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cgmanalysis: An R package for descriptive analysis of continuous glucose monitor data

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  • Tim Vigers
  • Christine L Chan
  • Janet Snell-Bergeon
  • Petter Bjornstad
  • Philip S Zeitler
  • Gregory Forlenza
  • Laura Pyle

Abstract

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.

Suggested Citation

  • Tim Vigers & Christine L Chan & Janet Snell-Bergeon & Petter Bjornstad & Philip S Zeitler & Gregory Forlenza & Laura Pyle, 2019. "cgmanalysis: An R package for descriptive analysis of continuous glucose monitor data," PLOS ONE, Public Library of Science, vol. 14(10), pages 1-12, October.
    • Handle: RePEc:plo:pone00:0216851
    DOI: 10.1371/journal.pone.0216851
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