Determinants of six-minute walk test performance in individuals with knee osteoarthritis
Bibliographic record
Abstract
Objective: The 6-minute walk test (6MWT), an Osteoarthritis Research Society International (OARSI)-recommended measure of physical function in knee osteoarthritis (OA), was originally developed to assess submaximal aerobic fitness in people with cardiovascular disease. The degree to which 6MWT performance reflects knee OA severity versus other patient factors remains unclear. Our objective was to assess the contributions of OA-related and non-OA-related patient characteristics to 6MWT performance in individuals with symptomatic knee OA. Design: In this cross-sectional study, participants scheduled for total knee arthroplasty completed the 6MWT and standardized questionnaires. Participant characteristics were compared by tertiles of 6MWT distance. Multivariable linear regression modelling was used to assess associations between patient factors and 6MWT distance. Results: Among 278 participants (mean age 67.1 years, 65.5% female, mean WOMAC pain 57.0, and mean 6MWT distance 323.1m), older age (adjusted beta coefficient -4.0 per year, 95% confidence interval [CI] -5.4, -2.5), female sex (adjusted beta [95% CI] -43.0 [-67.3, -18.7]), presence of obesity (adjusted beta [95% CI] -44.4 [-68.2, -20.5]), greater knee pain (adjusted beta [95% CI] per unit increase in WOMAC pain -1.12 [-2.1, -0.2]), worse knee-OA related function (adjusted beta [95% CI] per unit increase in KOOS-PS -1.1 [-2.0, -0.1]) were associated with shorter 6MWT distance. Greater arthritis coping efficacy (adjusted beta [95% CI] 5.2 [1.4, 9.0]) was associated with longer 6MWT distance. Conclusions: While 6MWT distance declines with greater knee OA symptom severity, other demographic, biomedical and psychosocial factors also significantly influence 6MWT performance. These should be considered when interpreting the 6MWT in this population.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".