The Dose-Related Effects of Extracorporeal Shock Wave Therapy for Knee Osteoarthritis
Bibliographic record
Abstract
OBJECTIVE: To investigate the dose-related effects of extracorporeal shock wave therapy (ESWT) for knee osteoarthritis. METHODS: Seventy-five subjects were recruited, 60 of which met the inclusion criteria. The patients were randomly classified into two groups: group L, which was a low-energy group (n=30; 1,000 shocks/session; energy flux density [EFD], 0.040 mJ/mm(2)) and group M, which was a medium-energy group (n=30; 1,000 shocks/session; EFD, 0.093 mJ/mm(2)). For each group, 1,000 shock waves were delivered to the medial tibial plateau area, once a week, for 3 weeks. The main outcome measures were the visual analogue scale (VAS), the Roles and Maudsley (RM) score, the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) score, and the Lequesne index. Each assessment was performed at the baseline and at 1, 4, and 12 weeks after ESWT. RESULTS: In both groups, the VAS, the RM and WOMAC scores, and the Lequesne index were significantly improved over time (p<0.001), and group M showed greater improvement over group L at the 1, 4 and 12 weeks assessments. CONCLUSION: In this study, medium-energy group (group M) showed greater improvement in regard to relieving pain and restoring functional outcome than the low-energy group (group L). Therefore, EFD can be considered to have significant influence when treating with ESWT for knee osteoarthritis.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".