A machine learning model for prenatal risk prediction of cephalopelvic disproportion-related dystocia: A retrospective study.

Journal: International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
Published Date: Apr 2, 2025

Abstract

OBJECTIVE: To develop a prenatal risk prediction model for cephalopelvic disproportion (CPD)-related dystocia. This model aims to complement obstetricians' empirical judgments by identifying high-risk CPD-related dystocia cases within populations deemed low-risk prenatally.

Authors

  • Su Zhang
  • Hong-Juan Jiang
    Center for Clinical Pharmacy, Cancer Center, Department of Pharmacy, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, Zhejiang, China.
  • Su-Xiao Liu
    Center for Reproductive Medicine, Department of Obstetrics, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, Zhejiang, China.
  • Yan-Ru Wang
    Center for Reproductive Medicine, Department of Pediatrics, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, Zhejiang, China.
  • Liu-Cheng Li
    Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
  • Hai-Hui Zhou
    Center for Reproductive Medicine, Department of Obstetrics, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, Zhejiang, China.
  • Ping Huang
    Division of HIV/AIDS Prevention, Centers for Disease Control and Prevention, Atlanta, GA, USA.
  • Xiu-Li Yang
    Center for Clinical Pharmacy, Cancer Center, Department of Pharmacy, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, Zhejiang, China.
  • Wei-Qi Xia
    Center for Clinical Pharmacy, Cancer Center, Department of Pharmacy, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, Zhejiang, China.

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