目的 构建并验证剖宫产术后再妊娠女性发生剖宫产瘢痕妊娠(caesarean scar pregnancy,CSP)的风险预测模型.方法 收集2018～2022年于乌鲁木齐市妇幼保健院剖宫产术后再妊娠女性663例,按7∶3随机划分为训练集(n=460)和测试集(n=203),将训练集病例分为CSP组(n=239)和非CSP组(n=221).采用单因素以及多因素Logistic回归分析评价CSP发生的危险因素.基于以上结果构建列线图模型,分别在测试集和训练集中进行验证并评价.通过受试者工作特征(receiver operating characteristic,ROC)曲线下面积(area under the curve,AUC)、Hosmer-Lemeshow检验等评价模型的预测效能,使用临床决策曲线分析(decision curve analysis,DCA)评估模型的临床应用价值.结果 多因素Logistic回归分析结果显示,剖宫产次数＞1次、子宫后位、流产次数＞1次、剖宫产瘢痕憩室、本次妊娠距前次剖宫产间流产史是CSP发生的危险因素(P＜0.05),剖宫产时机为产程中是CSP发生的保护因素(P＜0.05).基于以上结果构建列线图预测模型,模型在训练集中AUC为0.813(95％CI:0.773～0.852);在测试集中AUC为0.817(95％CI:0.755～0.878);训练集和测试集Hosmer-Lemeshow拟合优度检验该模型拟合度良好(x2=7.647,P=0.469;x2=6.162,P=0.629).校准曲线显示,该模型在预测剖宫产术后再妊娠发生CSP具有较好的一致性,DCA曲线显示,模型在训练集和测试集中均具有较高的临床效能.结论 以上研究构建的预测模型能有效预测CSP的发生,可为高风险人群早期识别和预防性治疗提供参考.
Construction and Verification of Nomogram Model for Predicting the Risk of Caesarean Scar Pregnancy
Objective To construct and validate the risk prediction model for the occurrence of caesarean scar pregnancy(CSP)in women with re-pregnancy after cesarean section.Methods A total of 663 women with re-pregnancy after cesarean section in Urumqi Maternal and Child Health Hospital from 2018 to 2022 were collected,and randomly divided the training set(n=460)and the test set(n=203)according to 7∶3,the cases of the training set were divided into the CSP group(n=239)and the non-CSP group(n=221),and the risk factors for the occurrence of CSP were evaluated by univariate and multivariate Logistic regression analysis.Based on the a-bove results,a nomogram model was constructed,validated and evaluated in the test set and the training set,respectively.The predictive efficacy of the model was evaluated by area under the curve(AUC)of receiver operating characteristic(ROC)and the Hosmer-Leme-show test,and the clinical application value of the model was evaluated by clinical decision curve analysis(DCA).Results The results of multivariate Logistic regression analysis showed that the number of cesarean section＞1,posterior uterine position,the number of mis-carriages＞1,CSD,the history of miscarriage between the current pregnancy and the previous cesarean section were the risk factors for the occurrence of CSP(P＜0.05),and the timing of cesarean section was the protective factor for the occurrence of CSP in the course of labor(P＜0.05).Based on the above results,the nomogram prediction model was constructed,the AUC of the model in the training set was 0.813(95％CI:0.773-0.852),and the AUC of the model in the test set was 0.817(95％CI:0.755-0.878).Hosmer-Lemeshow goodness-of-fit test for the training set and the test set model was well fitted(x2=7.647,P=0.469;x=6.162,P=0.629).The calibration curve showed that the model had good consistency in predicting the occurrence of CSP in re-pregnancy after cesarean section,and the DCA curve showed that the model had high clinical efficacy in both the training set and the test set.Conclusion The prediction model constructed in this study can effectively predict the occurrence of CSP,which can provide references for early identification and pre-ventive treatment for high-risk populations.
Caesarean scar pregnancyInfluencing factorsNomogram model
万方数据
维普
