Energy availability discriminates clinical menstrual status in exercising women
Bibliographic record
Abstract
BACKGROUND: Conditions of low energy availability (EA) (<30 kcal/kgLBM) have been associated with suppressed metabolic hormones and reductions in LH pulsatility in previously sedentary women during short-term manipulations of energy intake (EI) and exercise energy expenditure (EEE) in a controlled laboratory setting. The purpose of this study was to examine if EA, defined as EA = (EI-EEE)/kgLBM, is associated with disruptions in ovarian function in exercising women. METHODS: Menstrual status was confirmed with daily measures of urinary reproductive metabolites across 1-3 menstrual cycles or 28-day monitoring periods. EA was calculated for exercise days using EI from 3-day diet logs, EEE from heart-rate monitors and/or exercise logs for a 7-day period, and body composition from DXA. Resting energy expenditure (REE) was measured by indirect calorimetry. Total triiodothyronine (TT3) was measured from a fasting blood sample. RESULTS: 91 exercising women (23.1 ± 0.5 years) were categorized clinically as either exercising amenorrheic (ExAmen, n = 30), exercising oligomenorrheic (ExOligo, n = 20) or exercising eumenorrheic (ExEumen, n = 41). The eumenorrheic group was further divided into more specific subclinical groups as either exercising ovulatory (ExOv, n = 20), exercising inconsistent (ExIncon, n = 13), or exercising anovulatory (ExAnov, n = 8). An EA threshold of 30 kcal/kgLBM did not distinguish subclinical menstrual status (χ (2) = 0.557, p = 0.46) nor did EA differ across subclinical disturbance groups (p > 0.05). EA was lower in the ExAmen vs. ExEumen (30.9 ± 2.4 vs. 36.9 ± 1.7 kcal/kgLBM, p = 0.04). The ratio of REE/predicted REE was lower in the ExAmen vs. ExEumen (0.85 ± 0.02 vs. 0.92 ± 0.01, p = 0.001) as was TT3 (79.6 ± 4.1 vs. 95.3 ± 2.9 ng/mL, p = 0.002). CONCLUSIONS: EA did not differ among subclinical forms of menstrual disturbances in a large sample of exercising women, but EA did discriminate clinical menstrual status, i.e., amenorrhea from eumenorrhea.
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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 | 0.001 |
| 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".