A 38 h interval between hCG priming and oocyte retrieval increases in vivo and in vitro oocyte maturation rate in programmed IVM cycles
Bibliographic record
Abstract
BACKGROUND: Our aim was to evaluate whether extending the interval between human chorionic gonadotrophin (hCG) priming and immature oocyte retrieval increases the oocyte maturation rate following in vitro maturation (IVM). METHODS: This study was performed retrospectively. IVM was performed on 113 polycystic ovary syndrome patients (n = 120 cycles). Oocyte collection was performed either 35 h (Group 1; n = 76) or 38 h (Group 2; n = 44) after 10,000 IU of hCG priming. Following oocyte retrieval, oocyte maturity was assessed and the remaining immature oocytes were cultured in IVM medium up to Day 2. RESULTS: The number of in vivo matured oocytes collected was significantly higher in Group 2 (13.6%, 114/840 versus 7.3%, 96/1312 in Group 1) (P < 0.01); the oocyte maturation rate after Day 1 was significantly higher (P < 0.01) in Group 2 (46.3 versus 36.0% in Group 1); and clinical pregnancy (40.9 versus 25%) and implantation rates (15.6 versus 9.6%) were better in Group 2 than those in Group 1. CONCLUSIONS: The results suggest that extending the period of hCG priming time from 35 to 38 h for immature oocyte retrieval promotes oocyte maturation in vivo and increases the IVM rate of immature oocytes. Therefore, oocyte retrieval after 38 h of hCG priming may improve subsequent pregnancy outcome in cycles programmed for IVM treatment.
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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 | 0.000 | 0.003 |
| 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 | 0.000 |
| 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".