JBRA Assist. Reprod. 2025;29(Suppl 1):17-17
POSTER PRESENTATION
doi: 10.5935/1518-0557.20250072
1Cegyr, Eugin Group - Research department (Buenos Aires, Argentina)
Objective:
• Evaluate the occurrence of blastocyst formation imbalance in shared egg donor programs.
• Investigate whether blastocyst formation imbalance in shared egg donor programs affects the clinical outcomes of recipients.
• Compare the effectiveness of blastulation prediction using Magenta® with traditional methods of oocyte quality assessment.
• Explore the potential of artificial intelligence, such as Magenta®, to optimize oocyte distribution in shared egg donation programs and reduce blastocyst outcome imbalances.
Methods: Shared egg donor programs often result in significant imbalances in blastocyst outcomes among recipients, with some producing many blastocysts while others produce very few. This leads to unequal clinical outcomes and inefficient resource use. Oocyte quality assessment, traditionally based on subjective morphological evaluations, lacks precision and reproducibility, making it challenging to predict developmental potential or optimize oocyte distribution. AI-based tools like Magenta® offer a novel, objective approach to predicting blastulation potential, which could help improve oocyte allocation strategies and address these long-standing challenges in shared egg donation programs. A two-step retrospective cohort study was conducted. Step 1 (blastocyst formation imbalance): all the shared egg donor cycles (2018-2024) were evaluated for differences between paired recipients. Step 2 (blastulation prediction): all egg donor cycles (2023-2024) in which oocytes were categorized by Magenta® (score groups: A 0-2.5, B 2.6-5.0, C 5.1-7.5, D 7.6-10) were analyzed. Inclusion criteria: egg donation cycles undergoing PGT-A. Exclusion criteria: severe male factor cases. Step 1: Analyzed blastocyst formation imbalances between paired recipients (only in cases where two recipients received the same number of oocytes). Step 2: evaluated Magenta® scores and their association with blastulation and euploidy rates. Data were collected retrospectively from a private fertility center. Analyses were conducted using STATA 17.0, employing Chi-square tests for categorical variables and t-tests for continuous variables.
Results: In 209 donor cycles allocating similar oocyte numbers between two recipients, 23.9% (50/209; 95% CI 18.3-30.1%) exhibited one recipient with a difference of two or more blastocysts than in the paired recipient. In addition, 8.6% (18/209; 95% CI 5.2-13.2%) had the same imbalance with the additional complication that one recipient produced just one or no blastocysts. On the other hand, among 2582 donor oocytes assessed with Magenta® and fertilized via ICSI, oocytes with scores <2.5 had significantly lower blastulation rates (Cat A: 30.6%, B: 41.8%, C: 41.2%, D: 46.7%; p<0.01), with a 39% reduction in blastulation probability (RR 0.61, 95% CI 0.51-0.74). No significant association with euploidy was observed (RR 0.82, 95% CI 0.62-1.08). Finally, we evaluated 42 cycles in which a similar number of oocytes were allocated between two recipients and Magenta® was performed. In the blastocyst imbalance group, there was a trend towards greater differences in the proportion of low-quality oocytes based on Magenta® scores (45.5% vs. 33.3%, p=NS).
Conclusion: Significant blastocyst imbalances occur in one in four shared egg donor cycles, with one-third of these cases resulting in a recipient having few or no embryos to transfer. Integrating artificial intelligence into oocyte distribution strategies could help mitigate these disparities, improving outcomes for both patients and shared donation programs. These findings provide a solid foundation for the hypothesis that Magenta® could help reduce imbalances in shared egg donation programs. However, validation through prospective studies is needed, incorporating robust endpoints such as pregnancy and live birth rates to confirm its clinical utility.