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Original Research
A Meal Detection Algorithm for the Artificial Pancreas: A Randomized Controlled Clinical Trial in Adolescents With Type 1 Diabetes
Emilie Palisaitis, Anas El Fathi, Julia E. von Oettingen, Ahmad Haidar, Laurent Legault
Diabetes Care 2020 Dec; dc201232. https://doi.org/10.2337/dc20-1232
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Abstract

OBJECTIVE We developed a meal detection algorithm for the artificial pancreas (AP+MDA) that detects unannounced meals and delivers automatic insulin boluses.

RESEARCH DESIGN AND METHODS We conducted a randomized crossover trial in 11 adolescents aged 12–18 years with HbA1c ≥7.5% who missed one or more boluses in the past 6 months. We compared 1) continuous subcutaneous insulin infusion (CSII), 2) artificial pancreas (AP), and 3) AP+MDA. Participants underwent three 9-h interventions involving breakfast with a bolus and lunch without a bolus.

RESULTS In AP+MDA, the meal detection time was 40.0 (interquartile range 40.0–57.5) min. Compared with CSII, AP+MDA decreased the 4-h postlunch incremental area under the curve (iAUC) from 24.1 ± 9.5 to 15.4 ± 8.0 h ⋅ mmol/L (P = 0.03). iAUC did not differ between AP+MDA and AP (19.6 ± 10.4 h ⋅ mmol/L, P = 0.21) or between AP and CSII (P = 0.33). The AP+MDA reduced time >10 mmol/L (58.0 ± 26.6%) compared with CSII (79.6 ± 27.5%, P = 0.02) and AP (74.2 ± 20.6%, P = 0.047).

CONCLUSIONS The AP+MDA improved glucose control after an unannounced meal.

Footnotes

  • This article contains supplementary material online at https://doi.org/10.2337/figshare.13135547.

  • Received May 22, 2020.
  • Accepted October 20, 2020.
  • © 2020 by the American Diabetes Association
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A Meal Detection Algorithm for the Artificial Pancreas: A Randomized Controlled Clinical Trial in Adolescents With Type 1 Diabetes
Emilie Palisaitis, Anas El Fathi, Julia E. von Oettingen, Ahmad Haidar, Laurent Legault
Diabetes Care Dec 2020, dc201232; DOI: 10.2337/dc20-1232

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A Meal Detection Algorithm for the Artificial Pancreas: A Randomized Controlled Clinical Trial in Adolescents With Type 1 Diabetes
Emilie Palisaitis, Anas El Fathi, Julia E. von Oettingen, Ahmad Haidar, Laurent Legault
Diabetes Care Dec 2020, dc201232; DOI: 10.2337/dc20-1232
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© 2021 by the American Diabetes Association. Diabetes Care Print ISSN: 0149-5992, Online ISSN: 1935-5548.