In vitro oocyte maturation for the treatment of infertility associated with polycystic ovarian syndrome: the French experience
Bibliographic record
Abstract
BACKGROUND: In vitro oocyte maturation (IVM) permits the use of immature oocytes in IVF. IVM does not require ovarian stimulation and so can be offered to patients at risk of ovarian hyperstimulation syndrome. METHODS: For this indication, we carried out 45 cycles of IVM in 33 women with polycystic ovarian syndrome (PCOS). RESULTS: A total of 509 cumulus-oocyte complexes was obtained; 276 (54.2%) oocytes matured in 24 h and 45 (8.8%) in 48 h. The normal fertilization (2PN) rate of oocytes matured in 24 and 48 h was 69.5 and 73.3% respectively. Among the 214 embryos obtained, 103 were transferred and 30 were frozen. Forty transfers were performed (2.5 embryos/transfer). Eleven women had a positive beta-hCG test (26.2% of pregnancies/puncture, 27.5% of pregnancies/transfer) and nine women had a clinical pregnancy (20.0% of pregnancies/puncture, 22.5% of pregnancies/transfer). Five babies have been born and one pregnancy is ongoing. Results of the clinical examination carried out at birth were normal. CONCLUSIONS: Our results show that IVM may be offered as an alternative to conventional IVF and to ovarian drilling in women with PCOS. The role of IVM in the therapeutic armamentarium for this condition should be further clarified.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 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".