Objective To investigate the risk factors of uterine artery embolization(UAE)in treating cesarean scar pregnancy(CSP),and to construct a nomogram prediction model used for providing a basis for individualized treatment.Methods The clinical data of 305 CSP patients,who were admitted to the Shanxi Bethune Hospital from January 2014 to June 2023,were retrospectively analyzed.Multivariate logistic regression was used to analyze the independent risk factors for UAE in patients with CSP,based on which a risk prediction model was constructed.R language was used to draw a nomogram.The receiver operating characteristic(ROC)curve was used to evaluate the predictive power of the model.The model was verified and calibrated,and the decision curve analysis(DCA)curve was drawn to analyze its clinical utility.Results Of the 305 CSP patients,88(28.85％)received interventional operation and 217(71.15％)did not receive interventional operation.Univariate and multivariate analysis showed that gestational sac diameter(OR=1.062,95％CI=1.034-1.091,P=0.001),abdominal pain(OR=0.179,95％CI=0.085-0.379,P=0.001),residual muscle thickness(OR=6.532,95％CI=3.271-13.043,P=0.001),were the independent risk factor for UAE in CSP patients(P＜0.05).The following risk prediction model was established:h(t,X)=h0(t)exp(-1.718X1+1.877X2+0.061X3),which was presented as a nomogram.ROC curve analysis indicated that the overall prediction efficiency of the model was better than that of a single risk factor,and the Hosmer-Lemeshow test of the model had a better fit degree.The consistency index(C-index)was 0.828,suggesting that this model had good discrimination ability.After correction by the Bootstrap method,this model had a relatively high prediction accuracy.DCA curve evaluation revealed that this model had good clinical utilization value.Conclusion The nomogram of the risk prediction model,which is constructed based on the presence or absence of abdominal pain,gestational sac diameter and residual muscle thickness,has high accuracy and differentiation with a good consistency.This model has good clinical utilization value and it can be used to predict and evaluate whether a patient with CSP is at risk of UAE.
维普
万方数据