Comparison of Short-Term Effects of Extracorporeal Shock Wave Therapy, Low-Level Laser Therapy and Pulsed Electromagnetic Field Therapy in Knee Osteoarthritis: A Randomized Controlled Study
Bibliographic record
Abstract
Background: Knee osteoarthritis (OA) is the most prevalent form of osteoarthritis and a leading cause of chronic pain in adults. This study aimed to compare the short-term effects of extracorporeal shock wave therapy (ESWT), low-level laser therapy (LLLT), and pulsed electromagnetic field therapy (PEMF) on pain, function, and quality of life in patients with knee OA. Methods: A hundred and twenty patients with Kellgren–Lawrence grade 2–3 knee OA were randomized into four groups: ESWT (once a week for three sessions), LLLT (twice a week for eight sessions), PEMF (twice a week for eight sessions), and a control group with 30 patients in each group. All participants were instructed in a daily exercise program, including knee joint range of motion, stretching, and strengthening exercises (3 × 10 repetitions). Outcome measures, including the visual analog scale (VAS), the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), Short Form-36 (SF-36), and the Timed Up and Go (TUG) test, were assessed at baseline after treatment and at the third month. Results: There were no significant differences between groups at baseline regarding VAS, WOMAC, SF-36, and TUG scores (p > 0.05). Significant improvements were observed in all parameters post-treatment for all groups (p < 0.001). However, the improvements in the PEMF group were significantly lower than in the ESWT and LLLT groups, particularly for VAS, WOMAC pain, and SF-36 physical function scores (p < 0.05). No significant differences were found between ESWT and LLLT (p > 0.05). Conclusions: In the short-term, ESWT, LLLT, and PEMF effectively reduce pain, improve physical function, and enhance quality of life in patients with knee OA, though PEMF showed less pronounced improvements.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".