Biological signatures and prediction of an immunosuppressive status-persistent critical illness-among orthopedic trauma patients using machine learning techniques.

Journal: Frontiers in immunology
PMID: 36325351

Abstract

BACKGROUND: Persistent critical illness (PerCI) is an immunosuppressive status. The underlying pathophysiology driving PerCI remains incompletely understood. The objectives of the study were to identify the biological signature of PerCI development, and to construct a reliable prediction model for patients who had suffered orthopedic trauma using machine learning techniques.

Authors

  • Mingxing Lei
    Department of Orthopedic Surgery, Hainan Hospital of Chinese People's Liberation Army (PLA) General Hospital, Sanya, China.
  • Zhencan Han
    Xiangya School of Medicine, Central South University, Changsha, China.
  • Shengjie Wang
    Department of Orthopedic Surgery, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University, Shanghai, China.
  • Chunxue Guo
    Department of Biostatistics, Hengpu Yinuo (Beijing) Technology Co., Ltd, Beijing, China.
  • Xianlong Zhang
    Department of Orthopaedics, Shanghai Jiaotong University Affiliated Shanghai Sixth People's Hospital, Shanghai, 200233, P.R.China.
  • Ya Song
    Department of Orthopedic, Xiangya Hospital of Central South University, Changsha, China.
  • Feng Lin
    Radiology Department, The People's Hospital of Lezhi, Ziyang, Sichuan, China.
  • Tianlong Huang
    Department of Orthopedic Surgery, The Second Xiangya Hospital of Central South University, Changsha, China.

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