Effectiveness of Kinesio taping and conventional physical therapy in the management of knee osteoarthritis: a randomized clinical trial
Bibliographic record
Abstract
BACKGROUND: Knee osteoarthritis (OA) is the most common kind of arthritis that occurs due to degeneration of the joint articular cartilage, producing pain, stiffness, and impaired movement. The objective of the study was to evaluate the short-term effectiveness of Kinesio taping (KT) plus conventional physical therapy (CPT) and CPT alone in subjects with knee OA. MATERIALS AND METHODS: Forty male subjects were divided into two groups at random using a parallel assignment, double-blinded study design, viz., KT with CPT (transcutaneous electrical nerve stimulation and exercise therapy), and CPT alone for the period of 6 weeks of treatment. At baseline, third, and sixth weeks, the following outcome measures were taken, such as pain intensity (NPRS), knee range of motion (goniometry), Western Ontario and McMaster Osteoarthritis Index (WOMAC), and the Time Up and Go (TUG) test. STATISTICAL ANALYSIS: To reveal the patient's demographic profile concerning the outcome parameters, a descriptive statistic was applied. Furthermore, two-way mixed ANOVA and Tukey HSD post hoc tests were used to analyze within and between-group comparisons in SPSS 20.0. RESULTS: In both groups, pain and knee flexion were significantly improved during the 6-week period of interventions (p < 0.05). WOMAC and TUG test scores improved only in the KT plus CPT group. CONCLUSION: KT combined with CPT was found to be more effective than CPT alone in the third and sixth weeks of the treatment. In knee OA, this combination of treatments was found to reduce pain, enhance range of motion, and improve physical functioning.
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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 | 0.004 |
| 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 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".