Effect of low-level laser therapy (904 nm) and static stretching in patients with knee osteoarthritis: a protocol of randomised controlled trial
Bibliographic record
Abstract
BACKGROUND: Osteoarthritis (OA) is a highly prevalent and disabling disease. It is estimated that by 2030 the prevalence of symptomatic OA could reach 30 % of the population above 60 years. This randomised controlled trial will investigate the effect of low-level laser therapy (LLLT) and static stretching exercises, as monotherapy and in combination, on pain, quality of life, function, mobility, knee range of motion (KROM) and hamstring shortening in participants with knee OA. METHODS: This study will involve 145 people aged 50-75 years with symptomatic-radiographic knee OA. It will consist of two types of treatments: Low-level laser therapy (LLLT) and stretching exercises. The patients will be randomly allocated to five groups LLLTACTIVE+Stretch, LLLTPLACEBO+Stretch, Stretch, LLLT and Control (n = 29 each). Treatment frequency will be three sessions/week for all active groups. LLLT will involve the use of a Gallium-Arsenide laser (904 nm, 40 milliwatts, 3 J/point, 27 J/knee) over 24 sessions for the monotherapy group and 9 sessions for the LLLT+Stretch groups. Stretching will consist of seven exercises completed over 24 sessions. The control group will receive a booklet. Participants will be treated for 2 months (Stretch, LLLT and Control groups) or 3 months (LLLT + Stretch groups). Participants and the outcome assessor will be blind to treatment allocation throughout the study. The primary outcome is pain measured by Visual Analogue Scale. Secondary outcomes include quality of life assessed by Western Ontario and McMaster Universities Arthritis Index, function by Lequesne Algofunctional Index, mobility by Timed Up and Go Test, KROM by goniometry of knee flexion and hamstring shortening by popliteal angle. The statistical method will follow the principles of per-protocol analysis. DISCUSSION: Although exercise therapy is considered an effective treatment in patients with knee osteoarthritis, the knowledge of which exercise modalities would be the most appropriate for this population is lacking. LLLT has been used as resource to increase the effects of physical therapy. However, the specific dose and treatment frequency need to be better defined. The findings from this randomised controlled trial will provide evidence of the efficacy or otherwise, of LLLT and stretching exercises in the management of knee OA symptoms. TRIAL REGISTRATION: NCT01738737 at ClinicalTrials.gov.
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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 | 0.022 | 0.029 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.007 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.010 | 0.005 |
| Insufficient payload (model declined to judge) | 0.042 | 0.005 |
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".