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Original ArticleFree Preview
Open-source automated insulin delivery (AID) systems are used by many patients with type 1 diabetes. Data are needed on the efficacy and safety of an open-source AID system.
Download a PDF of the Research Summary.
In this multicenter, open-label, randomized, controlled trial, we assigned patients with type 1 diabetes in a 1:1 ratio to use an open-source AID system or a sensor-augmented insulin pump (control). The patients included both children (defined as 7 to 15 years of age) and adults (defined as 16 to 70 years of age). The AID system was a modified version of AndroidAPS 2.8 (with a standard OpenAPS 0.7.0 algorithm) paired with a preproduction DANA-i insulin pump and Dexcom G6 CGM, which has an Android smartphone application as the user interface. The primary outcome was the percentage of time in the target glucose range of 70 to 180 mg per deciliter (3.9 to 10.0 mmol per liter) between days 155 and 168 (the final 2 weeks of the trial).
A total of 97 patients (48 children and 49 adults) underwent randomization (44 to open-source AID and 53 to the control group). At 24 weeks, the mean (±SD) time in the target range increased from 61.2±12.3% to 71.2±12.1% in the AID group and decreased from 57.7±14.3% to 54.5±16.0% in the control group (adjusted difference, 14 percentage points; 95% confidence interval, 9.2 to 18.8; P<0.001), with no treatment effect according to age (P=0.56). Patients in the AID group spent 3 hours 21 minutes more in the target range per day than those in the control group. No severe hypoglycemia or diabetic ketoacidosis occurred in either group. Two patients in the AID group withdrew from the trial owing to connectivity issues.
In children and adults with type 1 diabetes, the use of an open-source AID system resulted in a significantly higher percentage of time in the target glucose range than the use of a sensor-augmented insulin pump at 24 weeks. (Supported by the Health Research Council of New Zealand; Australian New Zealand Clinical Trials Registry number, ACTRN12620000034932.)
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Automated Insulin Delivery in Type 1 Diabetes

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Supported by the Health Research Council of New Zealand. Hardware support was provided by SOOIL Development, Dexcom, and Vodafone New Zealand.
Disclosure forms provided by the authors are available with the full text of this article at
A data sharing statement provided by the authors is available with the full text of this article at
From the Departments of Pediatrics (M.J.B., R.A.M., O.J.S., M.I.B.) and Population Health (J.A.W.), University of Otago, and the Department of Pediatrics, Canterbury District Health Board (M.J.B., O.J.S., M.I.B.), Christchurch, Te Huataki Waiora School of Health, Sport and Human Performance, University of Waikato (H.R.C.), and Waikato Regional Diabetes Service, Waikato District Health Board (R.G.P., C.S.L., S.K.J.P.), Hamilton, the Department of Pediatric Endocrinology, Starship Children’s Health, Auckland District Health Board (C.A.J., A.M.F., C.L.), and the Liggins Institute, University of Auckland (C.A.J.), Auckland, the Department of Women’s and Children’s Health, Dunedin School of Medicine, University of Otago (C.M.F., S.D.J., B.J.W.), and the Pediatric Department, Southern District Health Board (B.J.W.), Dunedin, and Nightscout New Zealand, Hamilton (T.C.G.) — all in New Zealand; and OpenAPS, Seattle (D.M.L.).
Dr. de Bock can be contacted at or at the Department of Pediatrics, University of Otago, 4 Oxford Terrace, Christchurch 8011, New Zealand.
September 8, 2022
N Engl J Med 2022; 387:869-881
DOI: 10.1056/NEJMoa2203913

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