Insulin pump basal adjustment for exercise in type 1 diabetes: a randomised crossover study.

AIMS/HYPOTHESIS: The aim of this study was to investigate the effects of exercise, vs rest, on circulating insulin and glucose, following pre-exercise insulin pump basal rate reduction. METHODS: This was an open-label, two-stage randomised crossover study of 14 adults (seven women, seven men) with type 1 diabetes established on insulin pump therapy. In each stage, participants fasted and insulin delivery was halved following a single insulin basal rate overnight. Exercise (30 min moderate-intensity stationary bicycle exercise, starting 60 min post-basal reduction) and rest stages were undertaken in random order at a university hospital. Randomisation was computer-generated, and allocation concealed via sequentially numbered sealed opaque envelopes. Venous blood was collected at 15 min intervals from 60 min pre- until 210 min post-basal rate reduction. Changes in plasma free insulin (the primary outcome), and changes in plasma glucose, with exercise were compared with changes when resting. Outcomes were assessed blinded to group assignment. RESULTS: Following basal rate reduction when rested, mean (± SE) free insulin decreased by 4.9 ± 2.9%, 16.2 ± 2.6% and 18.6 ± 3.2% at 1, 2 and 3 h, respectively (p < 0.05 after 75 min). With exercise, relative to rest, mean free insulin increased by 6 ± 2 pmol/l after 15 min and 5 ± 2 pmol/l after 30 min (p < 0.001), then declined post-exercise (p < 0.001). Three participants (mean baseline glucose 5.0 ± 0.1 mmol/l) required glucose supplementation to prevent or treat exercise-related hypoglycaemia. In the other 11 participants (mean baseline glucose 8.4 ± 0.5 mmol/l), glucose increased by 0.8 ± 0.3 mmol/l with exercise (p = 0.028). CONCLUSIONS/INTERPRETATION: Halving the basal insulin rate 1 h prior to exercise did not significantly reduce circulating free insulin by exercise commencement. Exercise itself transiently increased insulin levels. In participants with low-normal glucose pre-exercise, hypoglycaemia was not prevented by insulin basal rate reduction alone. Greater insulin basal rate reduction and supplemental carbohydrate may be required to prevent exercise-induced hypoglycaemia. TRIAL REGISTRATION: ANZCTR.org.au ACTRN12613000581763 FUNDING: Australian Diabetes Society, Hugh DT Williamson Foundation, Lynne Quayle Charitable Trust Fund.

Glucose Control Using a Standard Versus an Enhanced Hybrid Closed Loop System: A Randomized Crossover Study.

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.

Effect of 6 months of hybrid closed-loop insulin delivery in adults with type 1 diabetes: a randomised controlled trial protocol.

INTRODUCTION: Manual determination of insulin dosing largely fails to optimise glucose control in type 1 diabetes. Automated insulin delivery via closed-loop systems has improved glucose control in short-term studies. The objective of the present study is to determine the effectiveness of 6 months' closed-loop compared with manually determined insulin dosing on time-in-target glucose range in adults with type 1 diabetes. METHODS AND ANALYSIS: This open-label, seven-centre, randomised controlled parallel group clinical trial will compare home-based hybrid closed-loop versus standard diabetes therapy in Australia. Adults aged ≥25 years with type 1 diabetes using intensive insulin therapy (via multiple daily injections or insulin pump, total enrolment target n=120) will undertake a run-in period including diabetes and carbohydrate-counting education, clinical optimisation and baseline data collection. Participants will then be randomised 1:1 either to 26 weeks of MiniMed 670G hybrid closed-loop system therapy (Medtronic, Northridge, CA, USA) or continuation of their current diabetes therapy. The hybrid closed-loop system delivers insulin automatically to address basal requirements and correct to target glucose level, while bolus doses for meals require user initiation and carbohydrate estimation. Analysis will be intention to treat, with the primary outcome time in continuous glucose monitoring (CGM) target range (3.9-10.0 mmol/L) during the final 3 weeks of intervention. Secondary outcomes include: other CGM parameters, HbA1c, severe hypoglycaemia, psychosocial well-being, sleep, cognition, electrocardiography, costs, quality of life, biomarkers of vascular health and hybrid closed-loop system performance. Semistructured interviews will assess the expectations and experiences of a subgroup of hybrid closed-loop users. ETHICS AND DISSEMINATION: The study has Human Research Ethics Committee approval. The study will be conducted in accordance with the principles of the Declaration of Helsinki and Good Clinical Practice. Results will be disseminated at scientific conferences and via peer-reviewed publications. TRIAL REGISTRATION NUMBER: ACTRN12617000520336; Pre-results.

Closed-Loop Insulin Delivery for Adults with Type 1 Diabetes Undertaking High-Intensity Interval Exercise Versus Moderate-Intensity Exercise: A Randomized, Crossover Study.

BACKGROUND: We aimed to compare closed-loop glucose control for people with type 1 diabetes undertaking high-intensity interval exercise (HIIE) versus moderate-intensity exercise (MIE). METHODS: Adults with type 1 diabetes established on insulin pumps undertook HIIE and MIE stages in random order during automated insulin delivery via a closed-loop system (Medtronic). Frequent venous sampling for glucose, lactate, ketones, insulin, catecholamines, cortisol, growth hormone, and glucagon levels was performed. The primary outcome was plasma glucose <4.0 mmol/L for ≥15 min, from exercise commencement to 120 min postexercise. Secondary outcomes included continuous glucose monitoring and biochemical parameters. RESULTS: Twelve adults (age mean ± standard deviation 40 ± 13 years) were recruited; all completed the study. Plasma glucose of one participant fell to 3.4 mmol/L following MIE completion; no glucose levels were <4.0 mmol/L for HIIE (primary outcome). There were no glucose excursions >15.0 mmol/L for either stage. Mean (±standard error) plasma glucose did not differ between stages pre-exercise; was higher during exercise in HIIE than MIE (11.3 ± 0.5 mmol/L vs. 9.7 ± 0.6 mmol/L, respectively; P < 0.001); and remained higher until 60 min postexercise. There were no differences in circulating free insulin before, during, or postexercise. During HIIE compared with MIE, there were greater increases in lactate (P < 0.001), catecholamines (all P < 0.05), and cortisol (P < 0.001). Ketones increased more with HIIE than MIE postexercise (P = 0.031). CONCLUSIONS: Preliminary findings suggest that closed-loop glucose control is safe for people undertaking HIIE and MIE. However, the management of the postexercise rise in ketones secondary to counter-regulatory hormone-induced insulin resistance observed with HIIE may represent a challenge for closed-loop systems.

"It Is Definitely a Game Changer": A Qualitative Study of Experiences with In-home Overnight Closed-Loop Technology Among Adults with Type 1 Diabetes.

BACKGROUND: This qualitative study explored trial participants' experiences of four nights of in-home closed loop. METHODS: Sixteen adults with type 1 diabetes, who completed a randomized crossover trial, were interviewed after four consecutive nights of closed-loop. Interviews were audio recorded, transcribed, and analyzed with a coding framework developed to identify the main themes. RESULTS: Participants had a mean age of 42 ± 10 years, nine were women; mean diabetes duration was 27 ± 7 years, and all were using insulin pumps. Overall, first impressions were positive. Participants found closed-loop easy to use and understand. Most experienced more stable overnight glucose levels, although for some these were similar to usual care or higher than they expected. Compared with their usual treatment, they noticed the proactive nature of the closed-loop, being able to predict trends and deliver micro amounts of insulin. Most reported technical glitches or inconveniences during one or more nights, such as transmission problems, problematic connectivity between devices, ongoing alarms despite addressing low glucose levels, and sensor inaccuracy. Remote monitoring by the trial team and their own hypoglycemic awareness contributed to feelings of trust and safety. Although rare, safety concerns were raised, related to feeling unsure whether the system would respond in time to falling glucose levels. CONCLUSIONS: This study provides relevant insights for implementation of closed-loop in the real world. For people with diabetes who are less familiar with technology, remote monitoring for the first few days may provide reassurance, strengthen their trust/skills, and make closed-loop an acceptable option for more people with type 1 diabetes.

Redundancy in Glucose Sensing: Enhanced Accuracy and Reliability of an Electrochemical Redundant Sensor for Continuous Glucose Monitoring.

BACKGROUND: Current electrochemical glucose sensors use a single electrode. Multiple electrodes (redundancy) may enhance sensor performance. We evaluated an electrochemical redundant sensor (ERS) incorporating two working electrodes (WE1 and WE2) onto a single subcutaneous insertion platform with a processing algorithm providing a single real-time continuous glucose measure. METHODS: Twenty-three adults with type 1 diabetes each wore two ERSs concurrently for 168 hours. Post-insertion a frequent sampling test (FST) was performed with ERS benchmarked against a glucose meter (Bayer Contour Link). Day 4 and 7 FSTs were performed with a standard meal and venous blood collected for reference glucose measurements (YSI and meter). Between visits, ERS was worn with capillary blood glucose testing ≥8 times/day. Sensor glucose data were processed prospectively. RESULTS: Mean absolute relative deviation (MARD) for ERS day 1-7 (3,297 paired points with glucose meter) was (mean [SD]) 10.1 [11.5]% versus 11.4 [11.9]% for WE1 and 12.0 [11.9]% for WE2; P < .0001. ERS Clarke A and A+B were 90.2% and 99.8%, respectively. ERS day 4 plus day 7 MARD (1,237 pairs with YSI) was 9.4 [9.5]% versus 9.6 [9.7]% for WE1 and 9.9 [9.7]% for WE2; P = ns. ERS day 1-7 precision absolute relative deviation (PARD) was 9.9 [3.6]% versus 11.5 [6.2]% for WE1 and 10.1 [4.4]% for WE2; P = ns. ERS sensor display time was 97.8 [6.0]% versus 91.0 [22.3]% for WE1 and 94.1 [14.3]% for WE2; P < .05. CONCLUSIONS: Electrochemical redundancy enhances glucose sensor accuracy and display time compared with each individual sensing element alone. ERS performance compares favorably with 'best-in-class' of non-redundant sensors.

Feasibility of an Orthogonal Redundant Sensor incorporating Optical plus Redundant Electrochemical Glucose Sensing.

BACKGROUND: Orthogonal redundancy for glucose sensing (multiple sensing elements utilizing distinct methodologies) may enhance performance compared to nonredundant sensors, and to sensors with multiple elements utilizing the same technology (simple redundancy). We compared the performance of a prototype orthogonal redundant sensor (ORS) combining optical fluorescence and redundant electrochemical sensing via a single insertion platform to an electrochemical simple redundant sensor (SRS). METHODS: Twenty-one adults with type 1 diabetes wore an ORS and an SRS concurrently for 7 days. Following sensor insertion, and on Day 4 with a standardized meal, frequent venous samples were collected for reference glucose measurement (laboratory [YSI] and meter) over 3 and 4 hours, respectively. Between study visits reference capillary blood glucose testing was undertaken. Sensor data were processed prospectively. RESULTS: ORS mean absolute relative difference (MARD) was (mean ± SD) 10.5 ± 13.2% versus SRS 11.0 ± 10.4% (P = .34). ORS values in Clarke error grid zones A and A+B were 88.1% and 97.6%, respectively, versus SRS 86.4% and 97.8%, respectively (P = .23 and P = .84). ORS Day 1 MARD (10.7 ± 10.7%) was superior to SRS (16.5 ± 13.4%; P < .0001), and comparable to ORS MARD for the week. ORS sensor survival (time-averaged mean) was 92.1% versus SRS 74.4% (P = .10). ORS display time (96.0 ± 5.8%) was equivalent to SRS (95.6 ± 8.9%; P = .87). CONCLUSIONS: Combining simple and orthogonal sensor redundancy via a single insertion is feasible, with accuracy comparing favorably to current generation nonredundant sensors. Addition of an optical component potentially improves sensor reliability compared to electrochemical sensing alone. Further improvement in optical sensing performance is required prior to clinical application.

Glycemia, Treatment Satisfaction, Cognition, and Sleep Quality in Adults and Adolescents with Type 1 Diabetes When Using a Closed-Loop System Overnight Versus Sensor-Augmented Pump with Low-Glucose Suspend Function: A Randomized Crossover Study.

BACKGROUND: We compared glycemia, treatment satisfaction, sleep quality, and cognition using a nighttime Android-based hybrid closed-loop system (Android-HCLS) with sensor-augmented pump with low-glucose suspend function (SAP-LGS) in people with type 1 diabetes. MATERIALS AND METHODS: An open-label, prospective, randomized crossover study of 16 adults (mean [SD] age 42.1 [9.6] years) and 12 adolescents (15.2 [1.6] years) was conducted. All participants completed four consecutive nights at home with Android-HCLS (proportional integral derivative with insulin feedback algorithm; Medtronic) and SAP-LGS. PRIMARY OUTCOME: percent continuous glucose monitoring (CGM) time (00:00-08:00 h) within target range (72-144 mg/dL). Secondary endpoints: percent CGM time above target (>144 mg/dL); below target (<72 mg/dL); glycemic variability (SD); symptomatic hypoglycemia; adult treatment satisfaction; sleep quality; and cognitive function. RESULTS: The primary outcome for all participants was not statistically different between Android-HCLS and SAP-LGS (mean [SD] 59.4 [17.9]% vs. 53.1 [18]%; p = 0.14). Adults had greater percent time within target range (57.7 [18.6]% vs. 44.5 [14.5]%; p < 0.006); less time above target (42.0 [18.7]% vs. 52.6 [16.5]%; p = 0.034); lower glycemic variability (35 [10.7] mg/dL vs. 46 [10.7] mg/dL; p = 0.003); and less (median [IQR]) time below target (0.0 [0.0-0.4]% vs. 0.80 [0.0-3.9]%; p = 0.025). In adolescents, time below target was lower with Android-HCLS vs. SAP-LGS (0.0 [0.0-0.0]% vs. 1.8 [0.1-7.9]%; p = 0.011). Nocturnal symptomatic hypoglycemia was less (1 vs. 10; p = 0.007) in adolescents, but not adults (5 vs. 13; p = 0.059). In adults, treatment satisfaction increased by 10 points (p < 0.02). Sleep quality and cognition did not differ. CONCLUSIONS: Android-HCLS in both adults and adolescents reduced nocturnal hypoglycemia and, in adults, improved overnight time in target range and treatment satisfaction compared with SAP-LGS.