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Background: Benefits of hybrid closed-loop (HCL) systems in a high-risk group with type 1 diabetes and impaired awareness of hypoglycemia (IAH) have not been well-explored., Methods: Adults with Edmonton HYPO scores ≥1047 were randomized to 26-weeks HCL (MiniMed™ 670G) vs standard therapy (multiple daily injections or insulin pump) without continuous glucose monitoring (CGM) (control). Primary outcome was percentage CGM time-in-range (TIR; 70-180 mg/dL) at 23 to 26 weeks post-randomization. Major secondary endpoints included magnitude of change in counter-regulatory hormones and autonomic symptom responses to hypoglycemia at 26-weeks post-randomization. A post hoc analysis evaluated glycemia risk index (GRI) comparing HCL with control groups at 26 weeks post-randomization., Results: Nine participants (median [interquartile range (IQR)] age 51 [41, 59] years; 44% male; enrolment HYPO score 1183 [1058, 1308]; Clarke score 6 [6, 6]; n = 5 [HCL]; n = 4 [control]) completed the study. Time-in-range was higher using HCL vs control (70% [68, 74%] vs 48% [44, 50%], P = .014). Time <70 mg/dL did not differ (HCL 3.8% [2.7, 3.9] vs control 6.5% [4.3, 8.6], P = .14) although hypoglycemia episode duration was shorter (30 vs 50 minutes, P < .001) with HCL. Glycemia risk index was lower with HCL vs control (38.1 [30.0, 39.2] vs 70.8 [58.5, 72.4], P = .014). Following 6 months of HCL use, greater dopamine (24.0 [12.3, 27.6] vs -18.5 [-36.5, -4.8], P = .014), and growth hormone (6.3 [4.6, 16.8] vs 0.5 [-0.8, 3.0], P = .050) responses to hypoglycemia were observed., Conclusions: Six months of HCL use in high-risk adults with severe IAH increased glucose TIR and improved GRI without increased hypoglycemia, and partially restored counter-regulatory responses., Clinical Trial Registration: ACTRN12617000520336., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: M.H.L and B.P. have received speaker honoraria from Medtronic. R.J.M. reports research grants from Novo Nordisk, Servier, Medtronic, and Grey Innovation; received honoraria for lectures from Eli Lilly and Company, Novo Nordisk, Sanofi, AstraZeneca, Merck Sharp & Dohme, Norvartis, and Boehringer Ingelheim; received travel support from Novo Nordisk, Sanofi, and Boehringer Ingelheim; is on the advisory boards for Novo Nordisk, Sanofi, Boehringer Ingelheim and Lilly Diabetes Alliance, and AstraZeneca; and has been a principal investigator for industry-sponsored clinical trials run by Novo Nordisk, Bayer, Janssen-Cilag, and AbbVie Inc. S.A.M. reports institutional support for research from Medtronic, speaker honoraria from Roche and Sanofi, and has served on an advisory board for Medtronic. J.S. has served on advisory boards for Medtronic, Roche Diabetes Care, and Sanofi Diabetes; her research group (Australian Centre for Behavioural Research in Diabetes) has received honoraria for this advisory board participation and has also received unrestricted educational grants and/or in-kind support from Abbott Diabetes Care, AstraZeneca, Medtronic, Roche Diabetes Care, and Sanofi Diabetes; has received sponsorship to attend educational meetings from Medtronic, Roche Diabetes Care, and Sanofi Diabetes; and has received consultancy income or speaker fees from Abbott Diabetes Care, AstraZeneca, Medtronic, Novo Nordisk, Roche Diabetes Care, and Sanofi Diabetes. A.J.J. has received research support from Medtronic, Sanofi, Abbott Laboratories, and Mylan; and has served on advisory boards for Medtronic, Sanofi, and Abbott Diabetes Care. D.N.O. has served on advisory boards for Abbott Laboratories, Medtronic, Merck Sharp & Dohme, Novo Nordisk, Roche, and Sanofi; received research support from Medtronic, Novo Nordisk, Roche, Eli Lilly and Company, and Sanofi; and received travel support from Novo Nordisk and Merck Sharp & Dohme. The remaining authors have nothing to disclose.

Objective: To determine feasibility and compare acceptance of an investigational Medtronic enhanced advanced hybrid closed-loop (e-AHCL) system in adults with type 1 diabetes with earlier iterations., Research Design and Methods: This nonrandomized three-stage (12 weeks each) exploratory study compared e-AHCL (Bluetooth-enabled MiniMed 780G insulin pump with automatic data upload [780G] incorporating an updated algorithm; calibration-free all-in-one disposable sensor; 7-day infusion set) preceded by a run-in (non-Bluetooth 780G [670G V4.0 insulin pump] requiring manual data upload; Guardian Sensor 3 [GS3] requiring calibration; 3-day infusion set), stage 1 (780G; GS3; 3-day infusion set), and stage 2 (780G; calibration-free Guardian Sensor 4; 3-day infusion set). Treatment satisfaction was assessed by Diabetes Technology Questionnaire (DTQ)-current (primary outcome) and other validated treatment satisfaction tools with glucose outcomes by continuous glucose monitoring metrics., Results: Twenty-one of 22 (11 women) participants (baseline HbA1c 6.7%/50 mmol/mol) completed the study. DTQ-current scores favored e-AHCL (123.1 [17.8]) versus run-in (101.6 [24.2]) and versus stage 1 (110.6 [20.8]) (both P < 0.001) but did not differ from stage 2 (119.4 [16.0]; P = 0.271). Diabetes Medication System Rating Questionnaire short-form scores for "Convenience and Efficacy" favored e-AHCL over run-in and all stages. Percent time in range 70-180 mg/dL was greater with e-AHCL versus run-in and stage 2 (+2.9% and +3.6%, respectively; both P < 0.001). Percent times of <70 mg/dL for e-AHCL were significantly lower than run-in, stage 1, and stage 2 (-0.9%, -0.6%, and -0.5%, respectively; all P < 0.01)., Conclusions: e-AHCL was feasible. User satisfaction increased compared with earlier Medtronic HCL iterations without compromising glucose control., (© 2024 by the American Diabetes Association.)

Objectives: Regular exercise is recommended for people with type 1 diabetes (PWD) to improve their health, but many do not meet recommended exercise targets. Educational resources supporting PWD to exercise exist, but their value is unclear. To determine the need for improved exercise resources in Australia, we surveyed adult PWD and health providers (HPs) about their confidence in managing type 1 diabetes (T1D) around exercise, barriers to exercise, and the adequacy of current resources., Methods: Australian adult PWD and HPs completed surveys to rate the importance of exercise in T1D management, confidence in managing T1D around exercise, barriers to giving and receiving education, resources used, and what form new resources should take., Results: Responses were received from 128 PWD and 122 HPs. Both groups considered exercise to be important for diabetes management. PWD cited time constraints (57%) and concern about dysglycemia (43%) as barriers to exercise, and many lacked confidence in managing T1D around exercise. HPs were more confident, but experienced barriers to providing advice, and PWD did not tend to rely on this advice. Instead, 72% of PWD found continuous glucose monitoring most helpful. Both groups desired better resources to support exercise in T1D, with PWD preferring to obtain information through a structured education program and HPs through eLearning., Conclusions: Australian HPs and PWD appreciate the importance of exercise in T1D management and express a clear desire for improved educational resources. Our findings provide a basis for developing a comprehensive package of resources for both adult PWD and HPs, to support exercise in PWD., (Crown Copyright © 2023. Published by Elsevier Inc. All rights reserved.)

Exercise has many physical and psychological benefits and is recommended for people with type 1 diabetes; however, there are many barriers to exercise, including glycemic instability and fear of hypoglycemia. Closed-loop (CL) systems have shown benefit in the overall glycemic management of type 1 diabetes, including improving HbA1c levels and reducing the incidence of nocturnal hypoglycemia; however, these systems are challenged by the rapidly changing insulin needs with exercise. This commentary focuses on the principles, strengths, and challenges of CL in the management of exercise, and discusses potential approaches, including the use of additional physiological signals, to address their shortcomings in the pursuit of fully automated CL systems.

Regular exercise is essential to overall cardiovascular health and well-being in people with type 1 diabetes, but exercise can also lead to increased glycemic disturbances. Automated insulin delivery (AID) technology has been shown to modestly improve glycemic time in range (TIR) in adults with type 1 diabetes and significantly improve TIR in youth with type 1 diabetes. Available AID systems still require some user-initiated changes to the settings and, in some cases, significant pre-planning for exercise. Many exercise recommendations for type 1 diabetes were developed initially for people using multiple daily insulin injections or insulin pump therapy. This article highlights recommendations and practical strategies for using AID around exercise in type 1 diabetes., Competing Interests: D.P.Z. has received honoraria for speaking engagements from Ascensia Diabetes, Insulet Canada, and Medtronic Diabetes; is on an advisory board for Dexcom; and has received an ISPAD-JDRF Research Fellowship and research support from Insulet and the Leona M. and Harry B. Helmsley Charitable Trust. B.P. has received speaker honoraria fees from Medtronic. R.A.L. has received personal fees from Abbott Diabetes Care, Bioling, Capillary Biomedical, Deep Valley Laboratories, Gluroo, Provention Bio, and Tidepool. His work is supported by a Diabetes, Endocrinology and Metabolism Career Development grant (1K23DK122017) from the National Institute of Diabetes and Digestive and Kidney Diseases. He co-leads the Bioengineering and Behavioral Sciences Working Group of the Stanford Diabetes Research Center (P30 DK116074), and he has received additional research support from Insulet, JDRF, and Medtronic. B.A.B. serves on the advisory boards of Arecor, Medtronic, and Novo Nordisk; has received speaking fees from Eli Lilly; and has received research grant support from Insulet, Medtronic, and Tandem. D.N.O. has served on advisory boards for Abbott Laboratories, Medtronic, Merck Sharp & Dohme, Novo Nordisk, Roche, and Sanofi. He has received research support from Eli Lilly, Medtronic, Novo Nordisk, Roche, and Sanofi and travel support from Merck Sharp & Dohme and Novo Nordisk. No other potential conflicts of interest relevant to this article were reported., (© 2023 by the American Diabetes Association.)

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.

Devices have facilitated improvement in glycemia in individuals with type 1 diabetes mellitus (T1DM), but self-management remains key. It is unclear whether people review their device data before clinic appointment. We assessed this by a survey. T1DM adults using glucose sensors and/or insulin pumps attending an Australian public hospital (diabetes clinics >4 months) were prospectively surveyed. The percentage who uploaded and reviewed their data was determined and their interest in education facilitating understanding of their device data was assessed. Of 138 adults (100% participation rate), 79% uploaded and 32% reviewed their device data before their clinic appointments. Individuals using pumps with sensors were most likely to review their data. Median HbA 1c levels were lower in those who did versus did not review their device data (50.8 vs. 61.8 mmol/mol, P  = 0.0001). Most (89%) were interested in education. Although diabetes technology has improved glycemia in T1DM, the benefits may be maximized through device-specific education programs enhancing self-management.

There is limited evidence supporting the recommendation that drivers with insulin-treated diabetes need to start journeys with glucose >90 mg/dL. Glucose levels of drivers with type 1 diabetes were monitored for 3 weeks using masked continuous glucose monitoring (CGM). Eighteen drivers (median [IQR] age 40 [35, 51] years; 11 men) undertook 475 trips (duration 15 [13, 21] min). Hypoglycemia did not occur in any trip starting with glucose >90 mg/dL (92%; n  = 436). Thirteen drivers recorded at least one trip (total n  = 39) starting with glucose <90 mg/dL. Among these, driving glucose was <70 mg/dL in five drivers (38%) during 10 trips (26%). Among five drivers (28%), a ≥ 36 mg/dL drop was observed within 20 min of starting their journey. Journey duration was positively associated with maximum glucose change. These findings support current guidelines to start driving with glucose >90 mg/dL, and to be aware that glucose levels may change significantly within 20 min. A CGM-based, in-vehicle display could provide glucose information and alerts that are compatible with safe driving. Clinical Trial Registration number: ACTRN12617000520336.

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% VO 2 max) and HIE (6 × 2 min ∼80% VO 2 max; 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.

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., (© 2021 by the American Diabetes Association.)

Aims: To compare meal-time glycaemia in adults with type 1 diabetes mellitus (T1D) managed with multiple daily injections (MDI) vs. insulin pump therapy (IPT), using self-monitoring blood glucose (SMBG), following diabetes education., Methods: Adults with T1D received carbohydrate-counting education and a bolus calculator: MDI (Roche Aviva Expert) and IPT (pump bolus calculator). All then wore 3-weeks of masked-CGM (Enlite, Medtronic). Meal-times were assessed by two approaches: 1) Set time-blocks (breakfast 06:00-10:00hrs; lunch 11:00-15:00hrs; dinner 17:00-21:00hrs) and 2) Bolus-calculator carbohydrate entries signalling meal commencement. Post-meal masked-CGM time-in-range (TIR) 3.9-10.0 mmol/L was the primary outcome., Results: MDI(n = 61) and IPT (n = 59) participants were equivalent in age, sex, diabetes duration and HbA1c. Median (IQR) education time provided did not differ (MDI: 1.1 h (0.75, 1.5) vs. IPT: 1.1 h (1.0, 2.0); p = 0.86). Overall, daytime (06:00-24:00hrs), lunch and dinner TIR did not differ for MDI vs. IPT participants but was greater for breakfast with IPT in both analyses with a mean difference of 12.8%, (95 CI 4.8, 20.9); p = 0.002 (time-block analysis)., Conclusion: After diabetes education, MDI and IPT use were associated with similar day-time glycemia, though IPT users had significantly greater TIR during the breakfast period. With education, meal-time glucose levels are comparable with use of MDI vs. pumps., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Conflicts of Interest JCL reports no potential conflicts of interest relevant to this article. SV reports no potential conflicts of interest relevant to this article. SAM reports speaker honoraria from Roche and that her institution has received research support from Medtronic. BP reports speaker honoraria fees from Medtronic. MBA reports no potential conflicts of interest relevant to this article. MIdB reports no potential conflicts of interest relevant to this article. LAB reports grant funding from AstraZeneca. MGB reports no potential conflicts of interest relevant to this article. NDC reports personal fees from Medtronic and Abbott, grant funds from Ypsomed. PGC reports no potential conflicts of interest relevant to this article. EAD reports no potential conflicts of interest relevant to this article. DJHW reports no potential conflicts of interest relevant to this article. JK reports speaker fees from Novo Nordisk and AstraZeneca, advisory board fees from Abbott Diabetes. RJM reports research grants from Novo Nordisk, Servier, Medtronic, The Rebecca Cooper Medical Research Foundation, St Vincent's Research Foundation, JDRF, Grey Innovations, The Diabetes Australia Research Trust/Program, and The National Health and Medical Research Council of Australia; honoraria for lectures from Eli Lilly, Novo Nordisk, Sanofi Aventis, Astra Zeneca, Merck Sharp & Dohme, Norvartis, and Boehringer Ingelheim; travel support from Novo Nordisk, Sanofi, and Boehringer Ingelheim; is on the advisory boards for Novo Nordisk, Sanofi Aventis, Boehringer Ingelheim-Eli Lilly Diabetes Alliance, and Astra Zeneca, and has been a principal investigator for industry sponsored clinical trials run by Novo Nordisk, Bayer, Johnson-Cilag, and Abbive. ACK reports no potential conflicts of interest relevant to this article. KK reports no potential conflicts of interest relevant to this article. RJM reports no potential conflicts of interest relevant to this article. WMC reports no potential conflicts of interest relevant to this article. CMS reports no potential conflicts of interest relevant to this article. KR reports no potential conflicts of interest relevant to this article. VJS reports no potential conflicts of interest relevant to this article. ST reports non-financial support from Abbott Diabetes. GMW reports no potential conflicts of interest relevant to this article. AJJ has received research support from Medtronic, the National Health and Medical Research Council, JDRF Australia and International, Sanofi-Aventis, Abbott, and Mylan and has served on advisory boards for Medtronic, Sanofi, and Abbott (Diabetes). TWJ reports no potential conflicts of interest relevant to this article. DNO has served on advisory boards for Abbott, Medtronic, MSD, Novo, Roche, and Sanofi; received research support from Medtronic, Novo, Roche, Lilly, and Sanofi; and travel support from Novo and MSD., (Copyright © 2021 Elsevier B.V. All rights reserved.)

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 HbA 1c 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%., (© 2021 by the American Diabetes Association.)

Background: This prerandomization analysis from the Australian HCL-Adult trial (registration number: ACTRN12617000520336) compared masked continuous glucose monitoring (CGM) metrics among adults using insulin pumps versus multiple daily injections (MDIs), who were all self-monitoring blood glucose (SMBG). Methods: Adults with type 1 diabetes, using an insulin pump or MDIs without real-time CGM (and entering a trial of closed-loop technology), were eligible. MDI users were given an insulin dosage calculator. All participants received diabetes and carbohydrate-counting education, then wore masked CGM sensors for 3 weeks. Ethics Approval: HREC-D 088/16 Results: Adults using MDIs ( n  = 61) versus pump ( n  = 59) did not differ by age, sex, diabetes duration, insulin total daily dose, or HbA 1c at baseline. After education, median (interquartile range) CGM time in range (TIR) 70-180 mg/dL (3.9-10.0 mmol/L) was 54% (47, 62) for those using MDIs and 56% (48, 66) for those using pump ( P  = 0.40). All CGM metrics were equivalent for 24 h/day for MDI and pump users. Overnight, those using MDIs (vs. pump) spent more time with glucose <54 mg/dL (<3.0 mmol/L): 1.4% (0.1, 5.1) versus 0.5% (0.0, 2.0), respectively ( P  = 0.012). They also had more CGM hypoglycemia episodes (121 vs. 54, respectively; incidence rate ratio [95% confidence interval] 2.48 [1.51, 4.06]; P  < 0.001). Conclusions: Adults with type 1 diabetes using pumps versus MDIs in conjunction with SMBG experienced less nocturnal hypoglycemia, measured by masked CGM, after equivalent diabetes and dietary education in conjunction with insulin dosage calculator provision to all. However, both groups had equivalent TIR. This observation may reflect advantages afforded by flexibility in basal insulin delivery provided by pumps.

Objective: To investigate glycemic and psychosocial outcomes with hybrid closed-loop (HCL) versus user-determined insulin dosing with multiple daily injections (MDI) or insulin pump (i.e., standard therapy for most adults with type 1 diabetes)., Research Design and Methods: Adults with type 1 diabetes using MDI or insulin pump without continuous glucose monitoring (CGM) were randomized to 26 weeks of HCL (Medtronic 670G) or continuation of current therapy. The primary outcome was masked CGM time in range (TIR; 70-180 mg/dL) during the final 3 weeks., Results: Participants were randomized to HCL ( n = 61) or control ( n = 59). Baseline mean (SD) age was 44.2 (11.7) years, HbA 1c was 7.4% (0.9%) (57 [10] mmol/mol), 53% were women, and 51% used MDI. HCL TIR increased from (baseline) 55% (13%) to (26 weeks) 70% (10%) with the control group unchanged: (baseline) 55% (12%) and (26 weeks) 55% (13%) (difference 15% [95% CI 11, 19]; P < 0.0001). For HCL, HbA 1c was lower (median [95% CI] difference -0.4% [-0.6, -0.2]; -4 mmol/mol [-7, -2]; P < 0.0001) and diabetes-specific positive well-being was higher (difference 1.2 [95% CI 0.4, 1.9]; P < 0.0048) without a deterioration in diabetes distress, perceived sleep quality, or cognition. Seventeen (9 device-related) versus 13 serious adverse events occurred in the HCL and control groups, respectively., Conclusions: In adults with type 1 diabetes, 26 weeks of HCL improved TIR, HbA 1c , and their sense of satisfaction from managing their diabetes compared with those continuing with user-determined insulin dosing and self-monitoring of blood glucose. For most people living with type 1 diabetes globally, this trial demonstrates that HCL is feasible, acceptable, and advantageous., (© 2020 by the American Diabetes Association.)

Guidelines for safe exercise strategies exist for both pediatric and adult patients living with type 1 diabetes. The management of type 1 diabetes during exercise is complex, but making insulin dosing adjustments in advance of activity can yield positive outcomes and reduce the likelihood of hypoglycemia. Closed loop (also known as automated insulin delivery) systems are able to partially automate insulin delivery and can assist in exercise and overall management of type 1 diabetes. Current exercise guidelines, however, focus primarily on management strategies for patients using multiple daily injections or open loop insulin pump therapy. Closed loop systems require strategic approaches to type 1 diabetes management, including appropriate timing and duration of exercise targets and carbohydrates around exercise that have yet to be standardized. This review aims to showcase how closed loop technology has evolved over the last decade and summarizes a number of closed loop and exercise studies both in free-living conditions and clinical trials. This review also highlights strategies and approaches for exercise and type 1 diabetes management using closed loop systems. Some differences in closed loop strategies for exercise include the importance of pump suspension if disconnecting during exercise, fewer grams of uncovered carbohydrates before exercise and these should be taken close to exercise onset to avoid a rise in automated insulin delivery. A primary goal for future closed loop systems is to detect exercise without user input, so that patients are not required to preset exercise targets well in advance of activity, as are the current recommendations., (Copyright © 2020 Canadian Diabetes Association. Published by Elsevier Inc. All rights reserved.)

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.

Objective: To evaluate exercise-related glucose and counterregulatory responses (CRR) in adults with type 1 diabetes with impaired awareness of hypoglycemia (IAH) using hybrid closed-loop (HCL) insulin delivery to maintain glucose homeostasis., Research Design and Methods: Twelve participants undertook 45-min high-intensity intermittent exercise (HIIE) and moderate-intensity exercise (MIE) in random order. The primary outcome was continuous glucose monitoring (CGM) time in range (70-180 mg/dL) for 24-h post-exercise commencement., Results: CGM time in range was similar for HIIE and MIE (median 79.5% [interquartile range 73.2, 87.6] vs. 76.1% [70.3, 83.9], P = 0.37), and time with levels <54mg/dL post-exercise commencement was 0%. HIIE induced greater increases in cortisol ( P = 0.002), noradrenaline ( P = 0.005), and lactate ( P = 0.002), with no differences in adrenaline, dopamine, growth hormone, or glucagon responses., Conclusions: IAH adults using HCL undertaking HIIE and MIE exhibit heterogeneity in CRR. Novel findings were a preserved cortisol response and variable catecholamine responses to HIIE., (© 2019 by the American Diabetes Association.)

Closed loop (CL) systems deliver insulin with a rapid onset and offset in action. Although favorable overall, the absence of a long-acting insulin increases the risk of diabetic ketoacidosis (DKA) which can occur with insulin delivery failure, acute illness, low carbohydrate diets, sodium glucose-linked transporter inhibitors, and high intensity exercise. A CL system relying entirely on interstitial glucose measurements may not provide an alert for DKA and many people with type 1 diabetes (T1D) do not carry a blood ketone meter and test-strips. Ketone sensing is theoretically feasible. A multianalyte platform incorporating a ketone sensor could provide an additional CL input without an increase in burden for the person with T1D, warning of impending DKA to allow remedial action to be taken. We outline the clinical case for inclusion of continuous ketone sensing as part of future CL systems.

Background: Experience from first-generation closed-loop (CL) systems informs refinements to enhance glucose control and user acceptance. A next-generation prototype enhanced-hybrid CL (E-HCL) system incorporates iterative changes to the Medtronic MiniMed 670G CL system, including automated correction boluses, lower target glucose level, and user enhancements. The aim was to explore safety, system performance, and glucose control using E-HCL in adults with type 1 diabetes. Methods: Twelve adults underwent this first in-human feasibility study. After a 1-week run-in using open-loop (OL), E-HCL was activated at the start of a supervised 1-week hotel phase, followed by 3 weeks free living at home. Supervised challenges included two meal interventions (unannounced and late meal bolus) and a sensor calibration intervention. Primary outcome was sensor glucose time-in-range (TIR); OL run-in and E-HCL at home were compared by Wilcoxon signed-rank test. Results: Twelve adults (seven men; median [interquartile range] age 48 [39, 57] years; HbA 1c 6.8 [6.2, 7.2]%, 51 [44, 55] mmol/mol; diabetes duration 31 [13, 41] years) completed the protocol. E-HCL resulted in greater TIR (85.3 [79.4, 88.4]% vs. 75.0 [66.6, 83.7]%, P  = 0.003) and lower mean sensor glucose (123.0 [119.3, 129.6] mg/dL vs. 143.5 [135.8, 154.5] mg/dL, P  = 0.002) than OL. Time spent <70 mg/dL increased using E-HCL (4.4 [3.3, 6.1]% vs. 3.0 [1.8, 3.8]%, P  = 0.02) with no difference in time <54 mg/dL ( P  = 0.64). Time in CL was 99.98 [99.0, 100.0]%. All participants were satisfied using E-HCL. Conclusions: In adults with well-controlled HbA 1c levels, a prototype E-HCL resulted in high TIR, few CL exits, and positive user experiences at the expense of increased hypoglycemia (<70 mg/dL). E-HCL represents a positive step in the journey toward optimizing glucose control in people living with type 1 diabetes.

Hybrid closed loop (HCL) insulin delivery with the Medtronic Minimed 670G system is effective and safe in people with type 1 diabetes (T1D). This study compared glucose control, closed loop (CL) exits, and alarm frequency with the standard HCL (s-HCL) versus enhanced HCL (e-HCL) Medtronic system. Pump-experienced T1D adults (n = 11; 9 female; mean [SD] age: 51 years [15 years]; HbA1c 7.5% [1.0%] or 58 mmol/mol [7.7 mmol/mol]) were assigned, in random order, s-HCL or e-HCL for 1 week each in a supervised live-in setting. e-HCL incorporated enhanced bolus reminders and iterative changes, broadening glucose and insulin delivery parameters permitting persistence in CL. For both s-HCL and e-HCL, insulin delivery was by a Medtronic pump with identical interventions (missed bolus, exercise, high-glycemic index, and high-fat meals), insulin action times, and insulin-carbohydrate ratios implemented. The primary outcome was continuous glucose monitoring time in target range. Analysis was by paired t-test for normally distributed data and Wilcoxon-signed rank test otherwise. e-HCL resulted in significantly fewer CL alerts and exits. Time in target and mean glucose favored e-HCL but did not reach statistical significance. No episodes of severe hypoglycemia or ketoacidosis occurred. Relative to s-HCL, e-HCL use significantly decreases CL exits and alerts, and tended to improve glycemia without compromising safety, despite multiple food and exercise challenges during the study. Longer term studies at home are merited.

Competing Interests: Conflict of interest: Barbora Paldus has received research support and honoraria from Medtronic, Novo-Nordisk and Sanofi. Melissa Lee has received research support and honoraria from Medtronic. David O’Neal has received research support and is on advisory boards for Medtronic, Novo-Nordisk and Sanofi. He has received honoraria from Medtronic, AMSL, Novo-Nordisk and Sanofi.