Effect of Shock Wave Therapyversus Corticosteroid Injection in Management of Knee Osteoarthritis
Bibliographic record
Abstract
Background: knee Osteoarthritis is the most common cause of musculoskeletal pain and disability. Shockwaves have been used as an alternative treatment for musculoskeletal disorders; intra-articular injection of steroid is a common treatment for osteoarthritis of the knee. This study aimed to investigate the efficacy of Shock wave therapy versus Corticosteroid intra articular injection in case of knee osteoarthritis.Methods: Sixty patients were diagnosed mild to moderate knee osteoarthritis; they were included in the study. Their ages were 43:65 years with mean age 50 ± 3.5 years. Patients were divided randomly into three equal groups, group (A) received shock wave therapy, group (B) received two intra-articular injections of corticosteroid at 1-month intervals and group (C) received sham shock wave. The outcome measurements were Western Ontario and McMaster Universities arthritis index (WOMAC) values, knee ROM, and pain severity using the visual analogue scale (VAS) were recorded. The patients were evaluated for these parameters before allocated in their groups then after 1, 2, and 6months later.Results: compared to sham group there were significant improvement of VAS and ROM of shock wave group and corticosteroid injection group than sham (placebo) group (p<0.000), (p<0.006, and 0.02) respectively. Furthermore there was significant improve of shock wave group than corticosteroid injection group where p was <0.000 for VAS, ROM and (WOMAC).Conclusion: The results of this study suggested that shock wave therapy may provide effective modality for relieving pain, increase Range of motion and improve function in knee osteoarthritis patient than intra articular corticosteroid injection.
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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) | 0.001 | 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) | 0.003 | 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".