Determinants of pain and functioning in hip osteoarthritis – a two-year prospective study
Bibliographic record
Abstract
OBJECTIVE: To identify predictors of pain and disability in hip osteoarthritis. DESIGN: A prospective analysis of determinants of pain and functioning in hip osteoarthritis. STUDY SETTING: Rehabilitation clinic in a central hospital. PATIENTS: A total of 118 men and women aged 55-80 years who had radiologically diagnosed hip osteoarthritis and associated clinical symptoms and participated in a randomized controlled trial. MAIN MEASURES: The self-reported disease-specific pain and physical function were assessed using the pain and functioning subscales of the Western Ontario and McMaster Universities (WOMAC) Osteoarthritis index. The self-reported generic physical and mental functioning were assessed by using the Finnish-validated SF-36-item Health Survey RAND-36 subscales for function and physical and mental component summary scores. Outcome measures were recorded at 0, 3, 6, 12, 18 and 24 months. RESULTS: Multivariate linear mixed model analyses revealed that lower disease-specific pain score and better functioning (WOMAC) were predicted by higher educational level (9.61 (3.15 to 16.07); 9.07 (2.05 to 16.09)), supervised exercise training (-10.13 (-17.87 to -2.39); -11.58 (-19.40 to -3.77)), habitual conditioning physical activity (-0.48 (-0.96 to -0.01); -0.39 (-0.84 to 0.05)), absence of comorbidities (-6.30 (-12.35 to -0.24); -7.87 (-14.45 to -1.30)) and absence of additional knee osteoarthritis (-7.62 (-13.87 to -1.36); -8.02 (-14.81 to -1.23)), respectively. The same factors, except for the comorbidities, also predicted general physical functioning score (RAND-36). CONCLUSIONS: Higher education, absence of knee osteoarthritis and comorbidities, supervised exercise training and habitual conditioning physical activity predicted a lower presence of pain and better functional status in patients with hip osteoarthritis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".