Abstract
OBJECTIVE: To identify the risk factors of postpartum hemorrhage (PPH) in women of advanced maternal age (AMA) undergoing natural childbirth and to develop a nomogram model for PPH risk prediction in this population. METHODS: This study retrospectively collected data from 220 AMA women who had a natural childbirth at the Third Affiliated Hospital of Chengdu Medical College, Chengdu Pidu District People's Hospital between March 2020 and May 2023, forming the training cohort. The cohort was categorized into the PPH group and the non-PPH group based on the occurrence of PPH. Clinical data were compared between the two groups. Univariate and multivariate logistic analyses were employed to identify the factors associated with PPH. A predictive model for the risk of PPH in AMA women was developed, and its predictive accuracy was assessed using calibration curves, receiver operating characteristic (ROC) curves, and decision curve analysis (DCA). Additionally, clinical data from 110 AMA women who had a natural childbirth at our hospital between June 2023 and August 2024 were collected, forming the validation cohort. RESULTS: The overall incidence of PPH was 17.58% (58/330), including 39 from the training cohort, and 19 from the validation cohort. Univariate logistic analysis revealed that age, placenta previa, hypertensive disorder of pregnancy (HDP), fetal macrosomia, uterine atony, and scarred uterus were significant risk factors for PPH in AMA women (all P < 0.05). Multivariate logistic model identified age, placenta previa, HDP, uterine atony, and scarred uterus as independent risk factors for PPH in AMA women (all P < 0.05). Based on these independent risk factors, a nomogram model for predicting PPH in AMA women was developed, demonstrating an area under the ROC curve (AUC) of 0.841 (95% CI: 0.773-0.908) in the training cohort and 0.868 (95% CI: 0.767-0.969) in the validation cohort. The calibration curve analysis indicated that the model's predicted PPH risk in AMA population closely aligned with the actual outcomes, while DCA demonstrated model's significant clinical utility. CONCLUSION: The nomogram prediction model developed in this study effectively estimates the risk of PPH in AMA women, offering valuable clinical guidance.