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Record W2081660367 · doi:10.2174/1874325001307010396

Low Level Laser Therapy (LLLT) for Neck Pain: A Systematic Review and Meta-Regression

2013· review· en· W2081660367 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueThe Open Orthopaedics Journal · 2013
Typereview
Languageen
FieldMedicine
TopicLaser Applications in Dentistry and Medicine
Canadian institutionsPrincess Margaret Cancer CentreSimon Fraser UniversityUniversity of TorontoMcMaster University
FundersMcMaster University
KeywordsMedicineLow level laser therapyMeta-regressionMeta-analysisNeck painLaser therapyPhysical therapyLaserInternal medicineAlternative medicinePathology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.560
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0060.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.216
GPT teacher head0.427
Teacher spread0.212 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it