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Alterations In Performance And Perceived Fatigability In Hormonal Contraceptive Users

2024· article· en· W4404007454 on OpenAlexaff
Brooklyn Wiggins, Sophie-Jayne Morgan, Jenny Zhang, Kirsty J. Elliott‐Sale, Patricia K. Doyle–Baker, Jalal Aboodarda

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2024
Typearticle
Languageen
FieldMedicine
TopicHormonal and reproductive studies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsHormoneHormonal contraceptionPsychologyMedicineFamily planningInternal medicinePopulationResearch methodologyEnvironmental health

Abstract

fetched live from OpenAlex

Exercise tolerance, characterized by an integration of neurophysiological and perceptual responses, has demonstrated contradictory profiles across the menstrual cycle. PURPOSE: This ongoing study aims to investigate the effects of endogenous and exogenous ovarian hormonal changes on determinants of exercise tolerance. METHODS: After a ramp-incremental test, combined monophasic oral contraceptive pill (OCP) and hormonal intrauterine device users (hIUD) (n = 7 in each group; 22 ± 1.2 yrs) completed two randomized visits whereby a cycling protocol at 5% below respiratory compensation point to task failure was performed. In OCP, sessions were performed in the active and inactive pill phases, randomly, and in hIUD, sessions were separated by ~14 days. Neuromuscular evaluations, including isometric knee extension maximal voluntary contraction (MVC) superimposed with electrical stimulation of the femoral nerve and transcranial magnetic stimulation of the motor cortex, were performed at baseline, every 5 min during cycling, and at task failure. Effort, pain, fatigue, and dyspnea were recorded at the same time intervals as neuromuscular evaluations. RESULTS: There was no significant difference between the OCP and IUD for all performance fatigability measures. Task duration was 43.9 ± 17.9 vs. 39.1 ± 13.2 min in the active vs. non-active pill phase in OCP and 41.5 ± 17.8 vs. 46.0 ± 19.9 min in the first vs. second visit in IUD, respectively (p = 0.128). Pre- to post-MVC decline was -14.0 vs. -21.1% in OCP and -25.9 vs. -25.6% in IUD (p = 0.374). Pre- to post-potentiated twitch decline was -32.8 vs. -34.3% in OCP and -37.8 vs. -33.6% in IUD (p = 0.526). Pre- to post-changes in voluntary activation were -6.9 vs. -3.6% in OCP and -6.6 vs. -5.6% in IUD (p = 0.307). There was no significant difference in the kinetics of effort, pain, fatigue, and dyspnea sensations across cycling tasks in the two experimental visits between OCP and IUD. CONCLUSIONS: During a warm weather race, TDEV displayed overall good agreement with a mean bias of -0.21 ± 0.48°C compared to TGI and fair agreement at race finish with a mean bias of -0.10 ± 0.6°C, therefore it is not equipped to diagnose exertional heat stroke. Continued validation and enhancement of the algorithm for TDEV in future, adequately powered studies with varying populations, environmental conditions, intensities, equipment and clothing worn, and at the upper limits of hyperthermia (i.e. >39.5°C) are needed to establish appropriate validity for use during training and competition.

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)0.000
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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)0.0020.000

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 head0.020
GPT teacher head0.297
Teacher spread0.278 · 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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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