Determinants of Health-Related Quality of Life in Patients with Knee Osteoarthritis
Bibliographic record
Abstract
The purpose of this study was to compare the correlates of health-related quality of life between men and women, who were outpatients of knee osteoarthritis (knee OA) with three levels of exercise groups and four distinct age groups. This study also aimed to understand the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), and the Medical Outcome Study 36-item short-form general health survey measures (SF-36) for the different levels of physical activity (Recommended, Insufficient, and Inactive); and to explore the implications for a possible correlation of physical activity levels, and health-related quality of life (HRQoL), and WOMAC in patients with knee osteoarthritis. In this study, two hundred and seven patients with knee OA were participated. The self-response questionnaires including WOMAC, SF-36 and self-report containing sections on demographic characteristics and physical activity categories were assessed throughout one month period. In the results we found that patients with knee OA, who reported a higher level of physical activity (Recommended) showed significantly lower in some measures of WOMAC, and higher in HRQoL than their insufficient and inactive counterparts. Furthermore, ”Physical Function,” ”Pain,” ”Age,” ”Operation” and ”Recommended Physical Activity” were the significant explanatory factors of HRQoL in knee OA patients. The explained variance of these variables towards WOMAC was 30.2%. ”Physical Function” which accounted for 20.1%, has the highest predictability towards HRQoL. Our results concludes that reducing pain perception, enhancing physical function through reinforcing exercise habits in patients' exercise therapy, the HRQoL of the knee OA patients might be enhanced.
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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 | 0.000 | 0.003 |
| 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) | 0.001 | 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".