Abstract:

Objective To analyze the influencing factors of ectopic pregnancy in the patients with in vitro fertilization-embryo transfer （IVF-ET），and to establish the nomogram model to predict the risk of ectopic pregrancy in the patients with IVF-ET. Methods The inclusion and exclusion criteria of the subjects were developed， the clinical informations of 522 patients with IVF-ET and successful pregnancy were analyzed retrospectively for modeling and internal validation； according to the above inclusion and exclusion criteria， the clinical informations of 1 126 patients with IVF-ET and successful pregnancy who were not in our hospital were screened for external verification. The baseline data of the patients were recorded， according to the occurrence of ectopic pregnancy in the IVF-ET patients， they were divided into occurrence group and non-occurrence group， Logistic regression was used to analyze the influencing factors of ectopic pregnancy in the patients with IVF-ET； based on the above influencing factors， the nomogram model for predicting the occurrence of ectopic pregnancy in the IVF-ET patients was established. The Bootstrap method was used for model verification， and the consistency index （C-index） was calculated to test the accuracy of the model； the area under the curve （AUC） of receiver operating characteristics （ROC） and calibration curve were used to evaluate the discrimination and calibration of the nomogram model. Results Among 522 patients in the internal validation group， 45 patients had ectopic pregnancy， the incidence rate was 8.62%； after the baseline data of the patients in two groups were compared， the Logistic regression analysis results showed that the history of intrauterine operation， smoking，pelvic inflammatory disease， previous ectopic pregnancy and elevated serum estradiol （E2） level on the day of human chorionic gonadotrophin （hCG） injection were the influencing factors of ectopic pregnancy in the patients with IVF-ET （OR>1，P<0.05）； the nomogram model for predicting the ectopic pregnancy in the IVF-ET patients was constructed； Bootstrap internal verification method was used to verify the nomogram model， the calibration degree of the model was good， and the C-index was 0.702； it showed that the model had good discrimination. The nomogram model was internally verified， the ROC curve was drawn and the AUC of nomogram model in predicting the risk of ectopic pregnancy in the patients with IVF-ET was 0.735（>0.70）， which had certain predictive value； the nomogram model was externally verified， the ROC curve was drawn and the AUC of nomogram model for predicting the risk of ectopic pregnancy in the patients with IVF-ET was 0.862（>0.80）， which had better predictive value. Conclusion Ectopic pregnancy in the patients with IVF-ET is affected by many factors such as history of intrauterine operation， smoking， pelvic inflammatory disease， previous ectopic pregnancy and the E2 level on the day of hCG injection， and the nomogram model based on multiple influencing factors provides an effective method for reasonably predicting the risk of ectopic pregnancy in the patients with IVF-ET.

Key words: In vitro fertilization-embryo transfer, Ectopic pregnancy, Influencing factors, Nomogram model