A Nomogram for Predicting the Risk of Twin and Preterm Births After Two Cleavage-Stage Embryo Transfer.

Abstract

Objective: To propose a prediction model aimed at increasing the live birth rate of patients undergoing two-cell embryo transfer while eliminating multiple pregnancy complications.

Methods: Women who underwent their first In Vitro Fertilization (IVF) cycle with transferred cleavage-stage embryos at the Affiliated Hospital of Southwest Medical University between January 2016 and December 2024 were included. This study recruited women who received the GnRH agonist long protocol (GnRH-a) or antagonist protocol (GnRH-ant) for ovarian stimulation. In addition, the clinical parameters related to the basic protocol and embryo characteristics were recorded.

Results: In the multivariate analysis, we found that female age, endometrial thickness on the Human Chorionic Gonadotropin (HCG) days, patients with Body Mass Index (BMI) >30, high-quality embryos with 4 cells between 1 and 4 pieces, high-quality embryos with 8 cells, available embryos between 5 and 15 pieces and high-quality embryos between 1 and 4 pieces were crucial factors in the twin pregnancies prediction model (p < 0.05). On the basis of these characteristics, we constructed a nomogram for twin pregnancies. Additionally, we compared the difference between premature and normal births and found that endometrial thickness on HCG days positively correlated with the model score. In the premature group, the endometrial thickness on HCG days was lower than that found in patients without premature births.

Conclusion: Endometrial thickness on the HCG day may influence the outcome of twin pregnancies. The high-quality embryos showed a higher positive correlation with the model score. Patients with preterm birth had less endometrial thickness on the HCG day than patients without premature birth. For patients with high-quality embryos, it is advisable to use single embryo transfer to reduce the rate of twin pregnancies. This nomogram will enhance the counseling of patients with infertility challenges.