Comparing Day 5 versus Day 6 euploid blastocyst in frozen embryo transfer and developing a predictive model for optimizing outcomes: a retrospective cohort study - Yin, Beining; Li, Sichen; Sun, Lin; Yao, Zhiyi; Cui, Yueyue; Zhang, Congli (Frontiers in Endocrinology, 2024)
Background: Optimal protocols for frozen-thawed embryo transfer (FET) after preimplantation genetic testing (PGT) remain unclear. This study compared Day 5 (D5) and Day 6 (D6) blastocysts and evaluated predictors of FET success.: A total of 870 patients with genetic diseases or chromosomal translocations who received PGT at the First Affiliated Hospital of Zhengzhou University from January 2015 to December 2019 were recruited. All patients underwent at least one year of follow-up. Patients were divided into groups according to the blastocyst development days and quality. Univariate and multivariate logistic regression were applied to identify risk factors that affect clinical outcomes and to construct a predictive nomogram model. Area under the curve (AUC) of the subject's operating characteristic curve and GiViTI calibration belt were conducted to determine the discrimination and fit of the model. Results: D5 blastocysts, especially high-quality D5, resulted in significantly higher clinical pregnancy (58.4% vs 49.2%) and live birth rates (52.5% vs 45%) compared to D6. Multivariate regression demonstrated the number of blastocysts, endometrial preparation protocol, days of embryonic development and the quality of blastocysts independently affected live birth rates (P<0.05). A nomogram integrating these factors indicated favorable predictive accuracy (AUC=0.598) and fit (GiViTI, P=0.192). Conclusions: Transferring high-quality D5 euploid blastocysts after PGT maximizes pregnancy outcomes. Blastocyst quality, blastocyst development days, endometrial preparation protocols, and number of blastocysts, independently predicted outcomes. An individualized predictive model integrating these factors displayed favorable accuracy for counseling patients and optimizing clinical management.