Machine learning-driven prediction of readmission risk in heart failure patients with diabetes: synergistic assessment of inflammatory and metabolic biomarkers.

Journal: International journal of cardiology
Published Date: Aug 8, 2025

Abstract

BACKGROUND: Heart failure (HF) and diabetes mellitus (DM) frequently coexist, exacerbating disease progression and increasing hospital readmission risk. Accurate prediction of readmission in HF patients with DM remains a clinical challenge. This study aims to develop and validate a machine learning (ML)-based model incorporating inflammatory and metabolic biomarkers to enhance risk stratification.

Authors

  • Yue Hu
    Department of Biobank, China-Japan Union Hospital of Jilin University, Changchun, China.
  • Yunhong Zhang
    School of Computer Science, Nanjing University of Information Science and Technology, Nanjing 210044, China.
  • Ping Han
  • Yanqing Pan
    Department of Cardiology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, Jiangsu, China.
  • Juanjuan Liu
    Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, 110004, People's Republic of China.
  • Yangni Li
    Department of General Practice, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
  • Defeng Pan
    Department of Cardiology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, Jiangsu 221004, China.
  • Jingjing Ren

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