Continuous Glucose Deviation Interval and Variability Analysis (CG-DIVA): A Novel Approach for the Statistical Accuracy Assessment of Continuous Glucose Monitoring Systems.

FDA iCGM requirements accuracy continuous glucose monitoring deviation intervals sensor-to-sensor variability

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:
03 Nov 2022
Historique:
entrez: 4 11 2022
pubmed: 5 11 2022
medline: 5 11 2022
Statut: aheadofprint

Résumé

The accuracy of continuous glucose monitoring (CGM) systems is crucial for the management of glucose levels in individuals with diabetes mellitus. However, the discussion of CGM accuracy is challenged by an abundance of parameters and assessment methods. The aim of this article is to introduce the Continuous Glucose Deviation Interval and Variability Analysis (CG-DIVA), a new approach for a comprehensive characterization of CGM point accuracy which is based on the U.S. Food and Drug Administration requirements for "integrated" CGM systems. The statistical concept of tolerance intervals and data from two approved CGM systems was used to illustrate the CG-DIVA. The CG-DIVA characterizes the expected range of deviations of the CGM system from a comparison method in different glucose concentration ranges and the variability of accuracy within and between sensors. The results of the CG-DIVA are visualized in an intuitive and straightforward graphical presentation. Compared with conventional accuracy characterizations, the CG-DIVA infers the expected accuracy of a CGM system and highlights important differences between CGM systems. Furthermore, it provides information on the incidence of large errors which are of particular clinical relevance. A software implementation of the CG-DIVA is freely available (https://github.com/IfDTUlm/CGM_Performance_Assessment). We argue that the CG-DIVA can simplify the discussion and comparison of CGM accuracy and could replace the high number of conventional approaches. Future adaptations of the approach could thus become a putative standard for the accuracy characterization of CGM systems and serve as the basis for the definition of future CGM performance requirements.

Sections du résumé

BACKGROUND UNASSIGNED
The accuracy of continuous glucose monitoring (CGM) systems is crucial for the management of glucose levels in individuals with diabetes mellitus. However, the discussion of CGM accuracy is challenged by an abundance of parameters and assessment methods. The aim of this article is to introduce the Continuous Glucose Deviation Interval and Variability Analysis (CG-DIVA), a new approach for a comprehensive characterization of CGM point accuracy which is based on the U.S. Food and Drug Administration requirements for "integrated" CGM systems.
METHODS UNASSIGNED
The statistical concept of tolerance intervals and data from two approved CGM systems was used to illustrate the CG-DIVA.
RESULTS UNASSIGNED
The CG-DIVA characterizes the expected range of deviations of the CGM system from a comparison method in different glucose concentration ranges and the variability of accuracy within and between sensors. The results of the CG-DIVA are visualized in an intuitive and straightforward graphical presentation. Compared with conventional accuracy characterizations, the CG-DIVA infers the expected accuracy of a CGM system and highlights important differences between CGM systems. Furthermore, it provides information on the incidence of large errors which are of particular clinical relevance. A software implementation of the CG-DIVA is freely available (https://github.com/IfDTUlm/CGM_Performance_Assessment).
CONCLUSIONS UNASSIGNED
We argue that the CG-DIVA can simplify the discussion and comparison of CGM accuracy and could replace the high number of conventional approaches. Future adaptations of the approach could thus become a putative standard for the accuracy characterization of CGM systems and serve as the basis for the definition of future CGM performance requirements.

Identifiants

pubmed: 36329636
doi: 10.1177/19322968221134639
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

19322968221134639

Auteurs

Manuel Eichenlaub (M)

Institut für Diabetes-Technologie, Forschungs- und Entwicklungsgesellschaft mbH an der Universität Ulm, Ulm, Germany.

Peter Stephan (P)

Mannheim, Germany.

Delia Waldenmaier (D)

Institut für Diabetes-Technologie, Forschungs- und Entwicklungsgesellschaft mbH an der Universität Ulm, Ulm, Germany.

Stefan Pleus (S)

Institut für Diabetes-Technologie, Forschungs- und Entwicklungsgesellschaft mbH an der Universität Ulm, Ulm, Germany.

Martina Rothenbühler (M)

Diabetes Center Berne, Bern, Switzerland.

Cornelia Haug (C)

Institut für Diabetes-Technologie, Forschungs- und Entwicklungsgesellschaft mbH an der Universität Ulm, Ulm, Germany.

Rolf Hinzmann (R)

Roche Diabetes Care GmbH, Mannheim, Germany.
IFCC Scientific Division - Working Group on Continuous Glucose Monitoring (WG-CGM).

Andreas Thomas (A)

IFCC Scientific Division - Working Group on Continuous Glucose Monitoring (WG-CGM).
Pirna, Germany.

Johan Jendle (J)

IFCC Scientific Division - Working Group on Continuous Glucose Monitoring (WG-CGM).
Department of Medical Sciences, Örebro University, Örebro, Sweden.

Peter Diem (P)

IFCC Scientific Division - Working Group on Continuous Glucose Monitoring (WG-CGM).
Endokrinologie Diabetologie Bern, Bern, Switzerland.

Guido Freckmann (G)

Institut für Diabetes-Technologie, Forschungs- und Entwicklungsgesellschaft mbH an der Universität Ulm, Ulm, Germany.
IFCC Scientific Division - Working Group on Continuous Glucose Monitoring (WG-CGM).

Classifications MeSH