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Record W2006246006 · doi:10.1002/lsm.20137

Randomized controlled trial on low level laser therapy (LLLT) in the treatment of osteoarthritis (OA) of the hand

2005· article· en· W2006246006 on OpenAlexaff
Lucie Brosseau, George A. Wells, Serge Marchand, Isabelle Gaboury, Barbara Stokes, Michelle Morin, Lynn Casimiro, Katharine Yonge, Peter Tugwell

Bibliographic record

VenueLasers in Surgery and Medicine · 2005
Typearticle
Languageen
FieldMedicine
TopicLaser Applications in Dentistry and Medicine
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsLow level laser therapyMedicineOsteoarthritisPlaceboRange of motionGrip strengthRandomized controlled trialPhysical therapyMorning stiffnessPain reliefCarpometacarpal jointAnesthesiaLaser therapySurgeryInternal medicineArthritisLaserAlternative medicine

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVES: Low level laser therapy (LLLT) offers promising symptomatic relief of osteoarthritic (OA) pain. We examined efficacy of active LLLT versus sham LLLT on finger joints and three superficial nerves. STUDY DESIGN/MATERIALS AND METHODS: OA-patients randomly assigned, received three treatments per week for 6 weeks of LLLT (n = 42) or sham LLLT (n = 46). RESULTS: Pain relief, morning stiffness, and functional status did not significantly improve for LLLT versus placebo. No significant differences were found in finger range of motion, except carpometacarpal opposition (P = 0.011), grip strength, and patient global assessment which improved for active LLLT participants (P = 0.041). CONCLUSIONS: LLLT is no better than placebo at reducing pain, morning stiffness, or improving functional status for OA-hand patients.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0180.002

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 head0.037
GPT teacher head0.308
Teacher spread0.271 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreEmpirical

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".

Quick stats

Citations102
Published2005
Admission routes1
Has abstractyes

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