Predicting high-risk factors for postoperative inadequate analgesia and adverse reactions in cesarean delivery surgery: a prospective study.

Journal: International journal of surgery (London, England)
Published Date: Apr 3, 2025

Abstract

BACKGROUND: Early identification of high-risk factors for inadequate analgesia and adverse reactions in obstetric patients is critical for improving outcomes. This study developed a machine learning model to predict these factors and optimize anesthesia management in obstetric surgery.

Authors

  • Kaiwen Zhang
    Department of Anesthesiology and Pain Medicine, Hubei Key Laboratory of Geriatric Anesthesia and Perioperative Brain Health, and Wuhan Clinical Research Center for Geriatric Anesthesia, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People's Republic of China.
  • Bo Jiao
  • Jiaoli Sun
  • Xianwei Zhang
    Department of Pharmacology, University of California, Davis, California, USA.
  • Guanglei Zhang
    Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University, Beijing, 100191, China; School of Biological Science and Medical Engineering, Beihang University, Beijing, 100191, China. Electronic address: guangleizhang@buaa.edu.cn.
  • Ningbo Li
  • Baowen Liu
  • 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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