The role of endometrial thickness in predicting ectopic pregnancy after in vitro fertilization and the establishment of a prediction model

Abstract

Objective: To explore the risk factors of ectopic pregnancy after in vitro fertilization.

Methods: This retrospective cohort study was conducted at the Reproductive Medical Center of the Third Affiliated Hospital of Zhengzhou University from January 2016 to April 2020. Univariate and multivariate analysis were used to analyze the related factors affecting the occurrence of ectopic pregnancy (EP) and to construct a nomographic prediction model for the incidence of ectopic pregnancy.

Results: A total of 12,766 cycles of 10109 patients were included, comprising 214 cases of EP and 12,552 cases of intrauterine pregnancy (IUP). Multivariate logistic regression analysis showed that the tubal factor was associated with a 2-fold increased risk for EP (aOR = 2.72, 95% CI: 1.69-4.39, P < 0.0001). A stratified analysis showed that women with an endometrial thickness (EMT) between 7.6 to 12.1mm (aOR = 0.57, 95%CI: 0.36-0.90, P = 0.0153) and >12.1mm (aOR = 0.42, 95%CI: 0.24-0.74, P = 0.0026) had a significant reduction of the risk of EP compared to women with an EMT of <7.6mm. Compared to cleavage stage transfer, blastocyst transfer can reduce the risk of ectopic pregnancy (aOR = 0.36, 95%CI: 0.26-0.50, P < 0.0001). The saturation model (full mode) establishes a nomographic prediction model with an AUC = 0.68 and a sensitivity and specificity of 0.67and 0.64, respectively. The nomination model was internally verified by self-sampling method (bootstrap sampling resampling times = 500). The resulting AUC = 0.68 (sensitivity: 0.65; specificity: 0.65) showed that the model was relatively stable.

Conclusions: Our findings indicate that EMT is inversely proportional to the risk of EP. Embryo stage, number of embryos transferred were also significantly associated with EP rate. A simple nomogram for the predicting the risk of EP was established in order to reduce the occurrence of EP.

Keywords: IVF; ROC; clinical prediction model; ectopic pregnancy; risk factors.