Copyright: ©Author(s) 2026. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial (CC BY-NC 4.0) license. No commercial re-use. See permissions. Published by Baishideng Publishing Group Inc.
World J Diabetes. Jul 15, 2026; 17(7): 120647
Published online Jul 15, 2026. doi: 10.4239/wjd.120647
Published online Jul 15, 2026. doi: 10.4239/wjd.120647
Association between the high-sensitivity C-reactive protein-triglyceride-glucose index and metabolic dysfunction-associated steatotic liver disease across different glycemic states
Wen-Hao Zhang, Rong-Dong-Qing Shi, Xian-Ming Li, Gui-Hua Yu, Xin-Yuan Ye, Yu Ding, Si-Hui Luo, Department of Endocrinology and Metabolism, The First Affiliated Hospital of University of Science and Technology of China, University of Science and Technology of China, Hefei 230001, Anhui Province, China
Wen-Hao Zhang, Rong-Dong-Qing Shi, Xian-Ming Li, Gui-Hua Yu, Xin-Yuan Ye, Yu Ding, Si-Hui Luo, Anhui Provincial Key Laboratory of Metabolic Health and Panvascular Diseases, Hefei 230001, Anhui Province, China
Kui Chen, Health Management Medicine Center, The Third Xiangya Hospital, Central South University, Changsha 410013, Hunan Province, China
Kui Chen, State Key Laboratory of Ultrasound in Medicine and Engineering, College of Biomedical Engineering, Chongqing Medical University, Chongqing, 400016, China
Qing Xu, Graduate School, Bengbu Medical University, Bengbu 233030, Anhui Province, China
Co-first authors: Wen-Hao Zhang and Rong-Dong-Qing Shi.
Co-corresponding authors: Yu Ding and Si-Hui Luo.
Author contributions: Zhang WH and Shi RDQ contributed equally to the manuscript as co-first authors; Ding Y and Luo SH contributed equally to the manuscript as co-corresponding authors; Zhang WH contributed to study conceptualization, methodology, data analysis, data interpretation and visualization, wrote, and revised the manuscript; Shi RDQ reviewed the manuscript, and contributed to methodology, data analysis and data interpretation; Chen K contributed to data collection, reviewed and revised the manuscript; Li XM, Yu GH, Ye XY, and Xu Q provided insightful comments on the interpretation of the data, and the structure and revision of the manuscript; Ding Y contributed to study conceptualization, administrative support, data interpretation, reviewed and revised the manuscript; Luo SH contributed to study conceptualization, administrative support, fund acquisition, data interpretation, reviewed and revised the manuscript; and the corresponding authors attest that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted.
AI contribution statement: No part of the main text of the manuscript or the response to reviewers was Al-generated. The study rationale, methodology, data analysis, results, interpretation, and conclusions were independently developed, written, reviewed, and approved by the authors. No AI tool was used for language polishing, translation, data analysis, or writing assistance. The authors take full responsibility for the accuracy, integrity, originality, and scientific validity of all content in the manuscript and the response to reviewers.
Supported by National Natural Science Foundation of China, No. 82300904 and No. 82100857.
Institutional review board statement: The studies were reviewed and approved by the Institutional Review Board of the First Affiliated Hospital of University of Science and Technology of China (Approval No: 2021 KY-034) and conformed to the guidelines of the Helsinki declaration and its later amendments or comparable ethical standards.
Informed consent statement: Written informed consent was obtained from all participants.
Conflict-of-interest statement: All authors declare that they have no conflicts of interest related to this work.
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: The data supporting this study are available from the corresponding author upon reasonable request, subject to privacy and ethical restrictions.
Corresponding author: Si-Hui Luo, MD, Department of Endocrinology and Metabolism, The First Affiliated Hospital of University of Science and Technology of China, University of Science and Technology of China, No. 17 Lujiang Road, Hefei 230001, Anhui Province, China. luosihui@ustc.edu.cn
Received: March 5, 2026
Revised: April 9, 2026
Accepted: June 9, 2026
Published online: July 15, 2026
Processing time: 127 Days and 2.1 Hours
Revised: April 9, 2026
Accepted: June 9, 2026
Published online: July 15, 2026
Processing time: 127 Days and 2.1 Hours
Core Tip
Core Tip: This large cross-sectional study (n = 7413) evaluated the high-sensitivity C-reactive protein-triglyceride-glucose index (CTI) as a non-invasive biomarker for metabolic dysfunction-associated steatotic liver disease (MASLD) across glycemic states. The CTI showed robust diagnostic performance (area under the curve: 0.808) with strongest predictive value in normal glucose regulation (adjusted OR = 3.07) and prediabetes (OR = 3.26), but weaker association in diabetes (OR = 1.58). Optimal CTI thresholds increased progressively from normoglycemia to diabetes (8.596, 8.908, 9.456, respectively). These findings suggest CTI is a practical biomarker for early MASLD risk identification, particularly in individuals without overt diabetes.