Anti-Mullerian hormone levels do not predict response to pulsatile GnRH in women with hypothalamic amenorrhea
Bibliographic record
Abstract
Pulsatile GnRH is used to induce ovulation in women with hypothalamic amenorrhea (HA), but tools to predict response are lacking. We assessed whether baseline AMH levels are associated with response to pulsatile GnRH in 16 women with HA. AMH levels were compared between non-responders and women who achieved follicular development or pregnancy. Median AMH for the cohort was 2.2 ng/mL. AMH levels were undetectable or low in four women, normal in nine and high in three. Follicular development was observed in 13 (81%) women (82% of cycles) and pregnancy achieved in 10 (63%) women (29% of cycles). All four women with low or undetectable AMH had follicular response and three achieved pregnancy. Of the 12 women with normal or high AMH, 10 had a follicular response and seven achieved pregnancy. Median AMH levels were comparable in those who achieved follicular development and those who did not (2.2 ng/mL versus 1.3 ng/mL, p = 0.78) and in those who became pregnant and those who did not (2.2 ng/mL versus 1.9 ng/mL, p = 0.52). In summary, low AMH does not preclude response to ovulation induction in women with HA, suggesting that ovarian potential may not be the primary determinant of AMH concentrations in this population.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".