Byeon H. Future of diabetic foot risk: Unveiling predictive continuous glucose monitoring biomarkers. World J Diabetes 2025; 16(6): 107006 [DOI: 10.4239/wjd.v16.i6.107006]
Corresponding Author of This Article
Haewon Byeon, PhD, Associate Professor, Director, Worker's Care & Digital Health Lab, Department of Future Technology, Korea University of Technology and Education, 1600 Chungjeol-ro, Cheonan 31253, South Korea. bhwpuma@naver.com
Research Domain of This Article
Endocrinology & Metabolism
Article-Type of This Article
Editorial
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Haewon Byeon, Worker's Care & Digital Health Lab, Department of Future Technology, Korea University of Technology and Education, Cheonan 31253, South Korea
Author contributions: Byeon H designed the study, involved in data interpretation, and developed methodology.
Supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, No. NRF-RS-2023-00237287.
Conflict-of-interest statement: No benefits in any form have been received or will be received from a commercial party related directly or indirectly to the subject of this article.
Open Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Haewon Byeon, PhD, Associate Professor, Director, Worker's Care & Digital Health Lab, Department of Future Technology, Korea University of Technology and Education, 1600 Chungjeol-ro, Cheonan 31253, South Korea. bhwpuma@naver.com
Received: March 13, 2025 Revised: April 1, 2025 Accepted: April 10, 2025 Published online: June 15, 2025 Processing time: 92 Days and 23.9 Hours
Abstract
This study critically analyzes the findings of Geng et al, which investigated the association between continuous glucose monitoring (CGM) metrics and the risk of diabetic foot (DF) in individuals with type 2 diabetes mellitus. The study demonstrated significant associations between lower time in range, higher glycemic risk index, mean blood glucose, and time above range and an increased risk of DF. While acknowledging the study's strengths, such as its large sample size and robust statistical methods, this analysis also highlights its limitations, including its cross-sectional design and reliance on self-reported data. The findings are discussed within the framework of established theories, including the concepts of metabolic memory, the glucocentric paradigm, and the role of inflammation. This analysis emphasizes that a comprehensive approach to glucose management, extending beyond traditional glycated hemoglobin A1c measurements, is crucial for DF risk mitigation. Recognizing the impact of poor adherence and ongoing inflammation, future research should prioritize exploring causal mechanisms, the effectiveness of interventions aimed at improving CGM metrics, and the specific contributions of glucose variability to DF development. In conclusion, these findings strongly support the clinical application of diverse CGM metrics to enhance patient outcomes and effectively manage the risk of DF.
Core Tip: Geng et al's study underscores the predictive power of continuous glucose monitoring (CGM) metrics, particularly the glycemic risk index, for diabetic foot risk in type 2 diabetes mellitus, surpassing traditional glycated hemoglobin A1c measures. The study calls for future research to validate these findings and explore CGM's role in clinical practice.
