Development and validation of machine learning models for predicting post-cesarean pain and individualized pain management strategies: a multicenter study.

Journal: BMC anesthesiology
PMID: 40211131

Abstract

BACKGROUND: Effective management of postoperative pain remains a significant challenge in obstetric care due to the variability in pain perception and response influenced by physical, medical, and psychosocial factors. Current standardized pain management protocols often fail to accommodate this variability, necessitating more tailored approaches.

Authors

  • Shenjuan Lv
    Department of Anesthesiology, Jinan Second Maternal and Child Health Hospital, Shandong, China.
  • Ning Sun
    State Key Laboratory of Chirosciences and Department of Applied Biology and Chemical Technology, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong SAR, China.
  • Chunhui Hao
    Department of Anesthesiology, Jinan Second Maternal and Child Health Hospital, Shandong, China. hch202408@126.com.
  • Junqing Li
    Ultrasound Department, Jinan Second Maternal and Child Health Hospital, Shandong, China.
  • Yun Li
    School of Public Health, University of Michigan, Ann Arbor, MI, USA.

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