Effects of Kinesiotaping along with Quadriceps Strengthening Exercises on Pain, Joint Range of Motion and Functional Activities of Knee in Subjects with Patellofemoral Osteoarthritis
Bibliographic record
Abstract
Background: Patello femoral Osteoarthritis is the most common degenerative disease in older age group, causing pain, physical disability, and decreased quality of life.As many treatment options available, kinesiotaping is an efficacious treatment for management of pain & disability in patellofemoral joint osteoarthritis. Previous studies have shown that kinesiotaping as well as quadriceps strengthening significantly yields functional benefits. But there is lack of evidence revealing combined effectiveness & effects of kinesiotaping along with quadriceps strengthening in subjects with patellofemoral joint osteoarthritis.Methods: 30 subjects with symptoms of patellofemoral osteoarthritis fulfilled the inclusion criteria were randomly assigned into 2 groups of 15 in each group. Taping along with quadriceps strengthening program is compared to the quadriceps strengthening program alone. Pain were measured by Visual Analogue Scale (VAS), knee ROM were measured by Goniometer, Functional status were measured by Western Ontario McMaster Universities index (WOMAC), score. Measurements were taken pre & post intervention.Results: The results indicated that kinesiotaping along with quadriceps strengthening exercises showed there was statistically significant improvement in pain (<0.05), knee ROM (<0.05) and functional activities (<0.05) after 6 weeks compared to quadriceps strengthening alone.Conclusion: Subjects with kinesiotaping along with quadriceps strengthening showed significant improvement in reducing pain, in improving ROM & functional activities at the end of 6th week treatment when compared to subjects with patellofemoral osteoarthritis underwent quadriceps strengthening exercises alone.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".