Can in vitro maturation overcome cycles with repeated oocyte maturation arrest? A classification system for maturation arrest and a cohort study
Bibliographic record
Abstract
OBJECTIVE: To investigate the role of gonadotropin-stimulated and human chorionic gonadotropin (hCG) -primed in vitro oocyte maturation (IVM) in cases of repeated in vitro fertilization (IVF) failure due to various forms of oocyte maturation arrest (OMA). METHODS: Retrospective cohort study. RESULTS: In all, 63 women with IVF failure due to OMA were evaluated in this study. According to the Hatirnaz & Dahan classification, 11 (17.5%) women were OMA type 1, 22 (34.9%) were OMA type 2, 0 were OMA type 3, 11 (17.5%) were OMA type 4, and 19 women were OMA type 5 (30.1%). Fewer oocytes were retrieved in the IVM than in the IVF cycles. No embryos were produced from oocytes collected in the IVM cycles of women with OMA types 1, 2, and 4. In the OMA type 5 group, 9 (47.4%) day 2 embryos and 6 (31.6%) day 3 embryos were obtained. The difference between the groups was statistically significant (P = 0.001, P = 0.002, respectively). Single day 3 embryo transfer was performed for the six patients with OMA type 5 but no clinical pregnancies occurred. CONCLUSIONS: Follicle-stimulating hormone-stimulated and hCG-primed IVM does not improve oocyte maturation, developmental potential, or pregnancy rates of women with OMA. Future studies directed to re-establishing normal cytoskeletal architecture and machinery, and resumption of meiosis may be beneficial for obtaining mature oocytes.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 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".