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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. Jun 15, 2026; 17(6): 115861
Published online Jun 15, 2026. doi: 10.4239/wjd.115861
Risk factors for carotid plaque in type 2 diabetes mellitus: The need for more extensive data
Xing-Yun Yang, Jia-Hui Zhao, Shi-Song Wang, Cun-Yi Zou
Xing-Yun Yang, Jia-Hui Zhao, Shi-Song Wang, Cun-Yi Zou, Department of Neurosurgery, The First Hospital of China Medical University, Shenyang 110001, Liaoning Province, China
Co-first authors: Xing-Yun Yang and Jia-Hui Zhao.
Author contributions: Yang XY and Zhao JH played important and indispensable roles in manuscript preparation as co-first authors; Yang XY, Zhao JH and Wang SS wrote the original draft; Zou CY contributed to manuscript conceptualization, writing, reviewing, and editing; all authors have read and approved the final version of the manuscript.
Supported by Natural Science Foundation of Liaoning Province, No. 2023-MSLH-401.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Corresponding author: Cun-Yi Zou, MD, Department of Neurosurgery, The First Hospital of China Medical University, No. 155 Nanjing Street, Shenyang 110001, Liaoning Province, China. cnzoucunyi@126.com
Received: October 30, 2025
Revised: November 21, 2025
Accepted: December 18, 2025
Published online: June 15, 2026
Processing time: 224 Days and 8.1 Hours
Core Tip

Core Tip: The precise risk factors for carotid plaque in patients with type 2 diabetes mellitus have not been clearly defined. A recent study has highlighted age, body mass index, fasting plasma glucose, glycated hemoglobin, serum creatinine, urinary albumin‑to‑creatinine ratio, and serum uric acid as key contributors to carotid atherosclerosis in this population. However, the study carries certain methodological limitations. To improve the robustness of these findings, future prospective multicenter research should incorporate diabetes duration and a full medical history. Additional use of machine learning techniques could further elucidate causal pathways and improve cerebrovascular risk stratification in individuals with type 2 diabetes mellitus.

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