The Effects of Progressive Resistance Strength Training on Pain, Mobility and Activities of Daily Living among Knee Osteoarthritis Patients: A randomized controlled trial
Bibliographic record
Abstract
ABSTRACT Objective The objective of this study was to investigate the effects of progressive resistance strength training of lower limb rehabilitation protocol (LLRP) on pain, activities of daily living (ADL) and mobility among knee OA patients who are overweight or obese. Materials and Methods Fifty-six overweight or obese knee OA patients were included and randomly assigned to a Rehabilitation Protocol Group (RPG) or Control Group (CG). The patients in the RPG performed the progressive resistance strength training of LLRP and followed the instructions of daily care (IDC) for duration of twelve weeks at home. The patients in the CG followed the IDC (conventional treatment) only. Outcome measures were assessed at baseline and after the interventions in both groups by comparing the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) score for pain, Timed Up and Go (TUG) test score for mobility and Katz Index of Independence scores for ADL. Results The patients in the RPG reported significant improvements in WOMAC score for pain (p = 0.001), Katz Index of Independence scores for ADL (p = 0.003) and TUG test score for mobility (p = 0.004). The patients in the CG also reported significant improvements in WOMAC score for pain (p = 0.002) and ADL (p = 0.052), but not in mobility score (p = 0.065). The improvement in the pain and ADL scores was greater in the patients of RPG than the CG with p-value of 0.001 and 0.000 respectively. Conclusion The progressive resistance strength training of LLRP is effective in terms of reducing pain, improving mobility and ADL among knee OA patients who are overweight or obese.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".