Early Pregnancy Outcomes in Fresh Versus Deferred Embryo Transfer Cycles for Endometriosis-Associated Infertility: A Retrospective Cohort Study
Bibliographic record
Abstract
Given the estrogen-dependence associated with endometriosis, hyper-stimulation associated with assisted reproduction treatment may exacerbate the disease process and adversely affect endometrial receptivity and subsequent implantation. In this way, a freeze-all deferred embryo transfer (ET) approach may benefit patients with endometriosis, although controversy exists regarding the mechanism of endometriosis-associated infertility and benefits of deferred ET on endometrial receptivity. Hence, the purpose of this study was to compare in vitro fertilization (IVF) outcomes in women with endometriosis, diagnosed by histology, undergoing fresh versus deferred-ET after elective cryopreservation. Of the 728 women included, no significant differences were observed in baseline patient characteristics and response to gonadotrophin stimulation between fresh and deferred ET groups. Furthermore, no significant differences in implantation rate (49.7 vs. 49.9%, p = 0.73), clinical pregnancy rate (40.9 vs. 39.9%, p = 0.49), and miscarriage rate (9.4 vs. 9.9%, p = 0.63) were observed between fresh and deferred ET groups, respectively. Hence, contrary to previous studies, our results suggest that a deferred ET “freeze-all” IVF strategy does not improve early pregnancy outcomes among women with endometriosis. However, prospective studies are required to validate these findings and further insight into the etiology and pathogenesis of endometriosis-associated infertility are necessary to optimize IVF protocols in this population.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".