A retrospective comparative study of double cleavage-stage embryo transfer versus single blastocyst in frozen-thawed cycles
Bibliographic record
Abstract
Abstract Background This retrospective study aimed to compare the outcomes of Day 3 double embryo transfer (DET) with single blastocyst transfer (SBT) during frozen embryo transfer (FET) cycles. A total of 999 women below the age of 38 years who underwent FET at Malaysia’s KL Fertility & Gynaecology Centre from January 2019 to December 2021 were analysed. Patients with autologous eggs were recruited in the study. All the eggs were inseminated by intracytoplasmic sperm injection. The embryos were vitrified on Day 3 cleavage-stage or blastocyst stage with Cryotop® method. The FET were performed following natural cycle (NC), modified natural cycle (m-NC) or hormone replacement therapy (HRT) cycles. The NC and m-NC groups received oral dydrogesterone for luteal phase support. Results There were no statistical differences in the rates of positive pregnancy, clinical pregnancy and ongoing pregnancy between the two groups. However, implantation rates were significantly higher in the SBT group (50.1% versus 37.6%, p < 0.05). The Day 3 DET group had significantly higher multiple pregnancy rates (28.7% versus 1.1%, p < 0.05). Subgroup analysis of embryo transfers performed following NC, m-NC or HRT cycles showed similar results. Conclusions This study suggests that SBT is the better choice for embryo transfers as it had higher implantation rates and its pregnancy rates were similar to Day 3 DET. The SBT also significantly reduced the incidence of multiple pregnancies without compromising pregnancy rates.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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".