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Interpreting blood GLUcose data with R package iglu.

Steven Broll1, Jacek Urbanek2, David Buchanan1

  • 1Department of Statistics, Texas A&M University, College Station, TX, United States of America.

Plos One
|April 1, 2021
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Summary
This summary is machine-generated.

The R package iglu offers comprehensive tools for analyzing continuous glucose monitoring (CGM) data, simplifying glucose control and variability assessments for researchers and clinicians.

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Area of Science:

  • Biomedical Informatics
  • Endocrinology
  • Data Science

Background:

  • Continuous Glucose Monitoring (CGM) provides detailed 24-hour glucose level data, crucial for clinical practice.
  • Analyzing CGM data requires specialized tools to extract meaningful insights into glucose control and variability.

Purpose of the Study:

  • To introduce the R package iglu, designed for comprehensive analysis and visualization of CGM data.
  • To enhance accessibility of CGM data analysis through an intuitive graphical user interface (GUI).

Main Methods:

  • Implementation of a wide range of CGM-derived metrics for glucose control and variability assessment.
  • Inclusion of visualization tools such as time-series and lasagna plots for CGM data.
  • Development of a point-and-click graphical user interface (GUI) for user-friendly operation.

Main Results:

  • The iglu package provides robust metrics for quantifying glucose control and variability from CGM data.
  • Visualization capabilities allow for clear interpretation of glucose trends and patterns.
  • The GUI makes advanced CGM data analysis accessible to users without programming expertise.

Conclusions:

  • The iglu R package is a valuable, open-source tool for advancing CGM research and data analysis.
  • Its ease of use and comprehensive features facilitate wider adoption and application in clinical settings.