Fully Automated Artificial Pancreas for Adults With Type 1 Diabetes Using Multiple Hormones: Exploratory Experiments.

algorithme artificial pancreas calcul des glucides closed-loop systems diabète de type 1 glucagon insulin insuline optimisation pancréas artificiel pramlintide systèmes en boucle fermée type 1 diabetes

Journal

Canadian journal of diabetes
ISSN: 2352-3840
Titre abrégé: Can J Diabetes
Pays: Canada
ID NLM: 101148810

Informations de publication

Date de publication:
Dec 2021
Historique:
received: 10 07 2020
revised: 11 02 2021
accepted: 14 02 2021
pubmed: 24 4 2021
medline: 14 1 2022
entrez: 23 4 2021
Statut: ppublish

Résumé

A fully automated insulin-pramlintide-glucagon artificial pancreas that alleviates the burden of carbohydrate counting without degrading glycemic control was iteratively enhanced until convergence through pilot experiments on adults with type 1 diabetes. Nine participants (age, 37±13 years; glycated hemoglobin, 7.7±0.7%) completed two 27-hour interventions: a fully automated multihormone artificial pancreas and a comparator insulin-alone artificial pancreas with carbohydrate counting. The baseline algorithm was a model-predictive controller that administered insulin and pramlintide in a fixed ratio, with boluses triggered by a glucose threshold, and administered glucagon in response to low glucose levels. The baseline multihormone dosing algorithm resulted in noninferior time in target range (3.9 to 10.0 mmol/L) (71%) compared with the insulin-alone arm (70%) in 2 participants, with minimal glucagon delivery. The algorithm was modified to deliver insulin and pramlintide more aggressively to increase time in range and maximize the benefits of glucagon. The modified algorithm displayed a similar time in range for the multihormone arm (79%) compared with the insulin-alone arm (83%) in 2 participants, but with undesired glycemic fluctuations. Subsequently, we reduced the glucose threshold that triggers glucagon boluses. This resulted in inferior glycemic control for the multihormone arm (81% vs 91%) in 2 participants. Thereafter, a model-based meal-detection algorithm to deliver insulin and pramlintide boluses closer to mealtimes was added and glucagon was removed. The final dual-hormone system had comparable time in range (81% vs 83%) in the last 3 participants. The final version of the fully automated system that delivered insulin and pramlintide warrants a randomized controlled trial.

Identifiants

pubmed: 33888413
pii: S1499-2671(21)00045-9
doi: 10.1016/j.jcjd.2021.02.002
pii:
doi:

Substances chimiques

Blood Glucose 0
Hypoglycemic Agents 0
Insulin 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

734-742

Informations de copyright

Copyright © 2021 Canadian Diabetes Association. Published by Elsevier Inc. All rights reserved.

Auteurs

Dorsa Majdpour (D)

Department of Biomedical Engineering, McGill University, Montréal, Québec, Canada; The Research Institute of McGill University Health Centre, Montréal, Québec, Canada.

Michael A Tsoukas (MA)

The Research Institute of McGill University Health Centre, Montréal, Québec, Canada; Royal Victoria Hospital, McGill University Health Centre, Montréal, Québec, Canada.

Jean-François Yale (JF)

The Research Institute of McGill University Health Centre, Montréal, Québec, Canada; Royal Victoria Hospital, McGill University Health Centre, Montréal, Québec, Canada.

Anas El Fathi (A)

Department of Biomedical Engineering, McGill University, Montréal, Québec, Canada.

Joanna Rutkowski (J)

Department of Biomedical Engineering, McGill University, Montréal, Québec, Canada.

Jennifer Rene (J)

Royal Victoria Hospital, McGill University Health Centre, Montréal, Québec, Canada.

Natasha Garfield (N)

Royal Victoria Hospital, McGill University Health Centre, Montréal, Québec, Canada.

Laurent Legault (L)

The Research Institute of McGill University Health Centre, Montréal, Québec, Canada; Montreal Children's Hospital, McGill University Health Centre, Montréal, Québec, Canada.

Ahmad Haidar (A)

Department of Biomedical Engineering, McGill University, Montréal, Québec, Canada. Electronic address: ahmad.haidar@mcgill.ca.

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