Short-Term Efficacy of High-Intensity Laser Therapy in Alleviating Pain in Patients with Knee Osteoarthritis: A Single-Blind Randomised Controlled Trial
Bibliographic record
Abstract
Objectives. The aim of the study is to evaluate the efficacy of high-intensity laser therapy (HILT) on pain reduction in patients with knee osteoarthritis (OA). Methods. Forty-two patients diagnosed with primary knee OA, with a Kellgren–Lawrence classification of 2–4, were recruited into the study. The patients were randomly allocated to two groups: HILT and control. The intervention group received HILT (energy density of 22.39 J/cm2, 562.5 joule/session), while the control group received a sham laser, which was done 2–3 sessions per week for a total of 10 sessions. Both the groups also received the same conservative treatment. The main outcome measures were the visual analogue scale (VAS) and the modified Thai version of the Western Ontario and McMaster Universities Osteoarthritis Index (T-WOMAC) which were evaluated at baseline and immediately after treatment completion. Results. At the end of the study, the overall analysis showed a significant decrease in VAS and T-WOMAC scores in both the groups; a greater decrease in scores was found in the HILT group than in the control group ( p < 0.001 ). The between-group comparison also showed a significant difference in VAS, but not in the T-WOMAC score, favouring HILT ( p < 0.05 ). Conclusion. The HILT plus conservative treatment can help alleviate pain in patients with knee OA. The findings of the present study could be used in clinical practice to add HILT as another noninvasive treatment option for knee OA. This could be advantageous, particularly for individuals who are at high risk of surgery due to multiple comorbidities or older people. Trial Registration. This clinical trial registration was performed at Clinical.gov (NCT04889885).
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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) | 0.007 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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".