First Outpatient Clinical Trial of a Full Closed-Loop Artificial Pancreas System in South America.


Journal

Journal of diabetes science and technology
ISSN: 1932-2968
Titre abrégé: J Diabetes Sci Technol
Pays: United States
ID NLM: 101306166

Informations de publication

Date de publication:
Jul 2023
Historique:
medline: 3 7 2023
pubmed: 14 5 2022
entrez: 13 5 2022
Statut: ppublish

Résumé

The first two studies of an artificial pancreas (AP) system carried out in Latin America took place in 2016 (phase 1) and 2017 (phase 2). They evaluated a hybrid algorithm from the University of Virginia (UVA) and the automatic regulation of glucose (ARG) algorithm in an inpatient setting using an AP platform developed by the UVA. The ARG algorithm does not require carbohydrate (CHO) counting and does not deliver meal priming insulin boluses. Here, the first outpatient trial of the ARG algorithm using an own AP platform and doubling the duration of previous phases is presented. Phase 3 involved the evaluation of the ARG algorithm in five adult participants (n = 5) during 72 hours of closed-loop (CL) and 72 hours of open-loop (OL) control in an outpatient setting. This trial was performed with an own AP and remote monitoring platform developed from open-source resources, called InsuMate. The meals tested ranged its CHO content from 38 to 120 g and included challenging meals like pasta. Also, the participants performed mild exercise (3-5 km walks) daily. The clinical trial is registered in ClinicalTrials.gov with identifier: NCT04793165. The ARG algorithm showed an improvement in the time in hyperglycemia (52.2% [16.3%] OL vs 48.0% [15.4%] CL), time in range (46.9% [15.6%] OL vs 50.9% [14.4%] CL), and mean glucose (188.9 [25.5] mg/dl OL vs 186.2 [24.7] mg/dl CL) compared with the OL therapy. No severe hyperglycemia or hypoglycemia episodes occurred during the trial. The InsuMate platform achieved an average of more than 95% of the time in CL. The results obtained demonstrated the feasibility of outpatient full CL regulation of glucose levels involving the ARG algorithm and the InsuMate platform.

Sections du résumé

BACKGROUND UNASSIGNED
The first two studies of an artificial pancreas (AP) system carried out in Latin America took place in 2016 (phase 1) and 2017 (phase 2). They evaluated a hybrid algorithm from the University of Virginia (UVA) and the automatic regulation of glucose (ARG) algorithm in an inpatient setting using an AP platform developed by the UVA. The ARG algorithm does not require carbohydrate (CHO) counting and does not deliver meal priming insulin boluses. Here, the first outpatient trial of the ARG algorithm using an own AP platform and doubling the duration of previous phases is presented.
METHOD UNASSIGNED
Phase 3 involved the evaluation of the ARG algorithm in five adult participants (n = 5) during 72 hours of closed-loop (CL) and 72 hours of open-loop (OL) control in an outpatient setting. This trial was performed with an own AP and remote monitoring platform developed from open-source resources, called InsuMate. The meals tested ranged its CHO content from 38 to 120 g and included challenging meals like pasta. Also, the participants performed mild exercise (3-5 km walks) daily. The clinical trial is registered in ClinicalTrials.gov with identifier: NCT04793165.
RESULTS UNASSIGNED
The ARG algorithm showed an improvement in the time in hyperglycemia (52.2% [16.3%] OL vs 48.0% [15.4%] CL), time in range (46.9% [15.6%] OL vs 50.9% [14.4%] CL), and mean glucose (188.9 [25.5] mg/dl OL vs 186.2 [24.7] mg/dl CL) compared with the OL therapy. No severe hyperglycemia or hypoglycemia episodes occurred during the trial. The InsuMate platform achieved an average of more than 95% of the time in CL.
CONCLUSION UNASSIGNED
The results obtained demonstrated the feasibility of outpatient full CL regulation of glucose levels involving the ARG algorithm and the InsuMate platform.

Identifiants

pubmed: 35549733
doi: 10.1177/19322968221096162
pmc: PMC10348001
doi:

Substances chimiques

Blood Glucose 0
Glucose IY9XDZ35W2
Hypoglycemic Agents 0
Insulin 0

Banques de données

ClinicalTrials.gov
['NCT04793165']

Types de publication

Clinical Trial Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1008-1015

Références

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Auteurs

Fabricio Garelli (F)

Grupo de Control Aplicado, Instituto LEICI (UNLP-CONICET), Facultad de Ingeniería, Universidad Nacional de La Plata, La Plata, Argentina.
Consejo Nacional de Investigaciones Científicas y Técnicas, Argentina.

Emilia Fushimi (E)

Grupo de Control Aplicado, Instituto LEICI (UNLP-CONICET), Facultad de Ingeniería, Universidad Nacional de La Plata, La Plata, Argentina.
Consejo Nacional de Investigaciones Científicas y Técnicas, Argentina.

Nicolás Rosales (N)

Grupo de Control Aplicado, Instituto LEICI (UNLP-CONICET), Facultad de Ingeniería, Universidad Nacional de La Plata, La Plata, Argentina.
Consejo Nacional de Investigaciones Científicas y Técnicas, Argentina.

Delfina Arambarri (D)

Grupo de Control Aplicado, Instituto LEICI (UNLP-CONICET), Facultad de Ingeniería, Universidad Nacional de La Plata, La Plata, Argentina.

Leandro Mendoza (L)

Grupo de Control Aplicado, Instituto LEICI (UNLP-CONICET), Facultad de Ingeniería, Universidad Nacional de La Plata, La Plata, Argentina.

María Cecilia Serafini (MC)

Grupo de Control Aplicado, Instituto LEICI (UNLP-CONICET), Facultad de Ingeniería, Universidad Nacional de La Plata, La Plata, Argentina.
Comisión de Investigaciones Científicas de la Provincia de Buenos Aires, Buenos Aires, Argentina.

Marcela Moscoso-Vásquez (M)

Consejo Nacional de Investigaciones Científicas y Técnicas, Argentina.
Instituto Tecnológico de Buenos Aires, Buenos Aires, Argentina.

Marianela Stasi (M)

Hospital Italiano de Buenos Aires, Buenos Aires, Argentina.

Patricia Duette (P)

Hospital Italiano de Buenos Aires, Buenos Aires, Argentina.

Julia García-Arabehety (J)

Hospital Italiano de Buenos Aires, Buenos Aires, Argentina.

Javier Nicolás Giunta (JN)

Hospital Italiano de Buenos Aires, Buenos Aires, Argentina.

Hernán De Battista (H)

Grupo de Control Aplicado, Instituto LEICI (UNLP-CONICET), Facultad de Ingeniería, Universidad Nacional de La Plata, La Plata, Argentina.
Consejo Nacional de Investigaciones Científicas y Técnicas, Argentina.

Ricardo Sánchez-Peña (R)

Consejo Nacional de Investigaciones Científicas y Técnicas, Argentina.
Instituto Tecnológico de Buenos Aires, Buenos Aires, Argentina.

Luis Grosembacher (L)

Hospital Italiano de Buenos Aires, Buenos Aires, Argentina.

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Classifications MeSH