Safety of User-Initiated Intensification of Insulin Delivery Using Cambridge Hybrid Closed-Loop Algorithm

Author:

Ware Julia12ORCID,Wilinska Malgorzata E.12,Ruan Yue1,Allen Janet M.1,Boughton Charlotte K.13ORCID,Hartnell Sara3,Bally Lia4,de Beaufort Carine56,Besser Rachel E. J.78ORCID,Campbell Fiona M.9,Draxlbauer Katharine10,Elleri Daniela11,Evans Mark L.13ORCID,Fröhlich-Reiterer Elke12,Ghatak Atrayee13,Hofer Sabine E.14,Kapellen Thomas M.15,Leelarathna Lalantha1617ORCID,Mader Julia K.18ORCID,Mubita Womba M.19,Narendran Parth1019,Poettler Tina18,Rami-Merhar Birgit20,Tauschmann Martin20,Randell Tabitha21,Thabit Hood1617ORCID,Thankamony Ajay2,Trevelyan Nicola22,Hovorka Roman12ORCID

Affiliation:

1. Metabolic Research Laboratories, Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK

2. Department of Paediatrics, University of Cambridge, Cambridge, UK

3. Department of Diabetes and Endocrinology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK

4. Department of Diabetes, Endocrinology, Nutritional Medicine and Metabolism, Inselspital, Bern University Hospital, Bern, Switzerland

5. Diabetes & Endocrine Care Clinique Pediatrique, Centre Hospitalier de Luxembourg, Luxembourg City, Luxembourg

6. Department of Paediatric Endocrinology, UZ-VUB, Brussels, Belgium

7. NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, UK

8. Department of Paediatrics, University of Oxford, Oxford, UK

9. Department of Paediatric Diabetes, Leeds Children’s Hospital, Leeds, UK

10. University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK

11. Department of Diabetes, Royal Hospital for Sick Children, Edinburgh, UK

12. Department of Pediatric and Adolescent Medicine, Medical University of Graz, Graz, Austria

13. Department of Diabetes, Alder Hey Children’s NHS Foundation Trust, Liverpool, UK

14. Department of Pediatrics I, Medical University of Innsbruck, Innsbruck, Austria

15. Hospital for Children and Adolescents, Leipzig University, Leipzig, Germany

16. Diabetes, Endocrinology and Metabolism Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK

17. Division of Diabetes, Endocrinology & Gastroenterology, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK

18. Division of Endocrinology and Diabetology, Department of Internal Medicine, Medical University of Graz, Graz, Austria

19. Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK

20. Department of Paediatrics and Adolescent Medicine, Medical University of Vienna, Vienna, Austria

21. Department of Paediatric Diabetes and Endocrinology, Nottingham Children’s Hospital, Nottingham University Hospitals NHS Trust, Nottingham, UK

22. Department of Paediatric Endocrinology and Diabetes, Southampton Children’s Hospital, Southampton General Hospital, Southampton, UK

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.

Funder

Wellcome Trust Strategic Award

Horizon 2020 Framework Programme

National Institute of Diabetes and Digestive and Kidney Diseases

JDRF

Leona M. and Harry B. Helmsley Charitable Trust

NIHR Cambridge Biomedical Research Centre

NIHR EME

Publisher

SAGE Publications

Subject

Biomedical Engineering,Bioengineering,Endocrinology, Diabetes and Metabolism,Internal Medicine

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