Establishment of a predictive model for postpartum hemorrhage in twins: a retrospective study

Abstract

Objective To explore the risk factors and develop a predictive model for postpartum hemorrhage in twin pregnancies. Methods This retrospective cohort study included 2,045 patients who met the inclusion criteria for inpatient deliveries at Ningbo Women's and Children's Hospital from January 2018 to August 2022. The patients were randomly divided into training and testing cohorts by 7:3, LASS0 regression screening variables and dichotomous logistic multifactor analysis were applied in R language to determine independent risk factors for postpartum hemorrhage in twin births nomograms were drawn to validate and evaluate the predictive efficacy of the model. Results Multifactorial Logistic regression analysis showed maternal age, assisted reproduction, platelet count, fibrinogen level, albumin level, hypertensive disorders of pregnancy, placenta praevia, number of previous cesarean deliveries, number of previous intrauterine manipulation, and neonatal weight were independent risk factors for postpartum hemorrhage in twin births. The area under curve (AUC) for the training cohort was 0.810 [95%CI (0.781, 0.839)], with a sensitivity of 76.5%, specificity of 71.0%, and positive and negative predictive values of 0.358 and 0.935, respectively, while the AUC for the testing cohorts was 0.821 [95%CI (0.781, 0.860)], with a sensitivity of 80.9%, specificity of 69.49%, and positive predictive value and negative predictive value of 0.426 and 0.929. Conclusion The predictive model can effectively and quantitatively assess the risk of postpartum hemorrhage in twin pregnancies and help clinicians to take personalized preventive measures.