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OBJECTIVEMaintenance of glycemic control during and after exercise remains a major challenge for individuals with type 1 diabetes. Glycemic responses to exercise may differ by exercise type (aerobic, interval, or resistance), and the effect of activity type on glycemic control after exercise remains unclear.RESEARCH DESIGN AND METHODSThe Type 1 Diabetes Exercise Initiative (T1DEXI) was a real-world study of at-home exercise. Adult participants were randomly assigned to complete six structured aerobic, interval, or resistance exercise sessions over 4 weeks. Participants self-reported study and nonstudy exercise, food intake, and insulin dosing (multiple daily injection [MDI] users) using a custom smart phone application and provided pump (pump users), heart rate, and continuous glucose monitoring data.RESULTSA total of 497 adults with type 1 diabetes (mean age ± SD 37 ± 14 years; mean HbA1c ± SD 6.6 ± 0.8% [49 ± 8.7 mmol/mol]) assigned to structured aerobic (n = 162), interval (n = 165), or resistance (n = 170) exercise were analyzed. The mean (± SD) change in glucose during assigned exercise was −18 ± 39, −14 ± 32, and −9 ± 36 mg/dL for aerobic, interval, and resistance, respectively (P < 0.001), with similar results for closed-loop, standard pump, and MDI users. Time in range 70–180 mg/dL (3.9–10.0 mmol/L) was higher during the 24 h after study exercise when compared with days without exercise (mean ± SD 76 ± 20% vs. 70 ± 23%; P < 0.001).CONCLUSIONSAdults with type 1 diabetes experienced the largest drop in glucose level with aerobic exercise, followed by interval and resistance exercise, regardless of insulin delivery modality. Even in adults with well-controlled type 1 diabetes, days with structured exercise sessions contributed to clinically meaningful improvement in glucose time in range but may have slightly increased time below range.

OBJECTIVE Maintaining healthy glucose levels is critical for the management of type 1 diabetes (T1D), but the most efficacious and cost-effective approach (capillary self-monitoring of blood glucose [SMBG] or continuous [CGM] or intermittently scanned [isCGM] glucose monitoring) is not clear. We modeled the population-level impact of these three glucose monitoring systems on diabetes-related complications, mortality, and cost-effectiveness in adults with T1D in Canada. RESEARCH DESIGN AND METHODS We used a Markov cost-effectiveness model based on nine complication states for adults aged 18–64 years with T1D. We performed the cost-effectiveness analysis from a single-payer health care system perspective over a 20-year horizon, assuming a willingness-to-pay threshold of CAD 50,000 per quality-adjusted life-year (QALY). Primary outcomes were the number of complications and deaths and the incremental cost-effectiveness ratio (ICER) of CGM and isCGM relative to SMBG. RESULTS An initial cohort of 180,000 with baseline HbA1c of 8.1% was used to represent all Canadians aged 18–64 years with T1D. Universal SMBG use was associated with ∼11,200 people (6.2%) living without complications and ∼89,400 (49.7%) deaths after 20 years. Universal CGM use was associated with an additional ∼7,400 (4.1%) people living complications free and ∼11,500 (6.4%) fewer deaths compared with SMBG, while universal isCGM use was associated with ∼3,400 (1.9%) more people living complications free and ∼4,600 (2.6%) fewer deaths. Relative to SMBG, CGM and isCGM had ICERs of CAD 35,017/QALY and 17,488/QALY, respectively. CONCLUSIONS Universal use of CGM or isCGM in the Canadian T1D population is anticipated to reduce diabetes-related complications and mortality at an acceptable cost-effectiveness threshold.

Background: Sequential Multiple Assignment Randomized Trials (SMARTs) efficiently address practical treatment comparison questions and adapt dynamically based on response. They may be useful for development of approaches to co-manage weight and glycemia T1D, which is critical yet challenging. Methods: Our SMART pilot with three diet periods enrolled young adults with T1D (BMI 27-39.9 kg/m²) . Participants were re-randomized after ∼3 months on the hypocaloric Look AHEAD (Low Fat) or Low Carbohydrate (Low Carb) ; or Mediterranean (Med, not calorie restricted) diet if Results: The proportion re-randomized was 57.9% and did not vary by diet. Weight was lost overall but insufficient weight loss was the most common reason for re-randomization for Low Fat and Med. An HbA1c increase ≥0.5% was most common on Med. Low diet acceptability was the most common reason for re-randomization on Low Carb. Conclusions: We achieved safe weight loss among young adults with T1D but observed heterogeneity in reasons for re-randomization by diet, although differences were not statistically significant. A fully-powered efficacy trial may confirm our findings. Disclosure D.Igudesman: None. R.E.Pratley: Other Relationship; Bayer AG, Corcept Therapeutics, Dexcom, Inc., Hanmi Pharm. Co., Ltd., Merck & Co., Inc., Metavention, Novo Nordisk, Pfizer Inc., Poxel SA, Sanofi, Scohia Pharma Inc., Sun Pharmaceutical Industries Ltd. M.R.Kosorok: n/a. D.M.Maahs: Advisory Panel; Abbott Diabetes, Eli Lilly and Company, Medtronic, Novo Nordisk, Sanofi, Consultant; Aditx Therapeutics, Inc., Biospex. E.J.Mayer-davis: None. J.Crandell: n/a. T.Pokaprakarn: None. K.Corbin: None. D.P.Zaharieva: Research Support; Insulet Corporation, International Society for Pediatric and Adolescent Diabetes, Leona M. and Harry B. Helmsley Charitable Trust. A.Addala: None. J.Thomas: None. A.Casu: None. M.Riddell: Advisory Panel; Zealand Pharma A/S, Zucara Therapeutics, Consultant; Eli Lilly and Company, Jaeb Center for Health Research, Speaker's Bureau; Dexcom, Inc., Eli Lilly and Company, Novo Nordisk. Funding National Institutes of Health 1DP3DK113358

Glycemic responses differ by exercise classification (i.e. aerobic, interval, resistance) in individuals with T1D, but the impact of insulin delivery modality (multiple daily injections [MDI], pump, closed loop) on these differences is unclear. Data from the Type 1 Diabetes Exercise Initiative study allowed us to compare glycemic responses by insulin delivery method. Adults (N=497) with T1D ([mean ± SD] age= 37 ± 14 years; HbA1C= 6.6 ± 0.8%) were assigned to complete six at-home sessions of aerobic, interval, or resistance exercise over 4 weeks, using study-developed instructional videos approximately 30 minutes in duration. Mean [95% CI] change in glucose during the assigned exercise was -[95% CI -22, -16], -15 [-18, -12], and -9 [-12, -7] mg/dL for aerobic, interval, and resistance exercise, respectively (P In summary, regardless of insulin delivery modality, adults with T1D experienced the largest glucose drop for aerobic exercise followed by interval exercise and resistance exercise. Disclosure M.Riddell: Advisory Panel; Zealand Pharma A/S, Zucara Therapeutics, Consultant; Eli Lilly and Company, Jaeb Center for Health Research, Speaker's Bureau; Dexcom, Inc., Eli Lilly and Company, Novo Nordisk. P.Calhoun: None. J.R.Castle: Advisory Panel; Insulet Corporation, Novo Nordisk, Zealand Pharma A/S, Stock/Shareholder; Pacific Diabetes Technologies. R.Beck: Consultant; Diasome, Eli Lilly and Company, Insulet Corporation, Novo Nordisk, Research Support; Ascensia Diabetes Care, Beta Bionics, Inc., Bigfoot Biomedical, Inc., Dexcom, Inc., Eli Lilly and Company, Medtronic, Novo Nordisk, Roche Diabetes Care, Tandem Diabetes Care, Inc. M.R.Rickels: Advisory Panel; Sernova, Corp., Vertex Pharmaceuticals Incorporated, Zealand Pharma A/S, Consultant; L-Nutra Inc. S.R.Patton: None. C.K.Martin: Advisory Panel; Wondr Health, Board Member; EHE Health, Other Relationship; ABGIL, ABGIL, Academy of Nutrition and Dietetics. Z.Li: None. P.G.Jacobs: Other Relationship; Pacific Diabetes Technologies, Research Support; Dexcom, Inc. M.B.Gillingham: None. R.L.Gal: None. F.J.Doyle: Other Relationship; Dexcom, Inc., Insulet Corporation, Roche Diabetes Care, Stock/Shareholder; Mode AGC. M.A.Clements: Consultant; Glooko, Inc., Research Support; Abbott Diabetes, Dexcom, Inc.

Glucose dynamics during and after resistance exercise in people with T1D is not well understood. We recruited 25 people with T1D to perform 3 separate sessions of in-clinic resistance exercise under low (basal) , medium (1.5x basal) , or high (3.0x basal) insulin infusion levels. Blood glucose was clamped by intravenous dextrose infusion 3 hours prior to, and 4 hours after a 45-minute session of strength training. Glucose tracer was infused to match the rate of endogenous glucose production (EGP) . Glucose and tracer data were used to fit a two-compartment model and quantify the rate of glucose disposal (Rd) and EGP. For 58 sessions across 25 participants, blood glucose levels remained constant during and after resistance exercise. The mean change in area under the curve (AUC) for Rd was not higher during resistance exercise compared to baseline (+1.2 mM, p=0.69) , but increased during previously published aerobic exercise (+12.5 mM, p Disclosure G.Young: None. M.Riddell: Advisory Panel; Zealand Pharma A/S, Zucara Therapeutics, Consultant; Eli Lilly and Company, Jaeb Center for Health Research, Speaker's Bureau; Dexcom, Inc., Eli Lilly and Company, Novo Nordisk. J.El youssef: None. P.G.Jacobs: Other Relationship; Pacific Diabetes Technologies, Research Support; Dexcom, Inc. N.S.Tyler: None. T.P.Nguyen: None. J.R.Castle: Advisory Panel; Insulet Corporation, Novo Nordisk, Zealand Pharma A/S, Stock/Shareholder; Pacific Diabetes Technologies. L.M.Wilson: n/a. D.Branigan: None. V.Gabo: None. F.H.Guillot: Stock/Shareholder; Pacific Diabetes Technologies. Funding National Institutes of Health (5R01DK110175, 1F30DK128914)

Background: Pancreatic islet remodelling in type 1 diabetes increases somatostatin (SST) expression, which inhibits glucagon counterregulation to hypoglycemia. Here, we characterized islet morphology and hormone composition in a rodent model of insulin-deficient type 2 diabetes (T2D) . Methods: Hypoinsulinemic T2D was induced in 8-9-week-old, male, Sprague-Dawley rats (n=4) via 3 weeks of high-fat feeding and a low-dose injection of streptozotocin (STZ; 35 mg/kg) . After 2 weeks of basal insulin treatment, pancreas tissue was extracted from T2D and healthy control (n=5) rats for immunohistochemical staining of representative islets. Results: Fasted plasma C-peptide levels of hyperglycemic (24.8±3.3 mmol/l) T2D rats were reduced by ∼44% (624±64 vs. 1107±121 pmol/l; p Conclusions: Fractional area expression of glucagon and SST increased per islet in insulin-treated rats with advanced T2D. These findings may help account for the increase in SST signaling that underscores defective glucagon counterregulation to hypoglycemia in insulin-deficient diabetic states. Disclosure E. G. Hoffman: None. S. C. Atherley: None. N. Akbarian: None. N. Dsouza: None. R. Liggins: Employee; Zucara Therapeutics, Stock/Shareholder; Zucara Therapeutics. M. Riddell: Advisory Panel; Zealand Pharma A/S, Zucara Therapeutics, Consultant; Eli Lilly and Company, Jaeb Center for Health Research, Speaker’s Bureau; Dexcom, Inc., Eli Lilly and Company, Novo Nordisk. Funding GlycoNet

Different types of exercise (i.e., aerobic vs. interval vs. resistance) may have different immediate glycemic effects in adults with T1D, but the impact of exercise type on percent time in range 70-180 mg/dL (TIR) on physically active and inactive days is unknown. The Type 1 Diabetes Exercise Initiative (T1DEXI) study examined CGM data on active vs. sedentary days to assess the effect of exercise type on TIR. Adults (N=497) with T1D ([mean ± SD] age= 37 ± 14 years; HbA1C= 6.6 ± 0.8%) , completed six aerobic, interval, or resistance study-designed exercise videos at home over a 4-week period. TIR was higher and mean glucose concentration lower on days when the study-designed exercise video was completed, as compared with sedentary days (Table) . Time below range was low in general in this cohort, although slightly higher on exercise days. Results were remarkably similar for each exercise type, with marginally less increase in hypoglycemia with resistance exercise. In summary, adults with type 1 diabetes have clinically significant improvements in TIR on active days as compared to inactive days, regardless of the exercise type. Disclosure Z.Li: None. P.G.Jacobs: Other Relationship; Pacific Diabetes Technologies, Research Support; Dexcom, Inc. C.K.Martin: Advisory Panel; Wondr Health, Board Member; EHE Health, Other Relationship; ABGIL, ABGIL, Academy of Nutrition and Dietetics. S.R.Patton: None. P.Calhoun: None. M.Riddell: Advisory Panel; Zealand Pharma A/S, Zucara Therapeutics, Consultant; Eli Lilly and Company, Jaeb Center for Health Research, Speaker's Bureau; Dexcom, Inc., Eli Lilly and Company, Novo Nordisk. M.R.Rickels: Advisory Panel; Sernova, Corp., Vertex Pharmaceuticals Incorporated, Zealand Pharma A/S, Consultant; L-Nutra Inc. R.Beck: Consultant; Diasome, Eli Lilly and Company, Insulet Corporation, Novo Nordisk, Research Support; Ascensia Diabetes Care, Beta Bionics, Inc., Bigfoot Biomedical, Inc., Dexcom, Inc., Eli Lilly and Company, Medtronic, Novo Nordisk, Roche Diabetes Care, Tandem Diabetes Care, Inc. J.R.Castle: Advisory Panel; Insulet Corporation, Novo Nordisk, Zealand Pharma A/S, Stock/Shareholder; Pacific Diabetes Technologies. M.A.Clements: Consultant; Glooko, Inc., Research Support; Abbott Diabetes, Dexcom, Inc. F.J.Doyle: Other Relationship; Dexcom, Inc., Insulet Corporation, Roche Diabetes Care, Stock/Shareholder; Mode AGC. R.L.Gal: None. M.B.Gillingham: None.

Background: Challenges with exercise related glucose control in type 1 diabetes (T1D) may impact adherence to guidelines which recommend 60 minutes daily of moderate to vigorous intensity aerobic activity for youth ages 6-17 years. We examined the association between physical activity and glucose control in youth with T1D. Methods: Interstitial glucose data from flash continuous glucose monitors (CGM, Abbott Diabetes Care’s Freestyle Libre Pro Flash Glucose Monitor) and physical activity data (Metria IH1 activity patch) were objectively measured. Data from 52 youth 9-17 years old with a median diabetes duration of 6 years (IQR: 3 to 8) and mean (±SD) HbA1c of 9.1 ± 1.5% were analyzed. Partial Pearson’s correlation coefficients adjusting for age, gender, and baseline HbA1c were used to assess the association between daily physical activity and glucose control; the primary analysis used a linear regression model adjusted for age, gender, and baseline HbA1c. Results: Participants with higher average energy expenditure, as measured by metabolic equivalent minutes (MET-min), on their active days had higher average % time in range (TIR: 70-180 mg/dL) in the 24 hours after exercise than participants with lower average MET-min on active days (p180 mg/dL decreased with increased activity (p=0.002). Activity was significantly associated with lower mean glucose (p=0.02) without an increase in % time Conclusions: Among youth with T1D, objectively measured physical activity levels are associated with improved glucose control and decreased hyperglycemia. Use of biometric technology, such as activity trackers, may motivate youth to be more physically active, but integration with other diabetes-specific technologies, such as CGM and insulin pumps, may offer solutions for improved blood sugar management. Disclosure J. Gal: None. Z. Li: None. S. M. Willi: Advisory Panel; Self; Boehringer Ingelheim International GmbH, Medtronic, Other Relationship; Self; National Institute of Diabetes and Digestive and Kidney Diseases. 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 The Leona M. and Harry B. Helmsley Charitable Trust