Safety of User-Initiated Intensification of Insulin Delivery Using Cambridge Hybrid Closed-Loop Algorithm
Year: 2022
Type: article
Abstract: Objective: Many hybrid closed-loop (HCL) systems struggle to manage unusually high glucose levels as experienced with intercurrent illness or pre-menstrually. Manual correction boluses may be needed, increasing hypoglycemia risk with overcorrection. The Cambridge HCL system includes a user-initiated algorithm intensification mode (“Boost”), activation of which increases automated insulin delivery by approximately 35%, while remaining glucose-responsive. In this analysis, we assessed the safety of “Boost” mode. Methods: We retrospectively analyzed data from closed-loop studies involving young children (1-7 years, n = 24), children and adolescents (10-17 years, n = 19), adults (≥24 years, n = 13), and older adults (≥60 years, n = 20) with type 1 diabetes. Outcomes were calculated per participant for days with ≥30 minutes of “Boost” use versus days with no “Boost” use. Participants with <10 “Boost” days were excluded. The main outcome was time spent in hypoglycemia <70 and <54 mg/dL. Results: Eight weeks of data for 76 participants were analyzed. There was no difference in time spent <70 and <54 mg/dL between “Boost” days and “non-Boost” days; mean difference: –0.10% (95% confidence interval [CI] –0.28 to 0.07; P = .249) time <70 mg/dL, and 0.03 (–0.04 to 0.09; P = .416) time < 54 mg/dL. Time in significant hyperglycemia >300 mg/dL was 1.39 percentage points (1.01 to 1.77; P < .001) higher on “Boost” days, with higher mean glucose and lower time in target range ( P < .001). Conclusions: Use of an algorithm intensification mode in HCL therapy is safe across all age groups with type 1 diabetes. The higher time in hyperglycemia observed on “Boost” days suggests that users are more likely to use algorithm intensification on days with extreme hyperglycemic excursions.
Authors: Julia Ware, Malgorzata E. Wilinska, Yue Ruan, Janet M. Allen, Charlotte K. Boughton, Sara Hartnell, Lia Bally, Carine de Beaufort, Rachel E. J. Besser, Fiona M. Campbell, Katharine Draxlbauer, Daniela Elleri, Mark L. Evans, Elke Fröhlich-Reiterer, Atrayee Ghatak, Sabine E. Hofer, Thomas M. Kapellen, Lalantha Leelarathna, Julia K. Mader, Womba M. Mubita, Parth Narendran, Tina Poettler, Birgit Rami-Merhar, Martin Tauschmann, Tabitha Randell, Hood Thabit, Ajay Thankamony, Nicola Trevelyan, Roman Hovorka
Institutions: University of Cambridge, Wellcome/MRC Institute of Metabolic Science, Wellcome Trust, Cambridge University Hospitals NHS Foundation Trust, University Hospital of Bern, Vrije Universiteit Brussel, Centre Hospitalier de Luxembourg, Universitair Ziekenhuis Brussel, University of Oxford, NIHR Oxford Biomedical Research Centre, Leeds Teaching Hospitals NHS Trust, University Hospitals Birmingham NHS Foundation Trust, Royal Hospital for Sick Children, Medical University of Graz, Alder Hey Children's NHS Foundation Trust, Alder Hey Children's Hospital, Innsbruck Medical University, Universität Innsbruck, Leipzig University, Manchester Academic Health Science Centre, University of Manchester, Manchester University NHS Foundation Trust, University of Birmingham, Medical University of Vienna, Nottingham University Hospitals NHS Trust, Southampton General Hospital, Southampton Children's Hospital
Language: English
Subfield: Endocrinology, Diabetes and Metabolism
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $3,500
Funders: Eli Lilly and Company, AstraZeneca, Sanofi, Leona M. and Harry B. Helmsley Charitable Trust, Juvenile Diabetes Research Foundation United States of America, Wellcome Trust, Insulet Corporation, Dexcom, National Institute for Health and Care Research, Novo Nordisk, Servier, Roche Diabetes Care, Horizon 2020 Framework Programme, Abbott Diabetes Care, NIHR Cambridge Biomedical Research Centre, National Institute of Diabetes and Digestive and Kidney Diseases, NIHR Evaluation Trials and Studies Coordinating Centre
OpenAlex ID: W4310953101