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Evaluation of a nomogram predictive model for the risk factors of postpartum hemorrhage of women after the second cesarean section |
Beijing Maternity Hospital, Capital Medical University, Beijing, 100026 |
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Abstract To explore the risk factors of affecting postpartum hemorrhage of women with the second cesarean section, and to construct and evaluate a nomogram prediction model. Methods: A retrospective analysis was conducted on the clinical data of 508 women who underwent the second cesarean section from March 2018 to June 2020. These women were divided into group A (women with postpartum hemorrhage) and group B (women without postpartum hemorrhage). Univariate analysis and multivariate Logistic regression analysis were used to select the risk factors affecting postpartum hemorrhage. Based on the selected risk factors, R software was used to establish a nomogram prediction model for postpartum hemorrhage, and the consistency of the model was tested. Results: The incidence of postpartum hemorrhage of 508 women with secondary cesarean section was 14.0%. Logistic regression analysis showed that breech position, placenta previa, less than 2 years after the previous cesarean section, and the prenatal blood loss ≥240ml were the risk factors of postpartum hemorrhage after the second cesarean section (P<0.05), while the use of oxytocin combined with misoprostol was a protective factor (P<0.05). The nomogram prediction model was evaluated, and the area under the ROC curve was 0.838 (95%CI: 0.788-0.887), and the slope of the calibration curve was close to 1. Hosmer-lemeshow goodness of fit test showed =4.551, P=0.473. Conclusion: The constructed nomogram prediction model based on the risk factors of postpartum hemorrhage of the women with the second cesarean section has good discrimination and consistency, which helps obstetric medical staff to screen the pregnant women with high-risk of postpartum hemorrhage after the second cesarean section, and can provide certain guiding for preventive nursing intervention measures.
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