Anti-Müllerian hormone levels to predict oocyte maturity and embryo quality during controlled ovarian hyperstimulation
Bibliographic record
Abstract
The aim of this study was to assess the correlation between controlled ovarian hyperstimulation (COH) outcome parameters and anti-Müllerian hormone (AMH) serum levels during in vitro fertilization (IVF) treatment in women with varying ovarian reserve levels.Prospective study of 46 women undergoing GnRH-antagonist short protocol for IVF. Participants included women with low ovarian reserve (N.=11), normoreserve (N.=16), and polycystic ovarian syndrome (PCOS; N.=19). AMH was measured on menstrual cycle day 1-3 (basal AMH), on the day of GnRH-antagonist administration (AMH-GnRH), on the day of hCG administration (AMH-hCG), and in follicular fluid on the day of oocyte retrieval (AMH-FF).Basal AMH was significantly correlated (P<0.001) with antral follicle count and number of follicles >11mm on hCG day (P<0.05). Both basal AMH and AMH-GnRH were significantly correlated (P<0.05) with the number of oocytes retrieved and metaphase II. AMH-hCG was correlated with top quality embryos (P=0.04). No correlations were found between COH outcome parameters and AMH-FF.Basal AMH serum concentration was the strongest predictor of oocyte yield. AMH concentration at the mid-follicular phase was also a good predictor of oocyte yield and this marker was the only useful ovarian reserve indicator during the follicle growth process to predict IVF outcomes. AMH-hCG levels appear to predict embryo quality. AMH levels during the COH can provide valuable data to help individualize treatment and predict COH results.
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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".