Effect of double embryo transfer derived from autologous frozen oocytes on multiple pregnancy rates and presentation of success rates stratified by age at retrieval
Bibliographic record
Abstract
Objective: To compare outcomes transferring one or two embryos in autologous frozen oocyte cycles. Material and Methods: A retrospective cohort study conducted at an academic fertility center between January 2012 and December 2018. One-hundred and fourteen patients underwent frozen oocyte transfers; 67 single embryo transfer (SET) and 47 double embryo transfer (DET). No subjects had more than two embryos transferred. Data were analyzed using t-test and chi-squared testing. Multivariate logistic regression was used to control for confounding effects. Power analysis suggested an 82% power with alpha of 5% and effect size of 27%. Results: Regarding the embryo stage, 72% were cleavage embryos and 28% were blastocyst embryos. Among those who had cleavage stage embryos, 48.8% underwent SET and 51.2% underwent DET. In the blastocyst embryos group these proportions were 84.4% and 15.6%, respectively. There were no difference in pregnancy rate for SET (40.3%) vs DET (36.2%) (p=0.78). Additionally, the live birth rate did not differ between SET and DET (28.4 vs 19.1%, respectively, p=0.26). The multivariate multilevel analysis provided adjusted odds ratios (95% confidence interval) of: 1.85 (0.46-7.44) for pregnancy; 0.497 (0.05-4.86) for clinical pregnancy; and 0.82 (0.11-6.29) for live birth when comparing SET and DET. Multiple pregnancy rates were significantly lower in the SET (0%), compared with DET group (44.4%) (p<0.002). Conclusion: SET results in excellent live birth outcomes in autologous frozen oocyte cycles. However DET results in significantly increased rates of multiple pregnancies. This suggests that SET is a viable option in autologous frozen oocyte cycles.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".