Efficacy of pulsed electromagnetic field therapy in the treatment of knee osteoarthritis: A double-blind, randomized-controlled trial
Bibliographic record
Abstract
Objectives: This study aims to evaluate the efficacy of combined pulsed electromagnetic field (PEMF) treatment and physical therapy on pain, stiffness, and functional limitation in patients with knee osteoarthritis (OA). Patients and methods: In this double-blind, randomized-controlled study, a total of 70 female patients with primary knee OA (mean age: 59.74±9.82 years; range, 40 to 80 years) were randomly allocated into PEMF and sham groups between March 2014 and July 2015. Both groups received 15 sessions of physical therapy over three weeks. Additionally, the PEMF group received PEMF treatment for 30 min/day, while the control group received sham PEMF. The patients were assessed by the Visual Analog Scale (VAS), Western Ontario and McMaster Universities Arthritis Index (WOMAC), and the Physician Global Assessment (PGA) scale before and three and seven weeks after treatment. Results: Regardless of the group, all patients' pain levels were significantly improved in both scales at three and seven weeks after treatment (p<0.001). The PEMF group had significantly less pain than the sham group based on the VAS score (p=0.003). The PEMF group had significantly lower functional limitation and stiffness at seven weeks (p=0.008). Recovery ratios based on the PGA score were significantly higher in the PEMF group both at three and seven weeks (p<0.05). Conclusion: Patients with knee OA who receive PEMF therapy in addition to physical therapy have more pain reduction and physical improvement. Based on these findings, PEMF is a safe and well-tolerated treatment of choice in this patient population.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".