Photobiomodulation therapy associated with supervised therapeutic exercises for people with knee osteoarthritis: a randomised controlled trial protocol
Bibliographic record
Abstract
BACKGROUND: Physical exercise, a cornerstone of the conservative management of knee osteoarthritis (KOA), is exhaustively recommended by important clinical guidelines. A strength therapeutic exercise program (STEP) relieves pain, improves physical function and ultimately ameliorates quality of life (QoL). Furthermore, photobiomodulation (PBM) has been used as an adjunct treatment for people with KOA; however, there are still controversial recommendations regarding its use on this population. Thus, we hypothesised that PBM, when associated with a STEP protocol on patients with KOA, could induce better clinical outcomes than a STEP protocol alone. METHODS AND ANALYSIS: The study is a 6-month triple-blind placebo-controlled randomised clinical trial with intention-to-treat analysis. The trial will include 120 people with clinic and radiographic signs of KOA. The intervention consists of a supervised STEP and PBM protocols conducted over an 8-week intervention period. Assessments are performed at baseline, right after treatment, and 3-month and 6-month follow-up periods. The primary clinical outcome is pain intensity according to a 10 cm Visual Analogue Scale. Secondary outcomes are the global Western Ontario & McMaster Universities Osteoarthritis Index; QoL assessed by the 36-item Short-Form health survey questionnaire; and performance-based physical parameters assessed by the 30 s chair stand test; the stair climb test; and the 40 m fast-paced walk test. ETHICS AND DISSEMINATION: The trial was approved by the Human Research Ethics Committee of the Federal University of São Carlos, São Paulo, Brazil (REC no 2.016.122). Results will be published in peer-reviewed journals. TRIAL REGISTRATION NUMBER: Brazilian Clinical Trials Registry (U1111-1215-6510).
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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 | 0.020 | 0.018 |
| Meta-epidemiology (narrow) | 0.007 | 0.003 |
| Meta-epidemiology (broad) | 0.015 | 0.005 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.009 | 0.005 |
| Insufficient payload (model declined to judge) | 0.062 | 0.009 |
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".