Development of a risk prediction model for sepsis-related delirium based on multiple machine learning approaches and an online calculator.

Journal: PloS one
Published Date: Jul 16, 2025

Abstract

BACKGROUND: Sepsis-associated delirium (SAD) occurs due to disruptions in neurotransmission linked to inflammatory responses from infections. It poses significant challenges in clinical management and is associated with poor outcomes. Survivors often experience long-term cognitive and behavioral issues that impact their quality of life and place a burden on their families. This study aimed to develop and validate an interpretable machine learning model for early prediction of SAD in critically ill patients. Additionally, we constructed an online risk calculator to facilitate real-time clinical assessment.

Authors

  • Lang Gao
    Department of Critical Care Medicine, Clinical Medical College of Qinghai University, Xi ning, China.
  • Guang Dong Wang
    Department of Respiratory and Critical Care Medicine, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shanxi, China.
  • Xing Yi Yang
    Department of Gastroenterology Disease, XianJu People's Hospital, Zhejiang Southeast Campus of Zhejiang Provincial People's Hospital, Affiliated Xianju's Hospital, Hang zhou Medical College, Xianju, Zhejiang, China.
  • Shi Jun Tong
    Department of Critical Care Medicine, Clinical Medical College of Qinghai University, Xi ning, China.
  • Xu Jie Wang
    Department of Emergency Medicine, Clinical Medical College of Qinghai University, Xi ning, China.
  • Yun Ruo Chen
    Department of Critical Care Medicine, Clinical Medical College of Qinghai University, Xi ning, China.
  • Jin Ying Bai
    Department of Critical Care Medicine, Clinical Medical College of Qinghai University, Xi ning, China.
  • Ya Xin Zhang
    Department of Neurology, Xia men Humanity Hospital, Fujian Medical University, Xia men, Fujian, China.

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