Prediction of clinical pregnancy in frozen-thawed embryo by a Nomogram model based on endometrial ultrasound parameters
Objective:To construct and validate a Nomogram prediction model incorporating ultrasound parameters related to endometrial tolerance,so as to assess the individualized probability of successful clinical pregnancy in frozen embryo transfer(FET).Methods:A prospective cohort study was conducted to analyze the clinical data of 357 patients(included 357 FET cycles)who underwent FET at the Reproductive Centre of the Sixth Medical Center of PLA General Hospital from March to December 2023.They were divided into a modelling group(219 cycles)and a validation group(138 cycles)according to the time of inclusion,and the modelling group was further divided into a clinical pregnancy group(107 cycles)and a non-pregnant group(112 cycles)according to whether they were pregnant or not.Baseline data and ultrasound measurements of the included patients were collected,single and multifactorial logistic regression analyses were used to screen for independent influences on clinical pregnancy,least absolute shrinkage and selection operator(LASSO)regression and Akaike information criterion(AIC)analyses were used to determine the variable combinations for constructing the optimal Nomogram model,and the performance of the Nomogram was assessed by the receiver operator characteristic(ROC)curves,the calibration curves,and the clinical decision curves.Results:There were no significant differences in female age,infertility years and basic sex hormone level between the modelling and validation groups(P＞0.05).And there were no significant differences in female age and infertility type between the clinical pregnancy and non-pregnant groups in the modelling group(P＞0.05).The results of univariate analysis showed that endometrial thickness,uterine artery resistance index(RI),uterine artery pulsatility index(PI),endometrial volume,endometrial vascularisation index(VI),flow index(FI),vascularised flow index(VFI),and Applebaums blood typing had significant effects on the clinical pregnancy rate(P＜0.05).Furthermore,multifactorial logistic regression analysis showed that endometrial volume[OR=2.769,95％CI(1.571,4.881),P＜0.001],uterine artery RI[OR=3.091,95％CI(1.332,7.170),P=0.009],endometrial VI[OR=2.641,95％CI(1.439,4.847),P=0.002]were the independent influencing factors of the clinical pregnancy rate.For screening model variables,the results of LASSO cross-validation agreed with those of the minimum AIC criterion,namely the performance of the model constructed by endometrial volume,uterine artery RI and endometrial VI combined with endometrial FI was better.The area under the ROC curve(AUC)in the modelling group and the validation group were 0.814[95％CI(0.756,0.872)]and 0.797[95％CI(0.720,0.873)],respectively,showing good model discrimination.The calibration curves and the decision curve showed that the predicted clinical pregnancy rates of the Nomogram were with superior accuracy and net clinical benefit.Conclusions:This study developed a Nomogram model for predicting early pregnancy outcomes in FET,which could be useful for personalized assessment of clinical pregnancy probability in FET.
万方数据
维普
