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World J Diabetes. Aug 15, 2026; 17(8): 121173
Published online Aug 15, 2026. doi: 10.4239/wjd.121173
Published online Aug 15, 2026. doi: 10.4239/wjd.121173
Risk stratification model for diabetic kidney disease progression based on metabolic and inflammatory biomarkers
Ni Du, Jun Wang, Department of Nephrology, Chongqing University Three Gorges Hospital, Chongqing 404010, China
Wen-Xia Li, Department of Endocrinology, Jiangmen Central Hospital, Jiangmen 529000, Guangdong Province, China
Chuang-Ye Qiu, Department of Nephrology, Jiangmen Central Hospital, Jiangmen 529000, Guangdong Province, China
Co-first authors: Ni Du and Wen-Xia Li.
Co-corresponding authors: Chuang-Ye Qiu and Jun Wang.
Author contributions: Du N and Li WX contributed equally to study design, data collection, and manuscript drafting as co-first authors; Qiu CY and Wang J supervised the study, provided critical revisions, and approved the final manuscript as co-corresponding authors; all authors read and approved the published version.
AI contribution statement: No AI tools were used at any stage of manuscript preparation. The authors assume full responsibility for the integrity and scientific validity of this work.
Supported by the Chongqing Wanzhou District Science and Health Joint Medical Research Project, No. wzwjw-kw2024015; and Science and Technology Plan Project in the Medical and Health Field of Jiangmen City, No. 2022YL01040.
Institutional review board statement: This study was approved by the Ethics Committee of Chongqing University Three Gorges Hospital (No. 2026-33) in accordance with the Declaration of Helsinki.
Informed consent statement: Written informed consent was waived by the Ethics Committee of Chongqing University Three Gorges Hospital (No. 2026-33) owing to the retrospective design and the exclusive use of anonymized clinical data.
Conflict-of-interest statement: All authors declare no conflict of interest in publishing the manuscript.
STROBE statement: The authors have read the STROBE Statement – checklist of items, and the manuscript was prepared and revised according to the STROBE Statement – checklist of items.
Data sharing statement: De-identified data are available from the corresponding author (18290529622@163.com) upon reasonable request and subject to institutional approval.
Corresponding author: Jun Wang, MD, Department of Nephrology, Chongqing University Three Gorges Hospital, No. 165 Xincheng Road, Wanzhou District, Chongqing 404010, China. 18290529622@163.com
Received: March 20, 2026
Revised: June 5, 2026
Accepted: July 14, 2026
Published online: August 15, 2026
Processing time: 138 Days and 13.9 Hours
Revised: June 5, 2026
Accepted: July 14, 2026
Published online: August 15, 2026
Processing time: 138 Days and 13.9 Hours
Core Tip
Core Tip: This study proposed an innovative risk stratification model for diabetes kidney disease progression by combining metabolic and inflammatory biomarkers with renal parameters. A nomogram-based model was a good predictive tool and stratified patients into three groups: (1) Low-risk for progression; (2) Moderate-risk for progression; and (3) High-risk for progression. This readily applicable clinical model could help identify patients eligible for early intervention, tailoring treatment schemes based on their individual risk of progression and therefore reduce the burden of end-stage renal disease in high prevalence diabetes populations.