Development and validation of a risk prediction model for post-traumatic stress disorder in postpartum women based on a prospective cohort study

Objective To construct and validate a risk prediction model for post-traumatic stress disorder (PTSD) in postpartum women based on a prospective cohort study.Methods A total of 1 340 women who delivered at the First Affiliated Hospital of Shandong First Medical University from February to June 2023 were included into a training set. Another 409 pregnant women from Jinan Maternity and Child Health Care Hospital and 311 pregnant women from Department of Obstetrics, Weifang People's Hospital, from June 1 to October 1, 2023 were included into external test sets. According to the presence of PTSD at postpartum 6-8 weeks, the training set was divided into two groups: PTSD (n=127) and non-PTSD (n=1 213). Univariate and multivariate logistic regression analyses were used to identify independent risk factors for PTSD, and a risk prediction model was constructed. The model's performance was evaluated using ROC curve analysis, Hosmer-Lemeshow test, calibration curve, and decision curve analysis.Results The incidence of postpartum PTSD was 9.48% in the training set and 9.58% in the test sets. Multivariate analysis identified independent risk factors, including family average monthly income, prenatal fear of delivery, history of pregnancy complications, delivery method, number of deliveries, postpartum pain intensity, social support level, and anxiety status. The constructed risk prediction model showed good discriminatory ability, calibration, and clinical utility in the training and test sets.Conclusions The model has good predictive efficacy and can be used to identify high-risk postpartum PTSD individuals early at discharge, providing evidence for clinical intervention.