Identification of a Susceptible and High-Risk Population for Postoperative Systemic Inflammatory Response Syndrome in Older Adults: Machine Learning-Based Predictive Model.

Journal: Journal of medical Internet research
PMID: 39501984

Abstract

BACKGROUND: Systemic inflammatory response syndrome (SIRS) is a serious postoperative complication among older adult surgical patients that frequently develops into sepsis or even death. Notably, the incidences of SIRS and sepsis steadily increase with age. It is important to identify the risk of postoperative SIRS for older adult patients at a sufficiently early stage, which would allow preemptive individualized enhanced therapy to be conducted to improve the prognosis of older adult patients. In recent years, machine learning (ML) models have been deployed by researchers for many tasks, including disease prediction and risk stratification, exhibiting good application potential.

Authors

  • Haiyan Mai
    Department of Pharmacy, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
  • Yaxin Lu
    Department of Big Data and Artificial Intelligence, the Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong, People's Republic of China.
  • Yu Fu
    Molecular Diagnosis and Treatment Center for Infectious Diseases Dermatology Hospital Southern Medical University Guangzhou China.
  • Tongsen Luo
    Department of Anesthesiology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
  • Xiaoyue Li
    College of Life Science and Engineering, Lanzhou University of TechnologyLanzhou 730050, P. R. China; The Key Lab of Screening, Evaluation and Advanced Processing of TCM and Tibetan Medicine, Education Department of Gansu Provincial GovernmentLanzhou 730050, P. R. China.
  • Yihan Zhang
    Department of Ophthalmology, Fudan Eye & ENT Hospital, Shanghai, China.
  • Zifeng Liu
    Shandong Yankuang Group Changlong Cable Manufacturing Co., Ltd, Jining, China.
  • Yuenong Zhang
    Department of Surgery and Anesthesia, The Third Affiliated Hospital of Sun Yat-sen University Yuedong Hospital, Meizhou, China.
  • Shaoli Zhou
    Department of Anesthesiology, The Third Affiliated Hospital of Sun Yat-Sen University, No. 600 Tianhe Road, Guangzhou, 10630, Guangdong, People's Republic of China. 13610272308@139.com.
  • Chaojin Chen
    Department of Anesthesiology, The Third Affiliated Hospital of Sun Yat-Sen University, No. 600 Tianhe Road, Guangzhou, 10630, Guangdong, People's Republic of China.

Keywords

External Resources

Popular Topics
Recent Journals