Cryopreserved embryo replacement is associated with higher birthweight compared with fresh embryo: multicentric sibling embryo cohort study
Bibliographic record
Abstract
Birth weight (BW) is higher after frozen embryo transfer (FET) than after fresh embryo replacement. No study has compared the BW of siblings conceived using the same oocyte/embryo cohort. The aim of this study was to determine whether the freezing-thawing procedure is involved in such difference. Multicenter study at Montpellier University Hospital, Clinique Ovo, Canada and Grenoble-Alpes University Hospital. The first cohort (Fresh/FET) included in vitro fertilization (IVF) cycles where the older was born after fresh embryo transfer (n = 158) and the younger after transfer of frozen supernumerary embryos (n = 158). The second cohort (FET/FET) included IVF cycles where older and younger were born after FET of embryos from the same cohort. The mean adjusted BW of the FET group was higher than that of the fresh group (3508.9 ± 452.4 g vs 3237.7 ± 463.3 g; p < 0.01). In the FET/FET cohort, the mean adjusted BW was higher for the younger by 93.1 g but this difference is not significant (3430.2 ± 347.6 g vs 3337.1 ± 391.9 g; p = 0.3789). Our results strongly suggest that cryopreservation is directly involved in the BW variation. Comparing BW difference between Fresh/FET cohort and FET/FET one, it suggests that parity is not the only responsible, increasing the role of cryopreservation step in BW variation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.002 | 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".