Extracorporeal shockwave therapy improves pain and function in subjects with knee osteoarthritis: A systematic review and meta-analysis of randomized clinical trials
Bibliographic record
Abstract
Objective To examine the safety and effectiveness of extracorporeal shockwave therapy (ESWT) for reducing pain and improving functionality in people with knee osteoarthritis (KOA). Methods The Cochrane Library, PubMed, CINAHL, Physiotherapy Evidence Database (PEDro) and Google Scholar were systematically searched for randomized trials published up to September 30th of 2019. The main outcome measures to evaluate the treatment effect were pain, as reported on a visual analogue scale (VAS), and the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). Secondary outcome measures were the range of motion (ROM) and walking tests. A quantitative analysis was conducted using the inverse variance method and the random effects model. Results Fourteen studies were included (n = 782 participants and 877 knees). Moderate quality of evidence showed that ESWT causes a decrease on the pain VAS [mean difference (MD) = 1.7 cm; confidence interval (CI) 95%: 1.1–2.3] and WOMAC (MD = 13.9 points; CI 95%: 6.9–20.8). The effect of ESWT using medium energetic density was greater than with low or high density in the WOMAC (Chi 2 = 9.8, p = 0.002) and bordered statistical significance on the VAS (Chi 2 = 3.8, p = 0.05). Very low quality of evidence showed that ESWT causes moderate improvement in the knee ROM (MD = 17.5°; CI 95%: 9.4–25.5) and walking test [standardized mean difference (SMD) = 0.58; CI 95%: 0.35–0.81]. Conclusions ESWT is an effective treatment for improving pain and functionality in patients with KOA in the short term with few minor side effects . Further clinical trials should include longer follow-up periods and be designed to lower the risk of bias.
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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 | 0.018 | 0.044 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.026 | 0.028 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 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".