Interpretable machine learning analysis of immunoinflammatory biomarkers for predicting CHD among NAFLD patients.

Journal: Cardiovascular diabetology
Published Date: Jul 3, 2025

Abstract

BACKGROUND: Coronary Heart Disease (CHD) and Non-Alcoholic Fatty Liver Disease (NAFLD) share overlapping pathogenic mechanisms including adipose tissue dysfunction, insulin resistance, and systemic inflammation mediated by adipokines. However, the specific impact of inflammation and immune responses on CHD risk in NAFLD patients remains poorly understood. This study evaluated the predictive value of ten immunoinflammatory indexes for CHD risk in NAFLD patients using an interpretable machine learning framework.

Authors

  • Wenyuan Dong
    Vasculocardiology Department, The Third People's Hospital of Datong, Datong, Shanxi, China.
  • Hongcheng Jiang
    Division of Cardiology, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1095, Jiefang Avenue, Wuhan, Hubei, China.
  • Yu Li
    Department of Public Health, Shihezi University School of Medicine, 832000, China.
  • Luo Lv
    Department of Cardiology, The Second Hospital of Shanxi Medical University, 382 Wuyi Road, Taiyuan, 030001, Shanxi, China.
  • Yuxin Gong
    Key Laboratory of Cardiovascular Diseases, Second Hospital of Shanxi Medical University, Taiyuan, Shanxi, China.
  • Bao Li
    Key Laboratory of Cardiovascular Diseases, Second Hospital of Shanxi Medical University, Taiyuan, Shanxi, China.
  • Hongjie Wang
    Department of Equipment, Weihai Maternal and Child Health Hospital, Weihai, China.
  • Hesong Zeng
    Division of Cardiology, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1095, Jiefang Avenue, Wuhan, Hubei, China. zenghs@tjh.tjmu.edu.cn.

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