Laser therapy versus pulsed electromagnetic field therapy as treatment modalities for early knee osteoarthritis: a randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: This randomized controlled trial aimed to compare the effects of pulsed electromagnetic field therapy (PEMFT) and low-level laser therapy (LLLT) on pain and physical function of participants with knee osteoarthritis (KOA). METHODS: According to the Kellgren-Lawrence classification, participants with grade 2-3 KOA were randomized to receive PEMFT or LLLT for six sessions lasting 15 min/session over a 3-week period. Pain at rest and when walking, standing from a sitting position, and climbing the stairs was assessed using the visual analog scale. Functional level was measured by the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), timed up-and-go test (TUG), and 10-m walk (10 MW) test. Measurements were obtained before and after the interventions. Significance was determined at p ≤ 0.05. RESULTS: Forty participants were included in the study. Pain and physical function improved significantly (p < 0.0001) in both groups. PEMFT was significantly more effective in reducing pain at rest, when standing from a sitting position, and when climbing the stairs, and in improving both WOMAC scores and TUG results (p ≤ 0.0003). The improvements in pain during the activities and the WOMAC scores reached the minimal clinically important difference. No adverse events occurred. CONCLUSION: Six sessions of PEMFT and LLLT had immediate positive effects on pain and physical function in individuals with low-grade KOA, with PEMFT resulting in significantly better results. TRIAL REGISTRATION: ISRCTN registry trial ID: ISRCTN17001174.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 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".