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Record W4382938549 · doi:10.55905/oelv21n6-110

Clinical measures and gait parameters in individuals with knee Osteoarthritis: a comparison between men and women

2023· article· en· W4382938549 on OpenAlexaboutno aff
Valdeci Carlos Dioní­sio, Mariana Nunes Faria, Fabiana da Silva Soares, Vanessa Martins Pereira Silva Moreira, Daniel A. Furtado, Adriano Alves Pereira, AmirAli Jafarnezhad

Bibliographic record

VenueOBSERVATÓRIO DE LA ECONOMÍA LATINOAMERICANA · 2023
Typearticle
Languageen
FieldMedicine
TopicKnee injuries and reconstruction techniques
Canadian institutionsnot available
Fundersnot available
KeywordsWOMACIsometric exercisePhysical therapyMedicineOsteoarthritisGaitPsychosocialPhysical medicine and rehabilitationVisual analogue scaleMuscle strengthCorrelationMathematics

Abstract

fetched live from OpenAlex

This study aimed to compare men and women on muscle strength, pain, physical function, and gait spatiotemporal parameters at three speeds, verifying the correlation between variables. Forty-two individuals with KOA (21 women) participated in this cross-sectional study. They were assessed using the visual analog pain scale (VAS) and Western Ontario and McMaster Universities Index (WOMAC), lower limb isometric muscle strength, and gait kinematics on a treadmill at three speeds. The results revealed that women had worse clinical measures (WOMAC and muscle strength) (p < 0.006) and reduced step length (p < 0.05). The results also showed that women had more variables correlated with step length and stronger correlations (r = 0.33 to 0.83) than men. In conclusion, the moderate to strong correlation between step length and clinical measures observed for women suggests that step length could be a suitable parameter for assessing women with KOA. Also, the critical role of clinical measures indicates that it could be beneficial to associate the usual intervention with a psychosocial approach for women.

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)0.001
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 score0.187
Threshold uncertainty score0.700

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.031
GPT teacher head0.312
Teacher spread0.281 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueOBSERVATÓRIO DE LA ECONOMÍA LATINOAMERICANASame topicKnee injuries and reconstruction techniquesFrench-language works237,207