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Publication Name World Journal of Diabetes
Manuscript ID 119604
DOI 10.4239/wjd.119604
Country China
Category Endocrinology & Metabolism
Manuscript Type Clinical Trials Study
Article Title Metabolic feature-based clustering for subtype identification and longitudinal outcome predictions in the Chinese prediabetic population
Manuscript Source Unsolicited Manuscript
All Author List Shu-Han Zhang, Jin-Ping Zhang, Lu-Lu Song, Li-Li Wu, Zhao-Qin Li, Yi-Fan He, Rui-Fen Deng, Wan-Lu Ma, Cong Zhang, Bo Zhang and Li-Ping Yu
Funding Agency and Grant Number
Funding Agency Grant Number
National High Level Hospital Clinical Research Funding 2025-NHLHCRF-JBGS-B-WZ-01
National Key Research and Development Program of China 2018YFC1313902
Corresponding Author Bo Zhang, MD, Professor, Department of Endocrinology, China-Japan Friendship Hospital, No. 2 Yinghua East Street, Chaoyang District, Beijing 100029, China. zhangbo@zryhyy.com.cn
Key Words Prediabetes; Metabolic subtypes; Longitudinal outcomes; Lifestyle intervention; Risk stratification
Core Tip Using unsupervised k-means clustering of core metabolic features, we identified four clinically meaningful prediabetes subtypes: Mild obesity-related dysmetabolism, mild age-related dysmetabolism, severe insulin resistance, and severe insulin deficiency. Among them, mild obesity-related dysmetabolism showed a clear metabolic advantage over mild age-related dysmetabolism, with a lower risk of progression to diabetes and a greater chance of reverting to normal glucose tolerance. Although enhanced lifestyle management was associated with reduced progression risk, metabolic subtype membership, not intervention exposure, was the main driver of outcome heterogeneity, highlighting its value for baseline risk stratification and precision prevention.
Citation Zhang SH, Zhang JP, Song LL, Wu LL, Li ZQ, He YF, Deng RF, Ma WL, Zhang C, Zhang B, Yu LP. Metabolic feature-based clustering for subtype identification and longitudinal outcome predictions in the Chinese prediabetic population. World J Diabetes 2026; In press
Received
2026-02-07 02:52
Peer-Review Started
2026-02-10 00:01
First Decision by Editorial Office Director
2026-02-25 07:49
Return for Revision
2026-02-25 07:49
Revised
2026-03-13 01:37
Publication Fee Transferred
2026-03-15 08:56
Second Decision by Editor
2026-06-01 02:34
Second Decision by Editor-in-Chief
Final Decision by Editorial Office Director
2026-06-03 09:08
Articles in Press
2026-06-03 09:08
Edit the Manuscript by Language Editor
Typeset the Manuscript
ISSN 1948-9358 (online)
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: http://creativecommons.org/Licenses/by-nc/4.0/
Copyright ©Author(s) (or their employer(s)) 2026. No commercial re-use. See Permissions. Published by Baishideng Publishing Group Inc.
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