Antimüllerian hormone, antral follicle count and ovarian volume predict menstrual cycle length in healthy women
Bibliographic record
Abstract
OBJECTIVE: Although menstrual cycle length is one of the main concerns of women and may have important health consequences, little is known about its predictors. The aim of this study was to identify predictors of menstrual cycle length variability in healthy women. DESIGN: Prospective cross-sectional study. PATIENTS: Two hundred healthy women aged 21-45. MEASUREMENTS: A questionnaire was administered to determine lifestyle factors. Ovarian parameters, metabolic parameters, pituitary hormones, sex steroids and antimüllerian hormone (AMH) were measured. RESULTS: Women with long (≥35 days) and normal (25-34 days) menstrual cycles had >5-fold and >2-fold higher serum AMH levels, respectively, compared to those with short cycles (<25 days). Menstrual cycle length was associated with age but not lifestyle factors. Only one factor group (AMH, antral follicle count [AFC], ovarian volume, testosterone and LH) was significantly associated with menstrual cycle length. Within this factor group, only the ovarian parameters (AMH, AFC, ovarian volume) predicted menstrual cycle length. Each SD increase in AMH (32·9 pmol/l) and ovarian volume (2·29 cm(3) ) was associated with 2·80-fold (95% CI: 1·67-4·69) and 1·62-fold (95% CI: 1·08-2·43) increased risks, respectively, for longer menstrual cycles. CONCLUSIONS: AMH, AFC and ovarian volume are positively associated with menstrual cycle length in healthy women. Our identification of AMH as an independent predictor of menstrual cycle length puts forth a new notion of utilizing menstrual cycle length to predict possible AMH-dependent/-associated outcomes. In addition, this novel relationship may facilitate the interpretation of AMH levels and its clinico-pathological significance across different centres.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".