Objective: To develop a standardized, free, open-source method for management and analysis of continuous glucose monitor (CGM) data, including calculation of key metrics recommended in the International Consensus on Use of Continuous Glucose Monitoring (ICUCGM) and graphical tools similar to the Ambulatory Glucose Profile (AGP).

Methods:  We developed a package (called cgmanalysis) written in the statistical programming language R (R Foundation for Statistical Computing, Vienna, Austria).

Results: The software can automatically recognize and read data exports from the Diasend®, Dexcom, iPro™2, Libre, and Carelink™ platforms.  Other data sources can be used if formatted appropriately.  The cleaning function processes raw data exported from a CGM device, and can handle multiple formats simultaneously.  The analysis function calculates the key metrics in the ICUCGM, in addition to other variables, including the mean amplitude of glycemic excursion (MAGE), and creates a data set for upload into a database or statistical software. The report function creates graphical data summaries, including a figure in the style of the AGP (see Figure), using Tukey smoothing to plot the median, inter-quartile range, and 5th and 95th percentiles by time of day.  Cgmanalysis is available on the Comprehensive R Archive Network, and the code and user guide are available on GitHub.  

Conclusions: The cgmanalysis package provides a standardized, free, open-source approach to manage and analyze CGM data, enabling sharing of data across technology platforms, collaboration between research groups, and more effective use of the growing pool of CGM data.

AN R PACKAGE FOR ANALYSIS OF CONTINUOUS GLUCOSE MONITOR DATA