Therapeutic Effects of Low Level Laser Therapy (LLLT) in Knee Osteoarthritis, Compared to Therapeutic Ultrasound
Bibliographic record
Abstract
INTRODUCTION: Low-level laser therapy (LLLT) is thought to have analgesic and biomodulatory effects. Our objective was to assess the pain-relieving effect of LLLT and possible changes in joint stiffness and disability of patients with knee osteoarthritis (KOA) and compare it to the more commonly used modality; therapeutic ultrasound(US). METHODS: 37 patients with mild or moderate KOA were randomized to receive either LLLT, placebo LLLT or US. All patients received a common treatment including acetaminophen (up to 2gr/d) and medical advices for lifestyle modification and exercise. Treatments were delivered 5 times a week over a period of 2 weeks. Active laser group was treated with a diode laser (wavelength 880 nm, continuous wave, power 50 mW) at a dose of 6 J/point (24 J/knee). The placebo control group was treated with an ineffective probe (power 0 mW) of the same appearance. The third group received pulsed ultrasound with an intensity of 1.5-2 w/cm2, and for 5 minutes per knee. Visual Analogue Scale (VAS) and Western Ontario MacMaster (WOMAC) questionnaires were used for data gathering before,1 and 3 months after completing the therapy. RESULTS: Pain reduced in all 3 groups but laser was superior in comparison. Stiffness improved 1 mo after therapy in the laser group but not in the others. Disability decreased in both laser and US groups (more significantly in the laser group) but not in the placebo group. CONCLUSION: Our results show that LLLT reduces pain, joint stiffness and disability in KOA and is superior to placebo and US.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".