Immediate effect of taping in physical performance of osteoarthritis of knee joint
Bibliographic record
Abstract
Background: Osteoarthritis (OA) is a degenerative joint disease which is an arthritic condition in which the articular cartilage has begun to erode and become soft and frayed. Current treatment is aimed at reducing symptoms and improving functions. Taping of the patella to pull it medially, followed by exercises, has been recently recommended for the treatment of knee OA. Aims and Objectives: This study aims to study the effect of taping in improving physical performance of OA of knee joint. Materials and Methods: The research project was conducted after getting clearance from Human Research Ethics Committee of the H M Patel Institution for Education and Research center. In this randomized control trial study, 50 subjects were included from the Outpatient Department of the Physiotherapy, Shree Krishna Hospital. Participants were divided into two groups; there were 25 participants in each group. One group received only exercise and the other group received tapping along with exercise. Outcomes were measured by Western Ontario and McMaster Universities OA Index (WOMAC) and timed up and go test (TUG). Results: Data are analyzed by finding P value. And also by correlating between prevalues and postvalues of outcomes measured. There was statistically significant improvement in WOMAC (P < 0.001) as well as TUG (P = 0.058), in the group which includes both taping and exercises. There was statistically significant improvement in WOMAC (P < 0.002) in the group which included only exercises, whereas there was no statistically significant improvement in TUG (P = 0.123). Conclusion: Taping is effective to improve the functional outcome of the patients with the OA of knee joint. [Natl J Physiol Pharm Pharmacol 2018; 8(4.000): 470-474]
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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) | 0.001 | 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) | 0.004 | 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".