Risk Factors and Predictive Models for Postpartum Hemorrhage after Vaginal Delivery

Abstract

Background: Postpartum hemorrhage (PPH) remains one of the biggest reasons of maternal morbidity and mortality. Clinical prediction of PPH remains challenging, particularly in the case of a vaginal birth. The purpose of this research is identifying patients at risk for PPH in vaginal delivery by using risk factors and predictive models. Methods: 1840 cases who underwent vaginal deliveries at Beijing Ditan Hospital, Capital Medical University between December 2020 to December 2022, which were divided into two groups based on the amount of blood loss (PPH and non-PPH groups). Fourteen risk factors could cause increased risk of PPH, including demographic characteristics and placental anomalies factors. Logistic regression analysis was used to influence the risk factors of PPH in vaginal delivery. According to the results of multivariate logistic regression analysis, a risk prediction model was established, the Hosmer-Lemeshow test was used to assess the model fit. Results: A total of 94 cases presented with PPH in this study, and the incidence of PPH was 5.10% (94/1840). Two items including macrosomia (odds ratio (OR): 2.229, 95% confidence interval (95% CI): 1.062–4.679) and placental anomalies (OR: 4.095, 95% CI: 2.488–6.742) were independent risk factors affecting the occurrence of PPH with vaginal delivery (p < 0.05). Conclusion: The construction of a logistic regression-based model can be used to predict the risk of PPH after vaginal delivery, predictability to be studied further. Clinically, more attention should be paid to vaginal delivery, early identification and screening of high-risk factors for PPH, as well as timely preventive interventions for high-risk groups so as to reduce the risk of PPH.