Developing an ML-Based Pretest Probability Model of Obstructive CAD in Patients With Stable Chest Pain.

Journal: JACC. Asia
Published Date: May 30, 2025

Abstract

BACKGROUND: Updated pretest probability models (ESC2019, the PTP model supported by the European Society of Cardiology after a pooled analysis; and RF-CL, the risk factor-weighted model) are recommended for initial evaluation of patients with stable chest pain before coronary computed tomography angiography to reduce unnecessary examination by recent guidelines. However, the reliability of those pretest probability models has not been fully investigated, especially in Chinese population.

Authors

  • Guanhua Dou
    Senior Department of Cardiology, Sixth Medical Center of Chinese PLA General Hospital, Beijing, China; Department of Cardiology, Second Medical Center and National Clinical Research Center for Geriatric Diseases of Chinese PLA General Hospital, Beijing, China.
  • Jia Zhou
  • Ziqiang Guo
    Key Laboratory of Intelligent Computing & Signal Processing of Ministry of Education, School of Computer Science and Technology, Anhui University, 111 Jiulong Road, 230601, Anhui, China.
  • Dongkai Shan
    Senior Department of Cardiology, Sixth Medical Center of Chinese PLA General Hospital, Beijing, China.
  • Xi Wang
    School of Information, Central University of Finance and Economics, Beijing, China.
  • Tao Li
    Department of Emergency Medicine, Jining No.1 People's Hospital, Jining, China.
  • Xinghua Zhang
    Radiology Department, Chinese PLA General Hospital, 28th Fuxing Road, Haidian District, Beijing, 100853, China.
  • Lei Xu
    Key Laboratory of Biomedical Information Engineering of the Ministry of Education, Department of Biomedical Engineering, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China.
  • Mei Zhang
    Clinical and Research Center for Infectious Diseases, Beijing Youan Hospital, Capital Medical University, Beijing, China.
  • Xudong Lv
    School of Instrumentation Science and Engineering, Harbin Institute of Technology, Harbin 150001, China.
  • Junjie Yang
    School of Automation Science and Engineering, Xian Jiaotong University, Xi'an, Shaanxi, China.
  • Yundai Chen
    Department of Pulmonary Vessel and Thrombotic Disease, Sixth Medical Center, Chinese PLA General Hospital, Beijing, China.

Keywords

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