International journal of women's health · 2026
The Influencing Factors and Predictive Algorithm of Pregnancy Outcomes in IVF/ICSI-ET Patients.
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Wang Chong, Yang Xiao-Jing, Feng Ying
Аннотация
PURPOSE: To explore the influencing factors of clinical pregnancy outcomes for in vitro fertilization/intracytoplasmic single sperm injection and embryo transfer (IVF/ICSI-ET) patients, and to establish a predictive algorithm to predict the rate of clinical pregnancy.
PATIENTS AND METHODS: A single-center retrospective analysis was performed on 1183 treatment cycles of patients undergoing IVF/ICSI-ET at Hangzhou Women's Hospital, covering the period from April 2018 to March 2023. All cases were categorized into clinical pregnancy and non-pregnant groups. Totally 24 clinical and laboratory indicators were analyzed by logistic regression model to analyze the factors affecting clinical pregnancy outcome in IVF/ICSI-ET treated couples. Furthermore, by stratifying the influencing factors and quantitatively assigning scores, a predictive algorithm was established to predict the clinical pregnancy outcomes by calculating the total score.
RESULTS: The results of multivariate logistic regression analysis showed that the male age (OR=0.965, 95% CI: 0.949~0.980) and progesterone (P) level on hCG day (OR=0.687, 95% CI: 0.500~0.944) were negatively correlated with clinical pregnancy in IVF/ICSI-ET couples, and that AMH (OR=1.085, 95% CI: 1.022~1.151), the number of high-quality embryos (OR=1.094, 95% CI: 1.039~1.152), and the number of transferred embryos (OR=2.218, 95% CI: 1.684~2.922) were positively associated with clinical pregnancy. Our multivariate logistic regression model reached a sensitivity of 64.55%, a specificity of 58.42%, and an AUC of 0.644 (95% CI: 0.614-0.673). A simple predictive algorithm of clinical pregnancy outcome was then developed using the five variables, both internal and external validations have been taken. The total score of the algorithm is between 0 and 23, and couples with total score of 10 or higher are highly likely to achieve clinical pregnancy.
CONCLUSION: Factors affecting clinical pregnancy in infertile couples mainly included male age, AMH, P level on hCG day, number of high-quality embryos, and number of embryos transferred. Clinicians can use predictive algorithms to predict clinical pregnancy outcomes more simpler and convenient, and develop personalized embryo transfer strategies more precisely.
PATIENTS AND METHODS: A single-center retrospective analysis was performed on 1183 treatment cycles of patients undergoing IVF/ICSI-ET at Hangzhou Women's Hospital, covering the period from April 2018 to March 2023. All cases were categorized into clinical pregnancy and non-pregnant groups. Totally 24 clinical and laboratory indicators were analyzed by logistic regression model to analyze the factors affecting clinical pregnancy outcome in IVF/ICSI-ET treated couples. Furthermore, by stratifying the influencing factors and quantitatively assigning scores, a predictive algorithm was established to predict the clinical pregnancy outcomes by calculating the total score.
RESULTS: The results of multivariate logistic regression analysis showed that the male age (OR=0.965, 95% CI: 0.949~0.980) and progesterone (P) level on hCG day (OR=0.687, 95% CI: 0.500~0.944) were negatively correlated with clinical pregnancy in IVF/ICSI-ET couples, and that AMH (OR=1.085, 95% CI: 1.022~1.151), the number of high-quality embryos (OR=1.094, 95% CI: 1.039~1.152), and the number of transferred embryos (OR=2.218, 95% CI: 1.684~2.922) were positively associated with clinical pregnancy. Our multivariate logistic regression model reached a sensitivity of 64.55%, a specificity of 58.42%, and an AUC of 0.644 (95% CI: 0.614-0.673). A simple predictive algorithm of clinical pregnancy outcome was then developed using the five variables, both internal and external validations have been taken. The total score of the algorithm is between 0 and 23, and couples with total score of 10 or higher are highly likely to achieve clinical pregnancy.
CONCLUSION: Factors affecting clinical pregnancy in infertile couples mainly included male age, AMH, P level on hCG day, number of high-quality embryos, and number of embryos transferred. Clinicians can use predictive algorithms to predict clinical pregnancy outcomes more simpler and convenient, and develop personalized embryo transfer strategies more precisely.