Is Kinesio Taping Effective for Knee Osteoarthritis? Randomised, Controlled, Double-blind Study
Bibliographic record
Abstract
OBJECTIVE: To determine the effects of Kinesio taping on pain, functional performance, range of motion, and postural stability in patients with knee osteoarthritis. STUDY DESIGN: Randomised double-blind controlled trial. PLACE AND DURATION OF STUDY: Department of Physical Medicine and Rehabilitation, University of Health Sciences, Izmir Bozyaka Training and Research Hospital, Turkey, from November 2019 to October 2021. METHODOLOGY: Fifty-seven patients with knee osteoarthritis (grade II or higher) according to the Kellgren-Lawrence classification received Kinesio tape or sham-Kinesio tape on the rectus femoris muscle three times a week. Patients were evaluated using the visual analogue scale (VAS), Western ontario and McMaster Universities Osteoarthritis Index (WOMAC), 50-meter walk time, range of motion (ROM), and postural stability index at baseline, 1st hour, 3rd week, 7th week. A mixed model analysis of repeated measures was used to test the effect of KT on outcome measures. Calculations were based on an intention-to-treat analysis. RESULTS: The only significant difference between groups was in the dynamic medio-lateral stability index [F (2.6,144.1)=3.83, p=0.015], indicating the inferiority of KT at week 3. There were differences within groups in 50-meter walking time and VAS at rest, which showed improvements over time in both groups. No significant difference was found between or within groups for other outcomes. CONCLUSION: The KT intervention for three consecutive weeks showed no superiority over sham-KT in terms of pain intensity, knee-related health status, knee ROM, functional performance, and postural stability. KEY WORDS: Kinesio taping, Knee osteoarthritis, Pain, Gait, Functions.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".