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| Influencing factors of the postpartum infection of puerperas after cesarean section and the predictive model establishment |
1.The Second People's Hospital of Liaocheng, Shandong Province, 252600；2. People's Hospital of Liaocheng;
3.Dongchangfu District Maternal and Child Health Care Hospital of Liaocheng |
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Abstract To explore the incidence of the postpartum infection of puerperas after cesarean section, and to study the influencing factors of the postpartum infection. Methods: The clinical data of 987 puerperas who had undergone cesarean section from three hospitals of Liaocheng were selected in this study from January 2021 to January 2023. The incidence of the postpartum infections of the puerperas within 5 days of follow up after cesarean section was counted. Univariate and multivariate logistic regression were applied to analyze the factors affecting the postpartum infections of the puerperas after cesarean section. A nomogram model was constructed based on these influence factors, and receiver operating characteristic (ROC) curve was drawn to evaluate the discriminability of this model, and the calibration curve was drawn to evaluate the consistency of the model. Results: Among 987 puerperas with caesarean section, 72 puerperas had postoperative infections, with an infection rate of 7.3%, including 41 (56.9%) cases with incision infection, 20 (27.8%) cases with endometritis and 11 (15.3%) cases with other infections. There was significant difference in the proportion of the postpartum infections after cesarean section among the puerperas with different ages, among the puerperas with different number of cesarean sections, among the puerperas with different albumin levels, between the puerperas with and without GDM, between the puerperas with and without premature rupture of membranes, and between the puerperas with and without transferred to cesarean section because of the abnormal second stage of labor (P<0.05). Multivariate logistic regression analysis showed that the age ≥30 years old, the number of cesarean section ≥3 times, the GDM, the premature rupture of membranes, the albumin level <35g/L and the transferred to cesarean section because of the abnormal second stage of labor of the puerperas with cesarean section were the risk factors of their postpartum infection (P<0.05). The area under the ROC curve of the nomogram model for predicting the postpartum infection of the puerperas with cesarean section was 0.820, with better discrimination, and the H-L goodness of fit test was 8.013 (P=0.621), and which indicated the good consistency. Conclusion: The advanced age, the multiple cesarean sections, the low albumin level, the GDM, the premature rupture of membranes, and the transferred to cesarean section because of the abnormal second stage of labor of the puerperas are the risk factors of their postpartum infection after cesarean section. The nomogram model constructed based on these factors has good discrimination and consistency, which can predict the risk of the postpartum infections of the puerperas after cesarean section betterly and can guide the intervention in clinic, so as to reduce the postpartum infection rate of the puerperas.
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