BackgroundCervical insufficiency can lead to preterm birth and neonatal mortality. Emergency cervical cerclage is a surgical intervention aimed at preventing preterm birth in patients with cervical insufficiency. However, some patients may experience cerclage failure. This study aimed to identify the risk factors associated with cerclage failure and develop a predictive nomogram model for patients with cervical insufficiency undergoing emergency cervical cerclage. MethodsData of 200 patients who underwent emergency cervical cerclage for cervical insufficiency were retrospectively analyzed. Patients were categorized into successful and failed groups based on their ability to take the infant home. Univariate and multivariate logistic regression analyses were performed to identify risk factors for cerclage failure. A nomogram model was developed based on multivariate logistic regression results, and its performance was assessed using receiver operating characteristic curves, calibration plots, and decision curve analysis (DCA). ResultsUnivariate logistic regression analysis identified 11 potential risk factors for cerclage failure, including the presence of polycystic ovary syndrome (PCOS), vaginitis, cervical dilation, preoperative C-reactive protein, routine vaginal lavage after cervical cerclage, delivery, gestational age, extended days, chorioamnionitis, intrauterine infection, cervical laceration, and premature rupture of membranes. Multivariate logistic regression analysis revealed that PCOS, cervical dilation after cervical cerclage were independent risk factors for cerclage failure while routine vaginal lavage was a protective factor against failure. The nomogram predictive model demonstrated an area under the curve value of 0.975, indicating excellent discriminatory ability. The calibration plot showed good consistency between the nomogram predictions and actual observations. DCA demonstrated the strong clinical applicability of the nomogram. ConclusionsThis study successfully identified risk factors associated with emergency cervical cerclage failure in patients with cervical insufficiency and developed a predictive nomogram model. This model can assist clinicians in making informed decisions and accurately predicting the risk of cerclage failure in these patients.
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