Dual-Hormone Closed-Loop System Using a Liquid Stable Glucagon Formulation Versus Insulin-Only Closed-Loop System Compared With a Predictive Low Glucose Suspend System: An Open-Label, Outpatient, Single-Center, Crossover, Randomized Controlled Trial.


Journal

Diabetes care
ISSN: 1935-5548
Titre abrégé: Diabetes Care
Pays: United States
ID NLM: 7805975

Informations de publication

Date de publication:
11 2020
Historique:
received: 11 11 2019
accepted: 16 08 2020
pubmed: 11 9 2020
medline: 25 5 2021
entrez: 10 9 2020
Statut: ppublish

Résumé

To assess the efficacy and feasibility of a dual-hormone (DH) closed-loop system with insulin and a novel liquid stable glucagon formulation compared with an insulin-only closed-loop system and a predictive low glucose suspend (PLGS) system. In a 76-h, randomized, crossover, outpatient study, 23 participants with type 1 diabetes used three modes of the Oregon Artificial Pancreas system: DH reduced hypoglycemia compared with SH during and after exercise (DH 0.0% [interquartile range 0.0-4.2], SH 8.3% [0.0-12.5], The glucagon formulation demonstrated feasibility in a closed-loop system. The DH system reduced hypoglycemia during and after exercise, with some increase in hyperglycemia.

Identifiants

pubmed: 32907828
pii: dc19-2267
doi: 10.2337/dc19-2267
doi:

Substances chimiques

Blood Glucose 0
Hypoglycemic Agents 0
Insulin 0
Glucagon 9007-92-5

Banques de données

ClinicalTrials.gov
['NCT03424044']
figshare
['10.2337/figshare.12815861']

Types de publication

Journal Article Randomized Controlled Trial Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

2721-2729

Informations de copyright

© 2020 by the American Diabetes Association.

Auteurs

Leah M Wilson (LM)

Harold Schnitzer Diabetes Health Center, Division of Endocrinology, Oregon Health & Science University, Portland, OR wilsolea@ohsu.edu.

Peter G Jacobs (PG)

Artificial Intelligence for Medical Systems (AIMS) Lab, Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR.

Katrina L Ramsey (KL)

Oregon Clinical and Translational Research Institute Biostatistics and Design Program, Oregon Health & Science University & Portland State University School of Public Health, Portland, OR.

Navid Resalat (N)

Artificial Intelligence for Medical Systems (AIMS) Lab, Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR.

Ravi Reddy (R)

Artificial Intelligence for Medical Systems (AIMS) Lab, Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR.

Deborah Branigan (D)

Harold Schnitzer Diabetes Health Center, Division of Endocrinology, Oregon Health & Science University, Portland, OR.

Joseph Leitschuh (J)

Artificial Intelligence for Medical Systems (AIMS) Lab, Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR.

Virginia Gabo (V)

Harold Schnitzer Diabetes Health Center, Division of Endocrinology, Oregon Health & Science University, Portland, OR.

Florian Guillot (F)

Harold Schnitzer Diabetes Health Center, Division of Endocrinology, Oregon Health & Science University, Portland, OR.

Brian Senf (B)

Harold Schnitzer Diabetes Health Center, Division of Endocrinology, Oregon Health & Science University, Portland, OR.

Joseph El Youssef (J)

Harold Schnitzer Diabetes Health Center, Division of Endocrinology, Oregon Health & Science University, Portland, OR.
Artificial Intelligence for Medical Systems (AIMS) Lab, Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR.

Isabelle Isa Kristin Steineck (IIK)

Steno Diabetes Center Copenhagen, Gentofte, Denmark.

Nichole S Tyler (NS)

Artificial Intelligence for Medical Systems (AIMS) Lab, Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR.

Jessica R Castle (JR)

Harold Schnitzer Diabetes Health Center, Division of Endocrinology, Oregon Health & Science University, Portland, OR.

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Classifications MeSH