Is high intensity laser therapy more effective than other physical therapy modalities for treating knee osteoarthritis? A systematic review and network meta-analysis
Bibliographic record
Abstract
Background: The use of physical therapy modalities, especially high intensity laser therapy (HILT), for individuals with knee osteoarthritis (KOA) is still controversial. Objective: To compare the effects of HILT to other physical therapy modalities on symptoms and function in individuals with KOA. Methods: Six databases (PubMed, Embase, Cochrane Library, Web of Science, EBSCO, and PEDro) were searched in March 2022. Included studies were randomized controlled trials involving HILT conducted on individuals with KOA. The end-trial weighted mean difference (WMD) and standard deviations (SD) with 95% confidence intervals (CI) were analyzed. Results: Ten studies with 580 participants were obtained, of which nine were included in the final network meta-analysis. In terms of relieving pain, HILT demonstrated the highest probability of being among the most effective treatments, with surface under the cumulative ranking (SUCRA) = 100%, and compared to a control (placebo laser or exercise or a combination of both) on the visual analog scale (VAS) for pain it demonstrated significant benefits (WMD 1.66, 95% CI 1.48-1.84). For improving self-reported function, as measured by the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) total scores, the HILT SUCRA value led with 98.9%. When individuals with KOA were treated by HILT, the improvement in stiffness was statistically significant (WMD 0.78, 95% CI 0.52-1.04) but the amount of improvement was smaller than the minimal clinically important difference (MCID). Conclusion: The current evidence suggests that HILT may be more effective than other physical therapy modalities for improving pain and function in individuals with KOA. For improving stiffness, however, it may not be clinically effective. Systematic review registration: [https://www.researchregistry.com], identifier [1148].
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".