A nomogram for predicting postpartum post-traumatic stress disorder: a prospective cohort study.

BACKGROUND

Postpartumpost-traumatic stress disorder (PTSD), as a psychological stress disorder, has long-term and widespread harm. Still, compared with other postpartum psychiatric disorders, postpartum PTSD has received relatively littleattention in China. This study aims to investigate the risk factors of postpartum PTSD and to develop a convenient and rapid nomogram screening tool to help clinical staff identify high-risk pregnant womenin time and take preventative and management measures.

METHODS

Recruited pregnant women hospitalized for delivery in Qingdao Municipal Hospital and Jinzhou Maternal and Child Health Hospital from November 2022 to October 2023 as convenient samples for the questionnaire survey. Telephone follow-up was conducted 42 days after delivery. After univariate analysis, multicollinearity analysis, and logistic regression analysis, the risk factors of postnatal PTSD were obtained, a prediction model was established, and a nomogram was drawn by R software. G*power3.1.9.7 calculated the effectiveness of the test. The model was validated internally using the Bootstrap approach, and external validation was carried out using a verification group. The accuracy of the model's predictions and its clinical application value were evaluated by the area under the curve, calibration plot, and decision curve analysis.

RESULTS

A total of 602 women were recruited in this study, and the incidence of postpartum PTSD was 11.1% (67/602). Multifactorial logistic regression analysis showed that poor self-assessment of sleep status in late pregnancy (OR = 5.336), cesarean section (OR = 2.825), instrumental delivery (OR = 5.994), having fear of labor (OR = 4.857), and a high score of Five Factors Inventory Neuroticism subscale (OR = 1.244) were independent risk factors for developing postpartum PTSD. A high Quality of Relationship Index score (OR = 0.891) was a protective factor for postpartum PTSD. In the training and validation sets, the nomogram model's area under the ROC curve was 0.928 and 0.907, respectively. The calibration curves showed that the nomogram model was well-fitted, and the Decision Curve Analysis indicated that the nomogram model had good value for clinical application.

CONCLUSIONS

With its strong predictive capacity, the prediction model built using postpartum PTSD risk factors can help clinical caregivers identify high-risk pregnant women early on and implement timely preventive intervention strategies.