cgmanalysis: An R package for descriptive analysis of continuous glucose monitor data.
Journal
PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081
Informations de publication
Date de publication:
2019
2019
Historique:
received:
26
04
2019
accepted:
22
09
2019
entrez:
12
10
2019
pubmed:
12
10
2019
medline:
11
3
2020
Statut:
epublish
Résumé
Continuous glucose monitoring (CGM) is an essential part of diabetes care. Real-time CGM data are beneficial to patients for daily glucose management, and aggregate summary statistics of CGM measures are valuable to direct insulin dosing and as a tool for researchers in clinical trials. Yet, the various commercial systems still report CGM data in disparate, non-standard ways. Accordingly, there is a need for a standardized, free, open-source approach to CGM data management and analysis. A package titled cgmanalysis was developed in the free programming language R to provide a rapid, easy, and consistent methodology for CGM data management, summary measure calculation, and descriptive analysis. Variables calculated by our package compare well to those generated by various CGM software, and our functions provide a more comprehensive list of summary measures available to clinicians and researchers. Consistent handling of CGM data using our R package may facilitate collaboration between research groups and contribute to a better understanding of free-living glucose patterns.
Identifiants
pubmed: 31603912
doi: 10.1371/journal.pone.0216851
pii: PONE-D-19-11955
pmc: PMC6788735
doi:
Substances chimiques
Blood Glucose
0
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
e0216851Subventions
Organisme : NIDDK NIH HHS
ID : K12 DK094712
Pays : United States
Organisme : NIDDK NIH HHS
ID : K23 DK116720
Pays : United States
Déclaration de conflit d'intérêts
The authors have declared that no competing interests exist.
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