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Record W2157129285 · doi:10.1093/humrep/dep411

High prevalence of subtle and severe menstrual disturbances in exercising women: confirmation using daily hormone measures

2009· article· en· W2157129285 on OpenAlexaff
Mary Jane De Souza, Rebecca J. Toombs, Jennifer L. Scheid, Emma O’Donnell, Sarah West, Nancy I. Williams

Bibliographic record

VenueHuman Reproduction · 2009
Typearticle
Languageen
FieldMedicine
TopicExercise and Physiological Responses
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMenstrual cycleAmenorrheaAnovulationMedicineLuteal phaseOvulationHormoneGynecologyPhysiologyObstetricsInternal medicinePregnancyBiologyObesity

Abstract

fetched live from OpenAlex

BACKGROUND: The identification of subtle menstrual cycle disturbances requires daily hormone assessments. In contrast, the identification of severe menstrual disturbances, such as amenorrhea and oligomenorrhea, can be established by clinical observation. The primary purpose of this study was to determine the frequency of subtle menstrual disturbances, defined as luteal phase defects (LPD) or anovulation, in exercising women, with menstrual cycles of 26-35 days, who engage in a variety of sports, both recreational and competitive. Secondly, the prevalence of oligomenorrhea and amenorrhea was also determined via measurement of daily urinary ovarian steroids rather than self report alone. METHODS: Menstrual status was documented by daily measurements of estrone and pregnanediol glucuronide and luteinizing hormone across two to three consecutive cycles and subsequently categorized as ovulatory (Ovul), LPD, anovulatory (Anov), oligomenorrheic (Oligo) and amenorrheic (Amen) in sedentary (Sed) and exercising (Ex) women. RESULTS: Sed (n = 20) and Ex women (n = 67) were of similar (P > 0.05) age (26.3 +/- 0.8 years), weight (59.3 +/- 1.8 kg), body mass index (22.0 +/- 0.6 kg/m2), age of menarche (12.8 +/- 0.3 years) and gynecological maturity (13.4 +/- 0.9 years). The Sed group exercised less (P < 0.001) (96.7 +/- 39.1 versus 457.1 +/- 30.5 min/week) and had a lower peak oxygen uptake (34.4 +/- 1.4 versus 44.3 +/- 0.6 ml/kg/min) than the Ex group. Among the menstrual cycles studied in the Sed group, the prevalence of subtle menstrual disturbances was only 4.2% (2/48); 95.8% (46/48) of the observed menstrual cycles were ovulatory. This finding stands in stark contrast to that observed in the Ex group where only 50% (60/120) of the observed menstrual cycles were ovulatory and as many as 50% (60/120) were abnormal. Of the abnormal cycles in the Ex group, 29.2% (35/120) were classified as LPD (short, inadequate or both) and 20.8% (25/120) were classified as Anov. Among the cycles of Ex women with severe menstrual disturbances, 3.5% (3/86) of the cycles were Oligo and 33.7% (29/86) were Amen. No cycles of Sed women (0/20) displayed either Oligo or Amen. CONCLUSIONS: This study suggests that approximately half of exercising women experience subtle menstrual disturbances, i.e. LPD and anovulation, and that one third of exercising women may be amenorrheic. Estimates of the prevalence of subtle menstrual disturbances in exercising women determined by the presence or absence of short or long cycles does not identify these disturbances. In light of known clinical consequences of menstrual disturbances, these findings underscore the lack of reliability of normal menstrual intervals and self report to infer menstrual status.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.039
GPT teacher head0.300
Teacher spread0.261 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations299
Published2009
Admission routes1
Has abstractyes

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