Effect of Stratified Exercise Therapy Versus Standard Physiotherapy on Pain and Function in Subjects with Knee Osteoarthritis
Bibliographic record
Abstract
Knee Osteoarthritis (OA) is a common degenerative condition among the elderly, leading to pain and functional limitations. While standard physiotherapy is routinely used to manage symptoms, stratified exercise therapy, an approach tailored to patient subgroups based on specific characteristics, is less commonly applied in orthopedic settings. This quasi-experimental study aimed to compare the effectiveness of stratified exercise therapy versus standard physiotherapy in reducing pain and improving function in individuals with Grade 2 and 3 Knee OA. A total of 180 participants with a mean age of 52 years were clinically diagnosed with Knee OA and randomly assigned to two groups. Group A (n=135) was subdivided into three subgroups based on BMI and upper leg muscle strength and received stratified exercise therapy. Group B (n=45) received standard physiotherapy. Both interventions were administered for over 12 weeks. Outcomes were assessed using the Visual Analogue Scale (VAS) for pain and the Western Ontario and McMaster University Osteoarthritis Index (WOMAC) for function. ANOVA and post hoc analyses revealed that while both groups showed significant improvements, stratified exercise therapy resulted in greater reductions in pain and improvements in function. These findings suggest that stratified exercise therapy may be a more effective option for managing Knee Osteoarthritis compared to standard physiotherapy.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".