Construction and validation of a risk nomogram prediction model for postpartum hemorrhage in pregnant women during spontaneous delivery

ObjectiveTo explore the risk factors for postpartum hemorrhage (PPH) in pregnant women during spontaneous delivery, and to establish a risk nomogram prediction model.

MethodsThe clinical information of 3 067 parturients who underwent an obstetric examination and eventually delivered vaginally in the department of obstetrics was collected.According to the occurence of PPH within 24 hours after delivery, the parturients were divided into PPH group (n=229) and non-PPH group (n=2 838).The clinical information of the two groups was compared, and logistic regression analysis was used to screen the risk factors for PPH in spontaneous delivery and a prediction model was established.The area under the ROC curve, sensitivity and specificity were used to evaluate the performance of the model, and Bootstrap self-sampling method was used to verify the model internally.

ResultsThere were significant differences between PPH group and non-PPH group in age, multiple pregnancy, pregnancy induced hypertension, prenatal D-dimer, prenatal Fib, the third stage of labor, placental adhesion, and fetal body mass (P < 0.01).Multivariate logistic regression analysis showed that high age, multiple births, pregnancy induced hypertension, pre-partum D-dimer elevation, long third stage of labor, placenta adhesion, and large fetal body mass were all risk factors for PPH in spontaneous delivery of pregnant women (P < 0.01), and pre-partum Fib elevation was a protective factor for PPH in spontaneousl delivery of pregnant women (P < 0.01).By using the above 8 indicators to construct and verify the nomogram prediction model, it was found that the AUC of the model was 0.824, the sensitivity was 0.819, and the specificity was 0.715 for predicting PPH in spontaneous delivery of pregnant women.After 1 000 samples of Bootstrap method, the MAE of the calibration curve was 0.004, which showed that the model had a good consistency in predicting the risk of spontaneous delivery PPH in pregnant women and the actual occurrence.

ConclusionsThe clinical integration of pregnant women's age, number of fetuses, pregnancy-induced hypertension, pre-partum D-dimer, pre-partum Fib, the third stage of labor, placental adhesions, and fetal weight indicators are used to construct a prediction model that can improve the accuracy of evaluating pregnant women's spontaneous delivery PPH.