A Comparison Between Low-Level Laser Therapy and Intra-articular Ozone Injection in Knee Osteoarthritis Treatment: A Randomized Clinical Trial
Bibliographic record
Abstract
Introduction: Knee osteoarthritis (KOA) is a common degenerative joint disease, causing deformity, pain and a limited joint range of motion. Modification of the lifestyle and an exercise training program are the cornerstone of treatment. Alternative therapies such as laser or ozone are commonly used, but there is not any comparative study of low-level laser therapy (LLLT) versus ozone therapy. The aim of the study was to compare the efficacy and safety of the LLLT versus ozone in patients with KOA. Methods: In this single-blinded randomized clinical trial, 60 patients with KOA were assigned to LLLT or ozone groups (n=30). The First basic pain severity, the Western Ontario and McMaster Universities Arthritis Index (WOMAC) score and physical function were determined. Then in the LLLT group, the patients were provided with 12 sessions of LLLT. In the ozone group, 6 sessions of intra-articular injection of ozone were organized (in each session a mixture of 10 mL of bupivacaine 0.25% with 15 mL of ozone 30 μg/mL). In the middle and at the end of the intervention period, we reassessed the joint pain and physical function and the degree of improvement compared between the two groups. Results: In the middle and at the end of the treatment period in both groups, the joint pain decreased significantly. The same as pain, the self-administrated WOMAC score and the range of joint motion improved significantly in both groups. All of these variables exposed more improvement in the ozone group patients. Conclusion: The study showed that both LLLT and ozone are acceptable non-invasive methods in the non-surgical treatment of KOA. Compared to LLLT, the ozone was more effective. These methods must be considered in any patient who is not suitable for surgical interventions or does not experience enough improvement in symptoms following long periods of common exercise training programs.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".