Variability of Insulin Requirements Over 12 Weeks of Closed-Loop Insulin Delivery in Adults With Type 1 Diabetes.

OBJECTIVE: To quantify variability of insulin requirements during closed-loop insulin delivery. RESEARCH DESIGN AND METHODS: We retrospectively analyzed overnight, daytime, and total daily insulin amounts delivered during a multicenter closed-loop trial involving 32 adults with type 1 diabetes. Participants applied hybrid day-and-night closed-loop insulin delivery under free-living home conditions over 12 weeks. The coefficient of variation was adopted to measure variability of insulin requirements in individual subjects. RESULTS: Data were analyzed from 1,918 nights, 1,883 daytime periods and 1,564 total days characterized by closed-loop use over 85% of time. Variability of overnight insulin requirements (mean [SD] coefficient of variation 31% [4]) was nearly twice as high as variability of total daily requirements (17% [3], P < 0.001) and was also higher than variability of daytime insulin requirements (22% [4], P < 0.001). CONCLUSIONS: Overnight insulin requirements were significantly more variable than daytime and total daily amounts. This may explain why some people with type 1 diabetes report frustrating variability in morning glycemia.Seventh Framework Programme of the European Union (ICT FP7- 247138). Additional support for the Artificial Pancreas work by JDRF, National Institute for Health Research Cambridge Biomedical Research Centre and Wellcome Strategic Award (100574/Z/12/Z). Abbott Diabetes Care supplied discounted continuous glucose monitoring devices, sensors, and communication protocol to facilitate real-time connectivity. We acknowledge support by the staff at the Addenbrooke’s Wellcome Trust Clinical Research Facility. Jasdip Mangat and John Lum (Jaeb Center) supported development and validation of the closed-loop system. Josephine Hayes (University of Cambridge) provided administrative support. Karen Whitehead (University of Cambridge) provided laboratory support. We acknowledge support by the staff at Profil Institut; Krisztina Schmitz-Grozs provided support as a research physician, Martina Haase supported the study as an insulin pump expert, and Maren Luebkert, Kirstin Kuschma and Elke Przetak provided administrative, coordinating and documentation support.This is the author accepted manuscript. The final version is available from the American Diabetes Association via http://dx.doi.org/10.2337/dc15-262

Automated closed-loop insulin delivery for the management of type 1 diabetes during pregnancy: the AiDAPT RCT

Background There are over 2000 pregnancies annually in women with type 1 diabetes in the UK. Despite recent improvements in diabetes technology, most women cannot achieve and maintain the recommended pregnancy glucose targets. Thus, one in two babies experience complications requiring neonatal care unit admission. Recent studies demonstrate that hybrid closed-loop therapy, in which algorithms adjust insulin delivery according to continuous glucose measurements, is effective for managing type 1 diabetes outside of pregnancy, but efficacy during pregnancy is unclear. Objective To examine the clinical efficacy of hybrid closed-loop compared to standard insulin therapy in pregnant women with type 1 diabetes. Design A multicentre, parallel-group, open-label, randomised, controlled trial in pregnant women with type 1 diabetes. Setting Nine antenatal diabetes clinics in England, Scotland and Northern Ireland. Participants Pregnant women with type 1 diabetes and above-target glucose levels, defined as glycated haemoglobin A1c of ≥ 48 mmol/mol (6.5%) in early pregnancy. Interventions A hybrid closed-loop system compared to standard insulin delivery (via insulin pump or multiple daily injections) with continuous glucose monitoring. Outcome measures The primary outcome is the difference between the intervention and control groups in percentage time spent in the pregnancy glucose target range (3.5–7.8 mmol/l) as measured by continuous glucose monitoring from 16 weeks’ gestation until delivery. Secondary outcomes include overnight time in range, time above range (> 7.8 mmol/l), glycated haemoglobin A1c, safety outcomes (diabetic ketoacidosis, severe hypoglycaemia, adverse device events), psychosocial functioning obstetric and neonatal outcomes. Results The percentage of time that maternal glucose levels were within target range was higher with closed-loop than standard insulin therapy: 68.2 ± 10.5 in closed-loop and 55.6 ± 12.5 in the control group (mean‑adjusted difference 10.5 percentage points, 95% confidence interval 7.0 to 14.0; p < 0.001). Results were consistent in secondary outcomes, with less time above range (−10.2%, 95% confidence interval −13.8 to −6.6%; p < 0.001), higher overnight time in range (12.3%, 95% confidence interval 8.3 to 16.2%; p < 0.001) and lower glycated haemoglobin A1c (−0.31%, 95% confidence interval −0.50 to −0.12%; p < 0.002) all favouring closed-loop. The treatment effect was apparent from early pregnancy and consistent across clinical sites, maternal glycated haemoglobin A1c categories and previous insulin regimen. Maternal glucose improvements were achieved with 3.7 kg less gestational weight gain and without additional hypoglycaemia or total daily insulin dose. There were no unanticipated safety problems (six vs. five severe hypoglycaemia cases, one diabetic ketoacidosis per group) and seven device-related adverse events associated with closed-loop. There were no between-group differences in patient-reported outcomes. There was one shoulder dystocia in the closed-loop group and four serious birth injuries, including one neonatal death in the standard care group. Limitations Our results cannot be extrapolated to closed-loop systems with higher glucose targets, and our sample size did not provide definitive data on maternal and neonatal outcomes. Conclusions Hybrid closed-loop therapy significantly improved maternal glycaemia during type 1 diabetes pregnancy. Our results support National Institute for Health and Care Excellence guideline recommendations that hybrid closed-loop therapy should be offered to all pregnant women with type 1 diabetes. Future work Future trials should examine the effectiveness of hybrid closed-loop started before pregnancy, or as soon as possible after pregnancy confirmation

Comparison of faster-acting aspart with insulin aspart under conditions mimicking underestimation or missed meal boluses in type 1 diabetes using closed-loop insulin delivery.

Funder: Novo Nordisk; Id: http://dx.doi.org/10.13039/50110000419

Evaluating the Impact of Applying Personal Glucose Targets in a Closed-Loop System for People With Type 1 Diabetes

Peer reviewed: TrueFunder: JDRF; FundRef: https://doi.org/10.13039/100008871Funder: National Institute for Health Research Cambridge Biomedical Research CentreBackground: CamAPS FX is a hybrid closed-loop smartphone app used to manage type one diabetes. The closed-loop algorithm has a default target glucose of 5.8 mmol/L (104.5 mg/dL), but users can select personal glucose targets (adjustable between 4.4 mmol/L and 11.0 mmol/L [79 mg/dL and 198 mg/dL, respectively]). Method: In this post-hoc analysis, we evaluated the impact of personal glucose targets on glycemic control using data from participants in five randomized controlled trials. Results: Personal glucose targets were widely used, with 20.3% of all days in the data set having a target outside the default target bin (5.5-6.0 mmol/L [99-108 mg/dL]). Personal glucose targets >6.5 mmol/L (117 mg/dL) were associated with significantly less time in target range (3.9-10.0 mmol/L [70-180 mg/dL]; 6.5-7.0 mmol/L [117-126 mg/dL]: mean difference = −3.2 percentage points [95% CI: −5.3 to −1.2; P 6.5 mmol/L (117 mg/dL) were associated with significantly lower time (<3.9 mmol/L [<70 mg/dL]; 6.5-7.0 mmol/L [117-126 mg/dL]: −1.85 percentage points [95% CI: −2.37 to −1.34; P < .001]; 7.0-7.5 mmol/L [126-135 mg/dL]: −2.68 percentage points [95% CI: −3.49 to −1.86; P < .001]). Conclusions: Discrete study populations showed differences in glucose control when applying similar personal targets