TY - UNPB
T1 - From Data to Insights
T2 - A Tool for Comprehensive Quantification of Continuous Glucose Monitoring (QoCGM)
AU - Cichosz, Simon Lebech
AU - Hangaard, Stine
AU - Kronborg, Thomas
AU - Vestergaard, Peter
AU - Jensen, Morten Hasselstrøm
PY - 2025/1
Y1 - 2025/1
N2 - Continuous Glucose Monitoring (CGM) has become a important technology in the management and research of both type 1 and type 2 diabetes, providing real-time data on glucose fluctuations that were previously inaccessible with traditional monitoring methods. Numerous analytical tools, such as cgmquantify, iglu, GLU, rGV, and CGManalyzer, have been developed for platforms like R and Python to calculate standard metrics and extract insights from CGM data. However, these tools often fail to address the full spectrum of analytical requirements. Furthermore, there is a significant lack of updated, open-source tools tailored for MATLAB, a platform widely used by the research community. To address this gap, we introduce Quantification of Continuous Glucose Monitoring (QoCGM), a comprehensive, open-source analytical tool for CGM data specifically designed for MATLAB. A case study involving 324 individuals with insulin-treated type 2 diabetes mellitus (T2DM) demonstrates the utility of QoCGM, highlighting the distinct aspects of glucose dynamics captured by different CGM derived metrics through an analysis of their coefficients of determination (R^2).
AB - Continuous Glucose Monitoring (CGM) has become a important technology in the management and research of both type 1 and type 2 diabetes, providing real-time data on glucose fluctuations that were previously inaccessible with traditional monitoring methods. Numerous analytical tools, such as cgmquantify, iglu, GLU, rGV, and CGManalyzer, have been developed for platforms like R and Python to calculate standard metrics and extract insights from CGM data. However, these tools often fail to address the full spectrum of analytical requirements. Furthermore, there is a significant lack of updated, open-source tools tailored for MATLAB, a platform widely used by the research community. To address this gap, we introduce Quantification of Continuous Glucose Monitoring (QoCGM), a comprehensive, open-source analytical tool for CGM data specifically designed for MATLAB. A case study involving 324 individuals with insulin-treated type 2 diabetes mellitus (T2DM) demonstrates the utility of QoCGM, highlighting the distinct aspects of glucose dynamics captured by different CGM derived metrics through an analysis of their coefficients of determination (R^2).
KW - endocrinology
U2 - 10.1101/2025.01.01.25319870
DO - 10.1101/2025.01.01.25319870
M3 - Preprint
BT - From Data to Insights
PB - medRxiv
ER -