Ultrasound‐guided spinal accessory nerve blockade in the diagnosis and management of trapezius muscle‐related myofascial pain
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".