European review for medical and pharmacological sciences · 2022
A model for pregnancy rates after IVF-ET in patients with infertility and endometriosis.
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Huang F-P, Zhang H-L, Xie X, Du S-R, Yi J-S
Аннотация
OBJECTIVE: The objective of the present study was to examine the clinical factors influencing the pregnancy rate of infertile patients with endometriosis and establish a predictive model.
PATIENTS AND METHODS: This study included 158 patients (158 cycles) with infertility and endometriosis who underwent laparoscopic surgery, and in vitro fertilization and embryo transfer (IVF-ET) were evaluated retrospectively between January 2019 and December 2020. The clinical factors in the pregnant and non-pregnant group were analyzed by univariate analysis. Statistically significant variables were subsequently used for multivariate logistic regression to establish the prediction model.
RESULTS: Multivariate logistic regression analyses showed that GnRH-a treatment after operation (OR, 6.562; 95% CI: 2.782-15.477; p<0.01), ASRM stage (OR, 0.218; 95% CI: 0.093-0.509; p<0.05), the number of high-quality transferred embryos (OR, 3.155; 95% CI: 1.647-6.047; p<0.05) were independently associated with successful pregnancy. The area under the curve (AUC) of the prediction model was 0.774 (95% CI: 0.700-0.847). According to Hosmer-Lemeshow, the model was well fitted (p>0.05). We applied the bootstrapping method to internal validation, and the result showed that the pregnancy rate predicted by the model and the real data were consistent.
CONCLUSIONS: The models for predicting pregnancy rates after IVF-ET in infertility and endometriosis patients showed high accuracy. The effective methods to increase the number of high-quality embryos need further study.
PATIENTS AND METHODS: This study included 158 patients (158 cycles) with infertility and endometriosis who underwent laparoscopic surgery, and in vitro fertilization and embryo transfer (IVF-ET) were evaluated retrospectively between January 2019 and December 2020. The clinical factors in the pregnant and non-pregnant group were analyzed by univariate analysis. Statistically significant variables were subsequently used for multivariate logistic regression to establish the prediction model.
RESULTS: Multivariate logistic regression analyses showed that GnRH-a treatment after operation (OR, 6.562; 95% CI: 2.782-15.477; p<0.01), ASRM stage (OR, 0.218; 95% CI: 0.093-0.509; p<0.05), the number of high-quality transferred embryos (OR, 3.155; 95% CI: 1.647-6.047; p<0.05) were independently associated with successful pregnancy. The area under the curve (AUC) of the prediction model was 0.774 (95% CI: 0.700-0.847). According to Hosmer-Lemeshow, the model was well fitted (p>0.05). We applied the bootstrapping method to internal validation, and the result showed that the pregnancy rate predicted by the model and the real data were consistent.
CONCLUSIONS: The models for predicting pregnancy rates after IVF-ET in infertility and endometriosis patients showed high accuracy. The effective methods to increase the number of high-quality embryos need further study.