Mr. Jinghao Cai Profile

Jinghao Cai

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Proceedings Article | 11 September 2024 Open Access

Analysis of continuous glucose monitoring data in patients with type 2 diabetes mellitus based on entropy analysis

Yiming Sun, Rui Tao, Yaxin Wang, Jinghao Cai, Hongru Li, Jian Zhou, Xia Yu

Proceedings Volume 13270, 132701C (2024) https://doi.org/10.1117/12.3045353

KEYWORDS: Glucose, Correlation coefficients, Blood, Statistical analysis, Education and training, Data analysis, Data modeling, Clinical practice, Sensors, Reflection

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Objective: The effectiveness of an analysis system of a continuous glucose monitoring (CGM) in the management of Type 2 Diabetes Mellitus (T2DM), focusing on the quality of glycemic control via sophisticated time series analysis. Methods: Approximate entropy (ApEn) and other entropies were used for analysis in the post hoc analysis of 858 subjects with T2MD. Spearman's correlation coefficient was calculated between entropy values and selected physiologic indicators to verify the possible clinical validity of these indicators. Main results: The application of entropy analysis enhanced the quantification of glycemic control complexity. Correlation for glycated hemoglobin A1c (HbA1c), glycated albumin (GA) was demonstrated with ApEn: −0.40, and −0.39, while the correlation coefficient for sample entropy (SampEn) was −0.29, and −0.26, respectively (all P < 0.001). These large negative correlations confirmed the validity of entropy measures in interpreting CGM data. Correlation analysis between entropy measures and metrics such as HbA1c highlighted the potential of this approach to provide insights into diabetes management. Conclusions: The use of entropy analysis has theoretically enriched the methodology for analyzing CGM measurements and provided a valuable tool for clinical practice. The method improves the management of glycemic control among patients with diabetes, potentially influencing personalized treatment strategies and improving overall diabetes care.

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