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Cgmquantify: Python and R Software Packages for Comprehensive Analysis of Interstitial Glucose and Glycemic Variability from Continuous Glucose Monitor Data | IEEE Journals & Magazine | IEEE Xplore

Cgmquantify: Python and R Software Packages for Comprehensive Analysis of Interstitial Glucose and Glycemic Variability from Continuous Glucose Monitor Data


Impact Statement:Cgmquantify fills the current gap of a lack of systematic, reproducible, and comprehensive methods for interstitial glucose and glycemic variability analysis from continu...Show More

Abstract:

Goal: Continuous glucose monitoring (CGM) is commonly used in Type 1 diabetes management by clinicians and patients and in diabetes research to understand how factors of ...Show More
Impact Statement:
Cgmquantify fills the current gap of a lack of systematic, reproducible, and comprehensive methods for interstitial glucose and glycemic variability analysis from continuous glucose monitor data for researchers, clinicians, and patients using continuous glucose monitors.

Abstract:

Goal: Continuous glucose monitoring (CGM) is commonly used in Type 1 diabetes management by clinicians and patients and in diabetes research to understand how factors of longitudinal glucose and glucose variability relate to disease onset and severity and the efficacy of interventions. CGM data presents unique bioinformatic challenges because the data is longitudinal, temporal, and there are infinite ways to summarize and use this data. There are over 25 metrics of glucose variability used clinically and in research, metrics are not standardized, and little validation exists across studies. The primary goal of this work is to present a software resource for systematic, reproducible, and comprehensive analysis of interstitial glucose and glycemic variability from continuous glucose monitor data. Methods: Comprehensive literature review informed the clinically-validated functions developed in this work. Software packages were developed and open-sourced through the Python Package Index (P...
Page(s): 263 - 266
Date of Publication: 18 August 2021
Electronic ISSN: 2644-1276
PubMed ID: 35402978

Funding Agency:


References

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