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Record W2340149649 · doi:10.1097/phm.0000000000000376

Assessment of Myofascial Trigger Points Using Ultrasound

2015· review· en· W2340149649 on OpenAlexaff
Dinesh Kumbhare, Alyaa H. Elzibak, Michael D. Noseworthy

Bibliographic record

VenueAmerican Journal of Physical Medicine & Rehabilitation · 2015
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMyofascial pain diagnosis and treatment
Canadian institutionsMcMaster University Medical Centre
Fundersnot available
KeywordsPalpationMedicineMyofascial pain syndromeMyofascial painUltrasoundUltrasound imagingUltrasonographyRadiologyMedical physicsPhysical medicine and rehabilitationPhysical therapyPathologyAlternative medicine

Abstract

fetched live from OpenAlex

Myofascial pain syndrome is a common musculoskeletal pain disorder characterized by the presence of myofascial trigger points (MTrPs). The diagnosis of myofascial pain syndrome is currently made on clinical grounds. Numerous diagnostic criteria are used to identify myofascial pain syndrome, including the localization of MTrPs. Identifying the presence of MTrPs currently requires the physician to palpate the symptomatic region. Because the interrater reliability of the palpation technique has been found to be poor, numerous groups have been interested in finding objective imaging measures to localize the MTrP. This comprehensive review focuses on summarizing ultrasound imaging techniques that have shown promise in visually localizing the trigger point. The authors' literature search identified three sonographic approaches that have been used in MTrP localization: conventional gray-scale imaging, Doppler imaging, and elastographic ultrasound imaging. This review article explains the basic physics behind the imaging methods and summarizes the characteristics of the MTrP as identified by the ultrasonic techniques.

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.996
Threshold uncertainty score0.841

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.026
GPT teacher head0.407
Teacher spread0.381 · 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 designOther design
Domainnot available
GenreReview

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

Citations69
Published2015
Admission routes1
Has abstractyes

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