Clinical efficacy of extracorporeal shockwave therapy for knee osteoarthritis: a systematic review and meta-regression of randomized controlled trials
Bibliographic record
Abstract
Objective:This study determined the clinical efficacy of extracorporeal shockwave therapy and the predictors of its efficacy for knee osteoarthritis.Data Sources:Electronic databases and search engines, namely MEDLINE, PubMed, EMBASE, Cochrane Library Database, Physiotherapy Evidence Database (PEDro), China Academic Journals Full-text Database, and Google Scholar, were searched until 5 March 2019, for randomized controlled trials without restrictions on language and publication year.Review Methods:Eligible trials and extracted data were identified by two independent investigators. The included articles were subjected to a meta-analysis and risk of bias assessment. Outcomes of interest included treatment success rate, pain, and physical function outcomes. A meta-regression analysis was performed to determine the predictors of treatment outcomes following shockwave therapy.Results:We included 50 trials (4844 patients) with a median (range) PEDro score of 6 (5–9). Meta-analyses results revealed an overall significant effect favoring shockwave therapy on the treatment success rate (odds ratio 3.22, 95% confidence interval (CI) 2.21–4.69, P < 0.00001; heterogeneity (I2) = 62%), pain reduction (standardized mean difference (SMD) −2.02, 95% CI −2.38 to −1.67, P < 0.00001; I2 = 95%), and Western Ontario and McMaster Universities Osteoarthritis Index function outcome (SMD −2.71, 95% CI −3.50 to −1.92, P < 0.00001; I2 = 97%). Follow-up duration and energy flux density were independent significant predictors of shockwave efficacy.Conclusion:Shockwave therapy is beneficial for knee osteoarthritis. Shockwave dosage, particularly the energy level and intervention duration, may have different contributions to treatment efficacy.
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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 | 0.042 | 0.085 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.030 | 0.059 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".