Effectiveness of Kinesio Taping on the Management of Knee Osteoarthritis: A Systematic Review of Randomized Controlled Trials
Bibliographic record
Abstract
Haimanot Melese,1 Abayneh Alamer,1 Melaku Hailu Temesgen,1 Fetene Nigussie2 1Department of Physiotherapy, School of Medicine, College of Health Sciences and Ayder Comprehensive Specialized Hospital, Mekelle University, Mekelle, Ethiopia; 2Department of Nursing Institute of Medicine, College of Health Sciences, Debre Berhan University, Debre Berhan, EthiopiaCorrespondence: Abayneh Alamer Tel +251 922276256Fax +251 344416681/91Email abayphysio@gmail.comAbstract: The purpose of this review was to summarize the current best evidence for the effectiveness of Kinesio Taping in reducing pain and increasing knee function for patients with knee osteoarthritis. A comprehensive search of literature published between 2014 and 2019 was conducted using the following electronic databases: PubMed, Google Scholar, Physiotherapy Evidence Database (PEDro), Science Direct, and Scopus. Only randomized controlled trials evaluating the effect of Kinesio Taping on knee osteoarthritis were included. PEDro was used to assess the risk of bias of included trials. This study was reported according to the guideline of the PRISMA statement. The methodological quality of the studies was done using the PEDro scale and GRADE approach. The overall quality of evidence was rated from moderate to high. Eighteen randomized trials involving 876 patients were included. The present systematic review demonstrated that there were significant differences between Kinesio Taping groups and control groups in terms of visual analog scale (VAS), Western Ontario and MacMaster Universities Osteoarthritis Index (WOMAC) scale and flexion range of motion. Kinesio Taping is effective in improving pain and joint function in patients with knee OA.Keywords: Kinesio Taping, osteoarthritis, knee joint, systematic review
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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 | 0.021 | 0.073 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.015 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".