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Record W4404600955 · doi:10.1038/s41598-024-79729-w

Endurance and electromyographic assessment of abdominopelvic motor control in women with primary dysmenorrhea: a cross-sectional study

2024· article· en· W4404600955 on OpenAlexaboutno aff
Rebeca del Prado-Álvarez, Cecilia Estrada-Barranco, Ángel González-de-la-Flor, Marta de la Plaza San Frutos, Jaime Almazán-Polo, Fabien Guérineau, María-José Giménez, Maríá García-Arrabé

Bibliographic record

VenueScientific Reports · 2024
Typearticle
Languageen
FieldMedicine
TopicMenstrual Health and Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMenstrual cycleElectromyographyPhysical therapyCross-sectional studyPhysical medicine and rehabilitationObservational studyMenstruationInternal medicinePathologyHormone

Abstract

fetched live from OpenAlex

Primary dysmenorrhea (PD), a prevalent menstrual condition characterized by pelvic pain during the menstrual cycle, significantly impacts the quality of life of women and produces increased pain sensitivity that can persist throughout the menstrual cycle. However, scientific literature has not studied whether there are implications for alterations in muscle function and endurance in the abdominopelvic region during the non-painful phases of the menstrual cycle. The aim of this study was to compare muscle function and endurance capacity in the abdominopelvic region in women with PD versus women without this condition. An observational, cross-sectional study was designed to analyze muscle activation and endurance capacity using electromyography (EMG) during McGill exercises. Forty-four women were included, 22 with PD and 22 without dysmenorrhea. The results did not indicate significant differences in muscle activation and endurance of the abdominopelvic musculature between the two groups (p > 0.05). However, the analysis suggests that women with primary dysmenorrhea might develop compensatory strategies that allow them to maintain physical function despite their condition. These results suggest that the approach to PD could focus more on pain management rather than physical functionality, and more studies are needed from a comprehensive approach to more accurately evaluate the relationship between PD and muscle function.

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 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)0.002
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 score0.017
Threshold uncertainty score0.401

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.010
GPT teacher head0.312
Teacher spread0.302 · 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 teacher head, 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

Citations6
Published2024
Admission routes1
Has abstractyes

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