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Record W2139494743 · doi:10.1186/s12970-015-0072-0

Energy availability discriminates clinical menstrual status in exercising women

2015· article· en· W2139494743 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of the International Society of Sports Nutrition · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle metabolism and nutrition
Canadian institutionsUniversity of Ottawa
FundersMedical Research and Materiel CommandNational Center for Advancing Translational SciencesU.S. Department of Defense
KeywordsMedicineSubclinical infectionInternal medicineMenstrual cycleEnergy expenditureEndocrinologyClinical nutritionExercise physiologyBasal metabolic rateResting energy expenditureHormonePhysiology

Abstract

fetched live from OpenAlex

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.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.074
Threshold uncertainty score0.234

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.023
GPT teacher head0.290
Teacher spread0.267 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it