What are the best parameters of low-level laser therapy to reduce pain intensity and improve mandibular function in orofacial pain? A systematic review and meta-analysis
Bibliographic record
Abstract
Purpose To determine the effectiveness of laser therapy for managing patients with orofacial pain (OFP). In addition, to determine which parameters provide the best treatment effects to reduce pain, improve function, and quality of life in adults with OFP.Methods Systematic review. Searches were conducted in six databases; no date or language restrictions were applied. Studies involving adults with OFP treated with laser therapy were included. The risk of bias (RoB) was performed with the Revised Cochrane RoB-2. A meta-analysis was structured around the OFP type, and outcomes. Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) assessed the overall certainty of the evidence.Results Eighty-nine studies were included. Most studies (n = 72, 80.9%) were considered to have a high RoB. The results showed that laser therapy was better than placebo in improving pain, maximal mouth open (MMO), protrusion, and tenderness at the final assessment, but with a low or moderate level of evidence. The best lasers and parameters to reduce pain are diode or gallium–aluminum–arsenide (GaAlAs) lasers, a wavelength of 400–800 or 800–1500 nm, and dosage of <25 J/cm2.Conclusions Laser therapy was better than placebo to improve pain, MMO, protrusion, and tenderness. Also, it was better than occlusal splint to improve pain, but not better than TENS and medication.Implications for rehabilitationLaser therapy was found to be good in improving pain, maximal mouth opening, jaw protrusion, and tenderness at the end of the treatment.For patients with all types of temporomandibular disorders (TMDs) (myogenous, arthrogenous, and mixed), the following lasers and parameters are recommended: diode or gallium–aluminum–arsenide (GaAlAs) laser, wavelength of 400–800 or 800–1500 nm, and a dosage <25 J/cm2.For patients with arthrogenous TMDs, the following lasers and parameters are recommended: Diode laser and a wavelength between 400 and 800 nm.For patients with myogenous TMDs, the following lasers and parameters are recommended: diode laser, wavelength between 800 and 1500 nm, and dosage of <25 J/cm2.For patients with mixed TMDs, the following lasers and parameters are recommended: diode, GaAlAs, or infrared laser, a wavelength of 800–1500 nm, a dosage >100 J/cm2, and an application time between 15 and 30 s or >60 seconds.
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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 | 0.015 | 0.034 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.027 | 0.036 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".