Low Level Laser Therapy (LLLT) for Neck Pain: A Systematic Review and Meta-Regression
Bibliographic record
Abstract
PURPOSE: This systematic review update evaluated low level laser therapy (LLLT) for adults with neck pain. METHODS: Computerized searches (root up to Feb 2012) included pain, function/disability, quality of life (QoL) and global perceived effect (GPE). GRADE, effect-sizes, heterogeneity and meta-regression were assessed. RESULTS: Of 17 trials, 10 demonstrated high risk of bias. For chronic neck pain, there was moderate quality evidence (2 trials, 109 participants) supporting LLLT over placebo to improve pain/disability/QoL/GPE up to intermediate-term (IT). For acute radiculopathy, cervical osteoarthritis or acute neck pain, low quality evidence suggested LLLT improves ST pain/function/QoL over a placebo. For chronic myofascial neck pain (5 trials, 188 participants), evidence was conflicting; a meta-regression of heterogeneous trials suggests super-pulsed LLLT increases the chance of a successful pain outcome. CONCLUSIONS: We found diverse evidence using LLLT for neck pain. LLLT may be beneficial for chronic neck pain/function/QoL. Larger long-term dosage trials are needed.
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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 | 0.014 | 0.040 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.025 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".