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Ultrasound‐guided spinal accessory nerve blockade in the diagnosis and management of trapezius muscle‐related myofascial pain

2011· article· en· W1889912337 on OpenAlexaff
P. Townsley, A. Ravenscroft, N. Bedforth

Bibliographic record

VenueAnaesthesia · 2011
Typearticle
Languageen
FieldMedicine
TopicNerve Injury and Rehabilitation
Canadian institutionsQueen's University
Fundersnot available
KeywordsMedicineAccessory nerveTrapezius muscleMyofascial pain syndromeNerve blockBlockadeAnesthesiaNeck painElectromyographySurgeryPhysical medicine and rehabilitation

Abstract

fetched live from OpenAlex

We report the first description of ultrasound-guided spinal accessory nerve blockade using single-shot and subsequently continuous infusion (via a perineural catheter) local anaesthetic techniques, for the diagnosis and treatment of myofascial pain affecting the trapezius muscle. A 38-year-old man presented with a two-year history of incapacitating left suprascapular pain after a fall onto his outstretched hand. The history and clinical examination was suggestive of myofascial pain affecting the trapezius muscle. This had been unresponsive to pharmacological therapy, physiotherapy or suprascapular nerve blockade. Following identification of the spinal accessory nerve in the posterior triangle of the neck, we performed ultrasound-guided nerve blocks, first using a single injection of local anaesthetic and subsequently using a continuous infusion via a perineural catheter, to block the nerve and temporarily relieve the patient's pain. We have demonstrated that the spinal accessory nerve is identifiable in the posterior triangle of the neck and can be blocked successfully using ultrasound guidance. This technique can aid the diagnosis and treatment of myofascial pain originating from the trapezius muscle.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.363
Threshold uncertainty score0.341

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.041
GPT teacher head0.292
Teacher spread0.251 · 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

Citations24
Published2011
Admission routes1
Has abstractyes

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