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Record W1983960218 · doi:10.3109/09638288.2010.520805

Correlation between single limb support phase and self-evaluation questionnaires in knee osteoarthritis populations

2011· article· en· W1983960218 on OpenAlexaboutno aff
Ronen Debi, Amit Mor, Ganit Segal, Ofer Segal, Gabriel Agar, Eytan M. Debbi, Nahum Halperin, Amir Haim, Avi Elbaz

Bibliographic record

VenueDisability and Rehabilitation · 2011
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsWOMACOsteoarthritisMedicinePhysical therapyQuartileGaitKnee painInternal medicineConfidence interval

Abstract

fetched live from OpenAlex

PURPOSE: To investigate the correlation between single limb support (SLS) phase (% of gait cycle) and the Western Ontario and McMaster University Osteoarthritis Index (WOMAC) questionnaire and Medical Outcomes Study 36-Item Short-Form Health Survey (SF-36 Health Survey) in patients with knee osteoarthritis (OA). METHOD: A prospective observational study was employed with 125 adults with bilateral medial compartment symptomatic knee OA who underwent a physical and radiographic evaluation. Velocity, step length and SLS were assessed by a computerised mat (GAITRite). Patients completed the WOMAC and SF-36 Health Survey questionnaires. RESULTS: Statistical analysis examined the correlations between SLS and both questionnaires, between Kellgren & Lawrence (K&L) scores and both questionnaires and between SLS correlations and K&L correlations. We found significantly stronger correlations between SLS and WOMAC-pain, WOMAC-function, the SF-36 pain sub-category, velocity and step length than between K&L scores and these parameters (Pearson's r = 0.50 vs. 0.26, 0.53 vs. 0.34, 0.50 vs. 023, 0.81 vs. 0.33, 0.77 vs. 0.37, respectively; all p < 0.05). Significant differences in SLS were found over WOMAC-pain, WOMAC-function and SF-36 overall score quartiles (p < 0.05 for all). CONCLUSION: We recommend integrating SLS as an objective parameter in the comprehensive evaluation of patients with knee OA.

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 score0.255
Threshold uncertainty score0.563

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 head0.042
GPT teacher head0.311
Teacher spread0.268 · 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

Citations52
Published2011
Admission routes1
Has abstractyes

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