The efficacy of extracorporeal shock wave therapy for knee osteoarthritis : an umbrella review
Bibliographic record
Abstract
BACKGROUND: An umbrella review was conducted to compare the effectiveness of extracorporeal shock wave therapy (ESWT) versus non-ESWT in the treatment of knee osteoarthritis (KOA). MATERIALS AND METHODS: Three databases including PubMed, Embase and Web of science were searched up to September 2023. Literature screening, quality evaluation, and data extraction were performed according to inclusion and exclusion criteria. Meta-analysis of outcome indicators was performed using Revman 5.4 software. RESULTS: A total of eight meta-analysis were included in this umbrella review. All meta-analysis were graded against a Measurement Tool to Assess Systematic Reviews 2 (AMSTAR 2) and scored between 8 and 11. Compared to the sham group, the ESWT group showed better results in WOMAC (Western Ontario and McMaster Universities Arthritis Index) [mean difference (MD)=-2.94, 95% CI: -5.52, -0.37, P=0.03, I²=60%], Visual Analog Scale (VAS) (MD=-2.0, 95% CI: -2.5, -1.5, P<0.01, I²=0%), range of motion (ROM) (MD=17.55, 95% CI: 13.49, 21.61, P<0.00001, I²=0%), and Lequesne index (MD=-2.85, 95% CI: -3.64, -2.07, P<0.00001, I²=48%). CONCLUSION: Based on the results of our analysis, ESWT is now an effective therapy for improving pain and function in patients with KOA.
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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 | 0.014 | 0.039 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.009 |
| Bibliometrics | 0.020 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.001 |
| 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".