia indices remained unchanged following adjustment (n = 28, P >.05). Variability in all outcomes, including weight change, was considerable (57.9% were re‐randomized primarily due to loss of <2% body weight). No outcomes varied by diet. Conclusions: Three months of a diet, irrespective of macronutrient distribution or caloric restriction, resulted in weight loss while improving or maintaining HbA1c levels without increasing hypoglycaemia in adults with T1D. [ABSTRACT FROM AUTHOR]

Aims: Using data from the ACT1ON study, we conducted secondary analyses to assess the relationship between minutes of moderate-to-vigorous physical activity (MVPA) and glycemia in adults with type 1 diabetes (T1D) and overweight or obesity. Materials and Methods: Participants (n = 66) with T1D provided measures of glycemia (hemoglobin A1c [HbA1c], percent of time below range <70 mg/dL, time-in-range [TIR 70-180 mg/dL], and time above range [TAR >180 mg/dL]) and self-reported physical activity (Global Physical Activity Questionnaire [GPAQ] and Previous Day Physical Activity Recalls [PDPAR]) at baseline, 3, 6, and 9 months postintervention. Wearable activity data were available for a subset of participants (n = 27). Associations were estimated using mixed effects regression models adjusted for design, demographic, clinical, and dietary covariates. Results: Among young adults 19-30 years of age with a baseline HbA1c of 7.9% ± 1.4% and body mass index of 30.3 (interquartile range 27.9, 33.8), greater habitual weekly MVPA minutes were associated with higher HbA1c through the GPAQ (P < 0.01) and wearable activity data (P = 0.01). We did not observe a significant association between habitual MVPA and any continuous glucose monitoring metrics. Using PDPAR data, however, we observed that greater daily MVPA minutes were associated with more TAR (P < 0.01) and reduced TIR (P < 0.01) on the day following reported physical activity. Conclusions: Among young adults with T1D and overweight or obesity, increased MVPA was associated with worsened glycemia. As physical activity is vital to cardiovascular health and weight management, additional research is needed to determine how to best support young adults with T1D and overweight or obesity in their efforts to increase physical activity. Clinical Trial Registration number: NCT03651622. [ABSTRACT FROM AUTHOR]

The article reviews the Omnipod 5 automated insulin delivery system for diabetes management from Insulet Corp.

Background Comanagement of glycemia and adiposity is the cornerstone of cardiometabolic risk reduction in type 1 diabetes (T1D), but targets are often not met. The intestinal microbiota and microbiota-derived short-chain fatty acids (SCFAs) influence glycemia and adiposity but have not been sufficiently investigated in longstanding T1D. Objectives We evaluated the hypothesis that an increased abundance of SCFA-producing gut microbes, fecal SCFAs, and intestinal microbial diversity were associated with improved glycemia but increased adiposity in young adults with longstanding T1D. Methods Participants provided stool samples at ≤4 time points (NCT03651622: https://clinicaltrials.gov/ct2/show/NCT03651622). Sequencing of the 16S ribosomal RNA gene measured abundances of SCFA-producing intestinal microbes. GC-MS measured total and specific SCFAs (acetate, butyrate, propionate). DXA (body fat percentage and percentage lean mass) and anthropometrics (BMI) measured adiposity. Continuous glucose monitoring [percentage of time in range (70–180 mg/dL), above range (>180 mg/dL), and below range (54–69 mg/dL)] and glycated hemoglobin (i.e. HbA1c) assessed glycemia. Adjusted and Bonferroni-corrected generalized estimating equations modeled the associations of SCFA-producing gut microbes, fecal SCFAs, and intestinal microbial diversity with glycemia and adiposity. COVID-19 interrupted data collection, so models were repeated restricted to pre-COVID-19 visits. Results Data were available for ≤45 participants at 101 visits (including 40 participants at 54 visits pre-COVID-19). Abundance of Eubacterium hallii was associated inversely with BMI (all data). Pre-COVID-19, increased fecal propionate was associated with increased percentage of time above range and reduced percentage of time in target and below range; and abundances of 3 SCFA-producing taxa (Ruminococcus gnavus , Eubacterium ventriosum , and Lachnospira) were associated inversely with body fat percentage, of which two microbes were positively associated with percentage lean mass. Abundance of Anaerostipes was associated with reduced percentage of time in range (all data) and with increased body fat percentage and reduced percentage lean mass (pre-COVID-19). Conclusions Unexpectedly, fecal propionate was associated with detriment to glycemia, whereas most SCFA-producing intestinal microbes were associated with benefit to adiposity. Future studies should confirm these associations and determine their potential causal linkages in T1D. This study is registered at clinical.trials.gov (NCT03651622; https://clinicaltrials.gov/ct2/show/NCT03651622). [ABSTRACT FROM AUTHOR]

Objective: To assess the relationship between mindfulness and glycemia among adolescents with type 1 diabetes (T1D) with suboptimal glycemia, and evaluate the potential mediation by ingestive behaviors, including disordered eating, and impulsivity. Research Design and Methods: We used linear mixed models for hemoglobin A1c (HbA1c) and linear regression for continuous glucose monitoring (CGM) to study the relationship of mindfulness [Child and Adolescent Mindfulness Measure (CAMM)] and glycemia in adolescents with T1D from the 18‐month Flexible Lifestyles Empowering Change (FLEX) trial. We tested for mediation of the mindfulness‐glycemia relationship by ingestive behaviors, including disordered eating (Diabetes Eating Problem Survey—Revised), restrained eating, and emotional eating (Dutch Eating Behavior Questionnaire); and impulsivity (total, attentional, and motor, Barrett Impulsiveness Scale). Results: At baseline, participants (n = 152) had a mean age of 14.9 ± 1.1 years and HbA1c of 9.4 ± 1.2% [79 ± 13 mmol/mol]. The majority of adolescents were non‐Hispanic white (83.6%), 50.7% were female, and 73.0% used insulin pumps. From adjusted mixed models, a 5‐point increase in mindfulness scores was associated with a −0.19% (95%CI −0.29, −0.08, p = 0.0006) reduction in HbA1c. We did not find statistically significant associations between mindfulness and CGM metrics. Mediation of the relationship between mindfulness and HbA1c by ingestive behaviors and impulsivity was not found to be statistically significant. Conclusions: Among adolescents with T1D and suboptimal glycemia, increased mindfulness was associated with lower HbA1c levels. Future studies may consider mindfulness‐based interventions as a component of treatment for improving glycemia among adolescents with T1D, though more data are needed to assess feasibility and efficacy. [ABSTRACT FROM AUTHOR]

Objective: To evaluate glucose control using fast-acting insulin aspart (faster aspart) compared with insulin aspart (IAsp) delivered by the MiniMed Advanced Hybrid Closed-Loop (AHCL) system in adults with type 1 diabetes.Research Design and Methods: In this randomized, open-label, crossover study, participants were assigned to receive faster aspart or IAsp in random order. Stages 1 and 2 comprised of 6 weeks in closed loop, preceded by 2 weeks in open loop. This was followed by stage 3, whereby participants changed directly back to the insulin formulation used in stage 1 for 1 week in closed loop. Participants chose their own meals except for two standardized meal tests, a missed meal bolus and late meal bolus. The primary outcome was the percentage of time sensor glucose values were from 70 to 180 mg/dL (time in range; [TIR]).Results: Twenty-five adults (52% male) were recruited; the median (interquartile range) age was 48 (37, 57) years, and the median HbA1c was 7.0% (6.6, 7.2) (53 [49, 55] mmol/mol). Faster aspart demonstrated greater overall TIR compared with IAsp (82.3% [78.5, 83.7] vs. 79.6% [77.0, 83.4], respectively; mean difference 1.9% [0.5, 3.3]; P = 0.007). Four-hour postprandial glucose TIR was higher using faster aspart compared with IAsp for all meals combined (73.6% [69.4, 80.2] vs. 72.1% [64.5, 78.5], respectively; median difference 3.5% [1.0, 7.3]; P = 0.003). There was no ketoacidosis or severe hypoglycemia.Conclusions: Faster aspart safely improved glucose control compared with IAsp in a group of adults with well-controlled type 1 diabetes using AHCL. The modest improvement was mainly related to mealtime glycemia. While the primary outcome demonstrated statistical significance, the clinical impact may be small, given an overall difference in TIR of 1.9%. [ABSTRACT FROM AUTHOR]

14 Kennedy A, Narendran P, Andrews RC, Daley A, Greenfield SM, Group E. Attitudes and barriers to exercise in adults with a recent diagnosis of type 1 diabetes: a qualitative study of participants in the exercise for type 1 diabetes (extod) study. Conclusion The hybrid regimen of using a proportion of basal insulin (i.e., 50%) via an ultra-long-acting insulin (degludec) once-daily injection, while maintaining a modified CSII basal insulin delivery (i.e., 50%), except for pump removal during exercise, appears to be safe and effective for glycemic control in adults with type 1 diabetes who exercise regularly. Prediction of hypoglycemia during aerobic exercise in adults with type 1 diabetes I Reddy R SP 1 sp , Resalat N SP 1 sp , Wilson LM SP 2 sp , Castle JR SP 2 sp , El Youssef J SP 1,2 sp , Jacobs PG SP 1 sp i I SP 1 sp Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR; SP 2 sp Department of Medicine, Division of Endocrinology, Harold Schnitzer Diabetes Health Center Oregon, Health & Science University, Portland, OR i I J Diabetes Sci Technol 2019; i B I 13 i b I : 919-927 i Background Although guidelines strongly recommend regular physical activity for individuals with type 1 diabetes (2,7), a primary barrier to exercise is the fear of hypoglycemia ([14],[15]). The greater risk for hypoglycemia in the hours after exercise is likely related to the increase in insulin sensitivity in the body that can last for several hours ([4]), thereby potentially reducing dinner bolus insulin needs ([5]). [Extracted from the article]

Objective: To investigate physiological responses to cardiopulmonary exercise (CPX) testing in adults with type 1 diabetes compared with age-, sex-, and BMI-matched control participants without type 1 diabetes.Research Design and Methods: We compared results from CPX tests on a cycle ergometer in individuals with type 1 diabetes and control participants without type 1 diabetes. Parameters were peak and threshold variables of VO2, heart rate, and power output. Differences between groups were investigated through restricted maximum likelihood modeling and post hoc tests. Differences between groups were explained by stepwise linear regressions (P < 0.05).Results: Among 303 individuals with type 1 diabetes (age 33 [interquartile range 22; 43] years, 93 females, BMI 23.6 [22; 26] kg/m2, HbA1c 6.9% [6.2; 7.7%] [52 (44; 61) mmol/mol]), VO2peak (32.55 [26.49; 38.72] vs. 42.67 ± 10.44 mL/kg/min), peak heart rate (179 [170; 187] vs. 184 [175; 191] beats/min), and peak power (216 [171; 253] vs. 245 [200; 300] W) were lower compared with 308 control participants without type 1 diabetes (all P < 0.001). Individuals with type 1 diabetes displayed an impaired degree and direction of the heart rate-to-performance curve compared with control participants without type 1 diabetes (0.07 [-0.75; 1.09] vs. 0.66 [-0.28; 1.45]; P < 0.001). None of the exercise physiological responses were associated with HbA1c in individuals with type 1 diabetes.Conclusions: Individuals with type 1 diabetes show altered responses to CPX testing, which cannot be explained by HbA1c. Intriguingly, the participants in our cohort were people with recent-onset type 1 diabetes; heart rate dynamics were altered during CPX testing. [ABSTRACT FROM AUTHOR]

Physical exercise is an important component in the management of type 1 diabetes across the lifespan. Yet, acute exercise increases the risk of dysglycaemia, and the direction of glycaemic excursions depends, to some extent, on the intensity and duration of the type of exercise. Understandably, fear of hypoglycaemia is one of the strongest barriers to incorporating exercise into daily life. Risk of hypoglycaemia during and after exercise can be lowered when insulin‐dose adjustments are made and/or additional carbohydrates are consumed. Glycaemic management during exercise has been made easier with continuous glucose monitoring (CGM) and intermittently scanned continuous glucose monitoring (isCGM) systems; however, because of the complexity of CGM and isCGM systems, both individuals with type 1 diabetes and their healthcare professionals may struggle with the interpretation of given information to maximise the technological potential for effective use around exercise (ie, before, during and after). This position statement highlights the recent advancements in CGM and isCGM technology, with a focus on the evidence base for their efficacy to sense glucose around exercise and adaptations in the use of these emerging tools, and updates the guidance for exercise in adults, children and adolescents with type 1 diabetes. [ABSTRACT FROM AUTHOR]

This pilot study delivered a comprehensive exercise education intervention to youth with new-onset type 1 diabetes (T1D) and their parents to increase knowledge and confidence with physical activity (PA) shortly after diagnosis. Youth initiated continuous glucose monitoring (CGM) and PA trackers within 1 month of diagnosis. Youth and their parents received the 4-session intervention over 12 months. Participants completed self-report questionnaires at baseline, 6- and 12-months. Surveys were analyzed using linear mixed effects models. Semi-structured interviews and focus groups explored experiences with the exercise education intervention. Groups and interviews were audio-recorded, transcribed, and analyzed using content analysis. A total of 16 parents (aged 46 ± 7 years; 88 % female; 67 % non-Hispanic White) and 17 youth (aged 14 ± 2 years; 41 % female; 65 % non-Hispanic White) participated. Worry about hypoglycemia did not worsen throughout the study duration. Parents and youth reported increased knowledge and confidence in managing T1D safely and preventing hypoglycemia during PA following receiving the tailored exercise education intervention. This study assessed a novel structured exercise education program for youth and their parents shortly following T1D diagnosis. These results support the broad translation and acceptability of a structured exercise education program in new-onset T1D. • 4T Exercise assesses structured exercise education in youth with new onset type 1 diabetes (T1D) and their parents • 4T Exercise involved four tele-health exercise education sessions during the first year following T1D diagnosis • Exercise education increased comfort, confidence, and knowledge of how to optimize glycemia during physical activity • Physical activity tracking and exercise education in new onset T1D is feasible and acceptable [ABSTRACT FROM AUTHOR]

Young adults with type 1 diabetes (T1D) often have difficulty co-managing weight and glycemia. The prevalence of overweight and obesity among individuals with T1D now parallels that of the general population and contributes to dyslipidemia, insulin resistance, and risk for cardiovascular disease. There is a compelling need to develop a program of research designed to optimize two key outcomes—weight management and glycemia—and to address the underlying metabolic processes and behavioral challenges unique to people with T1D. For an intervention addressing these dual outcomes to be effective, it must be appropriate to the unique metabolic phenotype of T1D, and to biological and behavioral responses to glycemia (including hypoglycemia) that relate to weight management. The intervention must also be safe, feasible, and accepted by young adults with T1D. In 2015, we established a consortium called ACT1ON : A dvancing C are for T ype 1 Diabetes and O besity N etwork, a transdisciplinary team of scientists at multiple institutions. The ACT1ON consortium designed a multi-phase study which, in parallel, evaluated the mechanistic aspects of the unique metabolism and energy requirements of individuals with T1D, alongside a rigorous adaptive behavioral intervention to simultaneously facilitate weight management while optimizing glycemia. This manuscript describes the design of our integrative study—comprised of an inpatient mechanistic phase and an outpatient behavioral phase—to generate metabolic, behavioral, feasibility, and acceptability data to support a future, fully powered sequential, multiple assignment, randomized trial to evaluate the best approaches to prevent and treat obesity while co-managing glycemia in people with T1D. Clinicaltrials.gov identifiers: NCT03651622 and NCT03379792. The present study references can be found here: https://clinicaltrials.gov/ct2/show/NCT03651622 https://clinicaltrials.gov/ct2/show/NCT03379792?term=NCT03379792&draw=2&rank=1 Submission Category: "Study Design, Statistical Design, Study Protocols". [ABSTRACT FROM AUTHOR]

Previous studies have shown that CGM use and frequent contact with the care team is associated with improved A1c. We hypothesized that youth with new onset T1D started on CGM with weekly CGM data review by a CDE would have improved outcomes compared to those on CGM alone. Youth with newly diagnosed T1D from 7/2018 to 3/2019 were started on CGM alone (control, n=46) while those from 3/2019 to 5/2020 were started on CGM with weekly data review by a CDE (GluVue, n=76). Dose adjustments were made via secure messaging. We visualized A1c trajectories using locally estimated scatter plot smoothing (Fig) and assessed for differences in A1c trajectory by GluVue status via cohort*time and cohort*time2 interaction terms in a linear mixed model regression adjusted for baseline characteristics (age, sex, race and insurance type). The mean (SD) A1c at diagnosis was 12.0% (1.8) in the control group and 12.3% (2.3) in the GluVue group. Baseline characteristics of control vs. GluVue: male 25% vs. 39%, Non-Hispanic White 41.3% vs. 35.5%, private insurance 80.4% vs. 73.7%. Mean A1c of the GluVue cohort was lower at 6 months (-0.45%), 9 months (-0.07%), and 12 months (-0.52%) post-diagnosis. A1c trajectories were significantly different between groups via regression analysis (p=0.004). Early initiation of CGM with remote monitoring was associated with lower A1c compared to CGM alone. These data support early CGM initiation plus care team contact in youth with T1D. Disclosure: P. Prahalad: None. K. K. Hood: Consultant; Self; Cecelia Health, Cercacor, LifeScan Diabetes Institute. D. Scheinker: Advisory Panel; Self; Carta Healthcare. M. Desai: None. D. M. Maahs: Advisory Panel; Self; Abbott Diabetes, Dompe, Eli Lilly and Company, Medtronic, Novo Nordisk, Consultant; Self; aditxt. V. Ding: None. B. Leverenz: None. J. Hooper: None. J. Leverenz: None. P. Sagan: None. A. Martinez-singh: None. A. Freeman: None. D. P. Zaharieva: None. Funding: National Institutes of Health (P30DK116074, R18DK122422) [ABSTRACT FROM AUTHOR]

CGM use is associated with improvements in A1c. We hypothesized that initiation of CGM in the 1st month after T1D diagnosis would improve A1c. Youth with newly diagnosed T1D from July 2018 to May 2020 (pilot cohort, n=122) were offered CGM initiation in the 1st month after T1D diagnosis (119 started CGM). We compared A1c outcomes in the pilot cohort with those diagnosed from 2014-2016 (controls, n=272) who were not offered early CGM. We visualized A1c trajectories using locally estimated scatter plot smoothing (Fig). We and assessed for differences in A1c trajectory by cohort via interaction terms in a linear mixed model adjusted for baseline characteristics (age, sex, race and insurance type). The mean A1c at diagnosis was higher in the pilot cohort (12.2 vs. 10.7%). The median age of diagnosis was 9.5 years [6.8, 13.3], 64% male, 38% non-Hispanic White, and 76% with private insurance in the pilot cohort. In this pilot, 89% initiated CGM in the first 30 days after diagnosis compared to 2% in the control cohort. After adjusting for baseline characteristics, the mean A1c of the pilot cohort was lower at 6 months (-0.81, p = 0.019), 9 months (-1.43, p = 0.013), and 12 months (-2.05, p = 0.012) post-diagnosis compared to the historic cohort. Early initiation of CGM was associated with a lower A1c compared to those in a historic cohort. These data support early initiation of CGM as standard of care in youth with T1D. Disclosure: P. Prahalad: None. J. Senaldi: None. A. Freeman: None. A. Addala: None. D. P. Zaharieva: None. K. K. Hood: Consultant; Self; Cecelia Health, Cercacor, LifeScan Diabetes Institute. D. Scheinker: Advisory Panel; Self; Carta Healthcare. M. Desai: None. D. M. Maahs: Advisory Panel; Self; Abbott Diabetes, Dompe, Eli Lilly and Company, Medtronic, Novo Nordisk, Consultant; Self; aditxt. V. Ding: None. B. Leverenz: None. J. Hooper: None. A. Chmielewski: None. B. P. Conrad: Advisory Panel; Self; Abbott Diabetes. J. Leverenz: None. A. Martinez-singh: None. P. Sagan: None. Funding: National Institutes of Health (R18DK122422, P30DK116074) [ABSTRACT FROM AUTHOR]

Hybrid closed-loop automated insulin delivery systems have been shown to aid glycemic control during exercise in type 1 diabetes, but their performance in the water has not been investigated. Anecdotal patient reports suggest continued function of the Omnipod 5 Automated Insulin Delivery System while swimming, despite reliance on Bluetooth, a radiofrequency with typically limited underwater transmission capability. Three frequent swimmers participating in the Omnipod 5 trial were identified. Omnipod 5 System and glycemic data from their combined 38 separate swimming sessions ranging 30-120 min (mean 48±16 min, total 31 hours) were retrospectively reviewed. Continuous glucose monitor (CGM)-to-Pod wireless communication during swims had a success rate of 58.4%. When sensor communication was lost, mean time without sensor data was 13±10 min (range 5-45 min). Automated mode was used in 74% of swims, of which insulin was automatically suspended in 86%. HypoProtect was activated for 42% of swims. See Table for CGM data. Overall, system communication was reasonable during swims and allowed for frequent insulin suspension. Glycemic control was unchanged across the three time points. These promising initial findings suggest that the Omnipod 5 System may have unique potential for use in water-based activities; further studies to investigate this potential and factors affecting performance are warranted. Disclosure: M. S. Hughes: None. R. S. Kingman: Research Support; Self; Insulet Corporation. R. Lal: Consultant; Self; Abbott Diabetes, Biolinq, Capillary Biomedical, Inc., Morgan Stanley, Tidepool. B. A. Buckingham: Advisory Panel; Self; Medtronic, Tolerion, Inc., Research Support; Self; Beta Bionics, Inc., Insulet Corporation, Medtronic, Tandem Diabetes Care. D. P. Zaharieva: None. [ABSTRACT FROM AUTHOR]