Assisted reproduction using donated embryos: outcomes from surveillance systems in six countries
Bibliographic record
Abstract
BACKGROUND: Embryo donation, though less often performed than other assisted reproductive technology (ART), can represent an attractive option for couples who do not wish to discard their embryos remaining after IVF, and for those who cannot or should not conceive naturally. Clinicians and potential participants could benefit from information comparing outcomes of embryo donation with those of other ARTs, in various countries. METHODS: We analyzed outcome information from ART treatment cycles using 2001-2008 data from national surveillance systems in the USA, Canada, the UK, Australia, New Zealand and Finland. We calculated the live birth rate (LBR) with relative risks, the average number of embryos transferred per cycle and the ratio between them (LBR per embryo transferred). We compared outcomes of embryo donation cycles with those for autologous IVF, frozen embryo transfer (FET) and oocyte donation (OD). RESULTS: LBRs for embryo donation cycles were 14-33%, compared with 16-28% for autologous FET, 22-35% for autologous IVF and 15-52% for OD. In every country except Australia/New Zealand, and in all countries combined, the LBR for embryo donation approximated that for IVF, with no statistically significant differences in Finland and Canada. The average number of embryos transferred per cycle was 1.5-2.8. The LBR per embryo transferred was 11-12% for donor embryo cycles, compared with 8-11% for autologous FET, 12-15% for autologous IVF and 9-21% for OD. CONCLUSIONS: We found that transfer of donated embryos in these countries yields pregnancy outcomes comparable to those of autologous ART procedures. The variation in outcome rates among countries is not entirely explained by the number of embryos transferred. The relatively high success rates and low costs make embryo donation an attractive family building alternative.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".