Interactions between serum FSH, inhibin B and antral follicle count in the decline of serum AMH during the menstrual cycle in late reproductive age
Bibliographic record
Abstract
Abstract Objective To investigate the hormonal interrelationships during the menstrual cycle in women of late reproductive age with suppressed serum AMH and antral follicle count (AFC). Methods Serum hormones (AMH, FSH, LH, estradiol, progesterone, inhibin A, inhibin B), AFC (2‐10 mm) and AMH/AFC ratio (an estimate of AMH/follicle) were assessed every 2‐3 days across the menstrual cycle in 26 healthy ovulatory women aged 18‐50 years. Results An 11‐fold fall in AMH/AFC was observed in women aged ≥45 years compared to those 18‐45 years ( P < .001). Although women ≥45 years exhibited normal menstrual cycle patterns of serum estradiol, progesterone, LH and inhibin A, FSH was elevated ( P < .001) and inhibin B suppressed ( P < .001) compared to the younger group. Overall FSH was inversely correlated ( r = .55, P < .05) and AMH directly correlated ( r = .88, P < .01) with AFC; however, these relationships were curvilinear and more pronounced when AFC was low. Inhibin B was directly linearly correlated ( r = .70, P < .01) with AFC across both high and low AMH/follicle groups. Conclusions It is hypothesized that the marked fall in AMH/follicle in late reproductive age is attributed to the change in the hormonal interplay between the pituitary and ovary. The fall in AFC leads to a decrease in inhibin B and a concomitant increase in FSH by a recognized feedback mechanism. It is postulated the elevated FSH suppresses AMH either directly or indirectly through oocyte‐specific growth factors leading to a marked fall in AMH/follicle. We propose that pituitary‐ovarian and intra‐ovarian regulatory systems underpin the accelerated fall in AMH/follicle during the transition to menopause.
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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 | 0.002 |
| 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".