Development and validation of a prediction model for postpartum hemorrhage at a single safety net tertiary care center.

BACKGROUND

Postpartum hemorrhage is a leading cause of pregnancy-related morbidity and mortality; however, there is limited ability to identify women at risk of this obstetrical complication.

OBJECTIVE

This study aimed to develop and validate a prediction model for postpartum hemorrhage based on antenatal and intrapartum risk factors.

STUDY DESIGN

This was a retrospective cohort study of women who delivered between April 2016 and March 2019 at a single safety net hospital. The prevalence of postpartum hemorrhage, defined as blood loss of ≥1000 mL at the time of delivery, was determined, and characteristics were compared between women with and without postpartum hemorrhage. Women were randomly assigned to a prediction or a validation cohort. The selection of predictors to be included in the model was based on known antenatal and intrapartum risk factors for postpartum hemorrhage. A multivariable logistic regression with a backward stepwise approach was used to create a prediction model. Area under the receiver operating characteristic curve and 95% bootstrap confidence intervals were calculated. Using the final model, a single threshold for classifying postpartum hemorrhage was chosen, and the resulting sensitivity, specificity, and false-negative and false-positive rates were explored.

RESULTS

The prevalence rates of postpartum hemorrhage in the prediction and validation cohorts were 6.3% (377 of 6000 cases) and 6.4% (241 of 3774 cases), respectively (P=.83). The following predictors were selected for the final model: maternal body mass index (kg/m), number of fetuses, history of postpartum hemorrhage, admission platelets of <100,000/µL, chorioamnionitis, arrest of descent, placental abruption, and active labor duration. The predictive model had an area under the receiver operating characteristic curve of 0.82 (95% confidence interval, 0.81-0.84). When applied to the validation cohort, the model had an area under the receiver operating characteristic curve of 0.81 (95% confidence interval, 0.78-0.83), a sensitivity of 86.9%, a specificity of 74.2%, a positive predictive value of 18.6%, a negative predictive value of 98.8%, a false-negative rate of 13.1%, and a false-positive rate of 25.9%.

CONCLUSION

The model performed reasonably well in identifying women at risk of postpartum hemorrhage. Further studies are necessary to evaluate the model in clinical practice and its effect on decreasing the prevalence of postpartum hemorrhage and associated maternal morbidity.