Development of interpretable machine learning models for prediction of acute kidney injury after noncardiac surgery: a retrospective cohort study.

Journal: International journal of surgery (London, England)
PMID: 38445452

Abstract

BACKGROUND: Early identification of patients at high-risk of postoperative acute kidney injury (AKI) can facilitate the development of preventive approaches. This study aimed to develop prediction models for postoperative AKI in noncardiac surgery using machine learning algorithms. The authors also evaluated the predictive performance of models that included only preoperative variables or only important predictors.

Authors

  • Rao Sun
    Department of Anesthesiology and Pain Medicine, Hubei Key Laboratory of Geriatric Anesthesia and Perioperative Brain Health, and Wuhan Clinical Research Center for Geriatric Anesthesia.
  • Shiyong Li
    Department of Anesthesiology and Pain Medicine, Hubei Key Laboratory of Geriatric Anesthesia and Perioperative Brain Health, and Wuhan Clinical Research Center for Geriatric Anesthesia.
  • Yuna Wei
    Yidu Cloud Technology Inc, Beijing, People's Republic of China.
  • Liu Hu
    Health Management Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei.
  • Qiaoqiao Xu
    Department of Anesthesiology and Pain Medicine, Hubei Key Laboratory of Geriatric Anesthesia and Perioperative Brain Health, and Wuhan Clinical Research Center for Geriatric Anesthesia.
  • Gaofeng Zhan
    Department of Anesthesiology and Pain Medicine, Hubei Key Laboratory of Geriatric Anesthesia and Perioperative Brain Health, and Wuhan Clinical Research Center for Geriatric Anesthesia.
  • Xu Yan
    Dept of Electrical and Computer Engineering, University of California, Los Angeles, CA, 90024, United States.
  • Yuqin He
    Department of Anesthesiology and Pain Medicine, Hubei Key Laboratory of Geriatric Anesthesia and Perioperative Brain Health, and Wuhan Clinical Research Center for Geriatric Anesthesia.
  • Yao Wang
    Department of Gastrointestinal Surgery, Zhongshan People's Hospital, Zhongshan, Guangdong, China.
  • Xinhua Li
    Department of Infectious Disease, The Third Affiliated Hospital of Sun Yat-sen University No. 600, Tianhe Road, Guangzhou 510630, China.
  • Ailin Luo
    Department of Anesthesiology and Pain Medicine, Hubei Key Laboratory of Geriatric Anesthesia and Perioperative Brain Health, and Wuhan Clinical Research Center for Geriatric Anesthesia.
  • Zhiqiang Zhou
    Department of Anesthesiology and Pain Medicine, Hubei Key Laboratory of Geriatric Anesthesia and Perioperative Brain Health, and Wuhan Clinical Research Center for Geriatric Anesthesia.

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