Elective single embryo transfer: Is frozen better than fresh?
Bibliographic record
Abstract
OBJECTIVE: Single embryo transfer (SET) has been recommended to avoid multiple births following assisted reproductive technology (ART) procedures. Many studies have shown that frozen embryo transfer may yield better pregnancy rates than fresh embryo transfer. This study looked into pregnancy rates following fresh versus frozen single embryo transfer procedures in age-matched patients. METHODS: This retrospective case control study was carried out at a private clinic [NewLife Fertility Clinic, ON, Canada]. Patient groups included infertile women treated with IVF/ICSI and elective single embryo transfer (eSET) given either fresh or frozen embryos. Cycle outcomes were compared between patient groups matched by age. The primary endpoints were positive testing for ß-hCG and viable ongoing pregnancy. The secondary endpoints were live birth and miscarriage rates. RESULTS: A total of 583 eSET cycles (212 fresh transfer cycles and 371 frozen transfer cycles) were performed. Significantly higher pregnancy and live birth rates were observed among patients aged ≤ 39 years given frozen embryos. CONCLUSION: Frozen single embryo transfer was associated with higher pregnancy and live birth rates when compared to fresh single embryo transfer.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".