Comparison of the effects of high-intensity laser with low-intensity laser in patients with knee osteoarthritis
Bibliographic record
Abstract
Knee osteoarthritis is a musculoskeletal disease characterized by degeneration and deterioration of articular cartilage. In addition to pharmacological therapy, physical modalities including low-intensity laser therapy (LILT) and high-intensity laser therapy (HILT), and kinesitherapy are used to treat knee osteoarthritis (КОА). To date, no research has been conducted in the Republic of North Macedonia that could be compared to existing research about the effects of HILT and LILT on functional ability in patients with КОА. The aim of this study was to compare the treatment effects of HILT and LILT in patients with KOA. Materials and methods: This was a randomized comparative single-blind study involving 72 patients divided into two groups. The first group was treated with 10 sessions of HILT, and the second group with 10 sessions of LILT. Patients of both groups performed exercises for 1 month. Functional outcome was evaluated after the end of the laser therapy and after 1 month using the Western Ontario and McMaster Universities Osteoarthritic Index (WOMAC). Statistical significance was defined as p<0.05. Results: At the end of the laser therapy and 1 month later, a statistically significant difference was found between the two groups, measured by the WOMAC index (p<0.001). Additionally, the WOMAC index was compared within the groups. Conclusion: Patients with KOA who were treated with HILT had significantly better functional recovery than patients treated with LILT.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".