Postpartum haemorrhage following vaginal delivery: a comprehensive analysis and development of predictive models for aetiological subgroups in Chinese women.

Objectives: This study aimed to dissect the aetiological subgroups of postpartum haemorrhage (PPH) that occur after vaginal delivery in women with full-term singleton pregnancies. Our goal was to craft and validate predictive models to guide clinical decision-making and optimise resource allocation.

Design: A retrospective cohort study.

Setting: Shengjing Hospital of China Medical University, Liaoning Maternal and Child Health Hospital, and Shenyang Women's and Children's Hospital.

Participants: 29 842 women who underwent vaginal delivery were enrolled in the study across three hospitals from 2016 to 2022.

Primary Outcome Measures: PPH, categorised into uterine atony (UA), placental factors (PF), cervical trauma (CT), and coagulation abnormalities (CA) by aetiology.

Results: The logistic regression for overall PPH and UA-PPH showcased high discrimination (AUCs of 0.807 and 0.794, respectively), coupled with commendable calibration and DCA-assessed clinical utility, culminating in the development of a nomogram for risk prediction. The PF-PPH model exhibited a modest AUC of 0.739, while the CT-PPH and CA-PPH models demonstrated suboptimal clinical utility and calibration.

Conclusion: The study identified factors associated with PPH and developed models with good performance for overall PPH and UA-PPH. The nomogram offers a valuable tool for risk prediction. However, models for PF-PPH, CT-PPH, and CA-PPH require further refinement. Future research should focus on larger samples and multicentre validation for enhanced model generalisability.