Clinical use of a 180-day implantable glucose sensor improves glycated haemoglobin and time in range in patients with type 1 diabetes.


Journal

Diabetes, obesity & metabolism
ISSN: 1463-1326
Titre abrégé: Diabetes Obes Metab
Pays: England
ID NLM: 100883645

Informations de publication

Date de publication:
07 2020
Historique:
received: 17 12 2019
revised: 25 01 2020
accepted: 04 02 2020
pubmed: 11 2 2020
medline: 25 6 2021
entrez: 11 2 2020
Statut: ppublish

Résumé

This real-world study evaluated the changes in glycated haemoglobin (HbA1c) and continuous glucose monitoring (CGM) metrics associated with use of the implantable 180-day Eversense CGM System (Eversense) in patients with type 1 diabetes. This was a prospective, multicentre, observational study among adult participants aged ≥18 years with type 1 diabetes across seven diabetes-care centres in Italy who had Eversense inserted for the first time. HbA1c was measured at baseline and at 180 days. Changes in time in range [TIR (glucose 70-180 mg/dL)], time above range [TAR (glucose >180 mg/dL)], time below range [TBR (glucose <70 mg/dL)] and glycaemic variability were also assessed. Data were also analysed by previous CGM use and by mode of insulin delivery. One-hundred patients were enrolled (mean age 36 ± 12 years, mean baseline HbA1c 7.4 ± 0.92% [57 ± 10 mmol/mol]). Fifty-six per cent of patients were users of the continuous subcutaneous insulin infusion pump and 45% were previous users of CGM. HbA1c significantly decreased in patients after 180 days of sensor wear (-0.43% ± 0.69%, 5 ± 8 mmol/mol, P < 0.0001). As expected, CGM-naïve patients achieved the greatest reduction in HbA1c (-0.74% ± 0.48%, 8 ± 5 mmol/mol). TIR significantly increased and TAR and mean daily sensor glucose significantly decreased while TBR did not change after 180 days of sensor wear. Real-world clinical use of the Eversense CGM System for 180 days was associated with significant improvements in HbA1c and CGM metrics among adults with type 1 diabetes. The study is registered on clinicaltrials.gov (NCT04160156).

Identifiants

pubmed: 32037699
doi: 10.1111/dom.13993
pmc: PMC7317779
doi:

Substances chimiques

Blood Glucose 0
Glycated Hemoglobin A 0
Insulin 0

Banques de données

ClinicalTrials.gov
['NCT04160156']

Types de publication

Journal Article Multicenter Study Observational Study

Langues

eng

Sous-ensembles de citation

IM

Pagination

1056-1061

Informations de copyright

© 2020 The Authors. Diabetes, Obesity and Metabolism published by John Wiley & Sons Ltd.

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Auteurs

Concetta Irace (C)

Department of Health Science, University Magna Graecia, Catanzaro, Italy.

Antonio Cutruzzolà (A)

Department of Clinical and Experimental Medicine, University Magna Graecia, Catanzaro, Italy.

Annamaria Nuzzi (A)

Diabetologia ed Endocrinologia ASL CN2, Alba Bra, Italy.

Roberta Assaloni (R)

SSD di Diabetologia, AAS2 Bassa Friulana-Isontina, Italy.

Barbara Brunato (B)

SSD di Diabetologia, AAS2 Bassa Friulana-Isontina, Italy.

Dario Pitocco (D)

UOSA Diabetologia, Fondazione IRCCS, University Agostino Gemelli, Rome, Italy.

Linda Tartaglione (L)

UOSA Diabetologia, Fondazione IRCCS, University Agostino Gemelli, Rome, Italy.

Sergio Di Molfetta (S)

Medicina Interna, Endocrinologia, Andrologia e Malattie Metaboliche, D.E.T.O., Università degli Studi di Bari "Aldo Moro", Bari, Italy.

Angelo Cignarelli (A)

Medicina Interna, Endocrinologia, Andrologia e Malattie Metaboliche, D.E.T.O., Università degli Studi di Bari "Aldo Moro", Bari, Italy.

Luigi Laviola (L)

Medicina Interna, Endocrinologia, Andrologia e Malattie Metaboliche, D.E.T.O., Università degli Studi di Bari "Aldo Moro", Bari, Italy.

Giuseppe Citro (G)

UOSD Diabetologia ed Endocrinologia ASP, Potenza, Italy.

Elisabetta Lovati (E)

Clinica Medica I, Fondazione IRCCS, University San Matteo, Pavia, Italy.

Agostino Gnasso (A)

Department of Clinical and Experimental Medicine, University Magna Graecia, Catanzaro, Italy.

Katherine S Tweden (KS)

Senseonics Inc., Germantown, Maryland, US.

Francine R Kaufman (FR)

Senseonics Inc., Germantown, Maryland, US.

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Classifications MeSH