Cryo-thawed embryos obtained from conception cycles have double the implantation and pregnancy potential of those from unsuccessful cycles
Bibliographic record
Abstract
BACKGROUND: The purpose of this study was to evaluate the influence of fresh IVF/ICSI cycle outcome on the prognosis of the related frozen embryo replacement (FER) cycle. METHODS: 459 FER cycles, involving 2049 cleavage stage embryos with no or up to 10% fragmentation, were performed for which the outcome of the fresh cycle was recorded. The cycles were divided into two groups; group A included cycles in which cryopreserved embryos were obtained from fresh cycles in which conception occurred. Group B were cycles in which cryopreserved embryos originated from unsuccessful fresh cycles. RESULTS: Groups A and B were comparable with respect to mean (+/- SD) age at cryopreservation (33 +/- 3.9 versus 33.2 +/- 4 years, P = not significant), mean number of oocytes retrieved and fertilized normally in the fresh cycle (11 +/- 5.2 versus 11.2 +/- 4.8, P = not significant) and mean age at the cryo-thawed transfer (34.5 +/- 4.2 versus 33.9 +/- 4 years, P = not significant). No significant difference was found between the two groups with regard to mean number of embryos cryopreserved (6.5 +/- 3.9 versus 6.2 +/- 3.6) and subsequently thawed (4.5 +/- 2.5 versus 4.5 +/- 1.8) per cycle and number of cryo-thawed embryos transferred per cycle (2.0 +/- 0.7 versus 2.1 +/- 0.8). However, the implantation rate per transferred embryo in group A was double that in group B (23 versus 11.2%, P < 0.0001). Moreover, the clinical pregnancy and ongoing pregnancy rates per cycle were significantly higher in group A compared with group B (34.8 and 27.3% versus 15.6 and 13.1%, P < 0.0001 and P = 0.0003 respectively). The difference in FER cycle outcome could not be explained by confounding variables. CONCLUSIONS: After thawing, cryopreserved embryos originating from conception IVF/ICSI cycles achieve double the implantation and pregnancy rates of those obtained from unsuccessful cycles.
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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 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.003 | 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".