Development and validation of a machine learning model for predicting vulnerable carotid plaques using routine blood biomarkers and derived indicators: insights into sex-related risk patterns.

Journal: Cardiovascular diabetology
Published Date: Aug 10, 2025

Abstract

BACKGROUND: Early detection of vulnerable carotid plaques is critical for stroke prevention. This study aimed to develop a machine learning model based on routine blood tests and derived indices to predict plaque vulnerability and assess sex-specific risk patterns across biomarker value ranges.

Authors

  • Yimin E
    Department of Vascular Surgery, Suzhou Municipal Hospital, The Affiliated Suzhou Hospital of Nanjing Medical University, Gusu School, Nanjing Medical University, No. 26 Daoqian Street, Jiangsu, Suzhou, China.
  • Zhichao Yao
    Department of Vascular Surgery, Suzhou Municipal Hospital, The Affiliated Suzhou Hospital of Nanjing Medical University, Gusu School, Nanjing Medical University, No. 26 Daoqian Street, Jiangsu, Suzhou, China.
  • Maolin Ge
    Department of Endocrinology, Nanjing Luhe People's Hospital, Yangzhou University, Nanjing, Jiangsu, China.
  • Guijun Huo
    Department of Vascular Surgery, Suzhou Municipal Hospital, The Affiliated Suzhou Hospital of Nanjing Medical University, Gusu School, Nanjing Medical University, No. 26 Daoqian Street, Jiangsu, Suzhou, China.
  • Jian Huang
    Center for Informational Biology, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave, West Hi-Tech Zone, Chengdu 611731, P. R. China.
  • Yao Tang
  • Zhanao Liu
    Department of Vascular Surgery, Suzhou Municipal Hospital, The Affiliated Suzhou Hospital of Nanjing Medical University, Gusu School, Nanjing Medical University, No. 26 Daoqian Street, Jiangsu, Suzhou, China.
  • Ziyi Tan
    Department of Vascular Surgery, Suzhou Municipal Hospital, The Affiliated Suzhou Hospital of Nanjing Medical University, Gusu School, Nanjing Medical University, No. 26 Daoqian Street, Jiangsu, Suzhou, China.
  • Yuqi Zeng
    Department of Vascular Surgery, Suzhou Municipal Hospital, The Affiliated Suzhou Hospital of Nanjing Medical University, Gusu School, Nanjing Medical University, No. 26 Daoqian Street, Jiangsu, Suzhou, China.
  • Junjie Cao
    Rocket Force University of Engineering, Xi'an, 710025, P. R. China.
  • Dayong Zhou
    Department of Vascular Surgery, Suzhou Municipal Hospital, The Affiliated Suzhou Hospital of Nanjing Medical University, Gusu School, Nanjing Medical University, No. 26 Daoqian Street, Jiangsu, Suzhou, China. zhoudy@njmu.edu.cn.

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