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Record W2572792635 · doi:10.1016/j.jams.2016.11.007

Protocol: Testing the Relevance of Acupuncture Theory in the Treatment of Myofascial Pain in the Upper Trapezius Muscle

2017· article· en· W2572792635 on OpenAlexaboutno aff
Dale S. Elsdon, Selina Spanswick, Chris Zaslawski, Peter Meier

Bibliographic record

VenueJournal of Acupuncture and Meridian Studies · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMyofascial pain diagnosis and treatment
Canadian institutionsnot available
Fundersnot available
KeywordsAcupunctureMedicinePhysical therapyVisual analogue scaleRandomized controlled trialRepeated measures designMyofascial pain syndromeMcGill Pain QuestionnairePlaceboNeck painDry needlingPhysical medicine and rehabilitationSurgery

Abstract

fetched live from OpenAlex

A protocol for a prospective single-blind parallel four-arm randomized placebo-controlled trial with repeated measures was designed to test the effects of various acupuncture methods compared with sham. Eighty self-selected participants with myofascial pain in the upper trapezius muscle were randomized into four groups. Group 1 received acupuncture to a myofascial trigger point (MTrP) in the upper trapezius. Group 2 received acupuncture to the MTrP in addition to relevant distal points. Group 3 received acupuncture to the relevant distal points only. Group 4 received a sham treatment to both the MTrP and distal points using a deactivated acupuncture laser device. Treatment was applied four times within 2 weeks with outcomes measured throughout the trial and at 2 weeks and 4 weeks posttreatment. Outcome measurements were a 100-mm visual analog pain scale, SF-36, pressure pain threshold, Neck Disability Index, the Upper Extremity Functional Index, lateral flexion in the neck, McGill Pain Questionnaire, Massachusetts General Hospital Acupuncture Sensation Scale, Working Alliance Inventory (short form), and the Credibility Expectance Questionnaire. Two-way analysis of variance (ANOVA) with repeated measures were used to assess the differences between groups.

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 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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.682
Threshold uncertainty score0.287

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.039
GPT teacher head0.329
Teacher spread0.290 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations3
Published2017
Admission routes1
Has abstractyes

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