Primary prevention cardiovascular disease risk prediction model for contemporary Chinese (1°P-CARDIAC): Model derivation and validation using a hybrid statistical and machine-learning approach.

Journal: PloS one
Published Date: Jul 28, 2025

Abstract

BACKGROUND: Cardiovascular disease (CVD) is the leading cause of mortality and morbidity in China and worldwide while we are lacking in validated primary prevention model specifically for Chinese. To identify CVD high-risk individuals for early intervention, we created and validated a primary prevention risk prediction model, Personalized CARdiovascular DIsease risk Assessment for Chinese (1°P-CARDIAC), in contemporary Chinese cohorts in Hong Kong.

Authors

  • Yekai Zhou
    School of Computing and Data Science, The University of Hong Kong, Hong Kong Special Administration Region, China.
  • Celia Jiaxi Lin
    School of Nursing, The University of Hong Kong, Hong Kong Special Administration Region, China.
  • Qiuyan Yu
    Plant and Environmental Sciences New Mexico State University Las Cruces New Mexico USA.
  • Joseph Edgar Blais
    Centre for Safe Medication Practice and Research, Department of Pharmacology and Pharmacy, The University of Hong Kong, Hong Kong Special Administration Region, China.
  • Eric Yuk Fai Wan
    Department of Family Medicine and Primary Care, The University of Hong Kong, Hong Kong, China.
  • Emmanuel Wong
    Department of Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administration Region, China.
  • Kathryn Tan
    Department of Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administration Region, China.
  • David Chung-Wah Siu
    Department of Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administration Region, China.
  • Kai Hang Yiu
    Department of Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administration Region, China.
  • Esther Wai Yin Chan
    Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China (Hong Kong).
  • Doris Yu
    School of Nursing, The University of Hong Kong, Hong Kong Special Administration Region, China.
  • William Wong
    Department of Radiation Oncology, Mayo Clinic in Arizona, Phoenix, Arizona.
  • Tak-Wah Lam
    Department of Computer Science, The University of Hong Kong, Hong Kong, 999077, China.
  • Ian Chi Kei Wong
    Department of Pharmacology and Pharmacy, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China (Hong Kong).
  • Ruibang Luo
    Department of Computer Science, The University of Hong Kong, Hong Kong, 999077, China. rbluo@cs.hku.hk.
  • Celine S L Chui
    Laboratory of Data Discovery for Health (D24H), Hong Kong Science Park, Hong Kong Science and Technology Park, Hong Kong Special Administration Region, China.

Keywords

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