Alleviation of Pancoast's Tumor Pain by Ultrasound‐Guided Percutaneous Ablation of Cervical Nerve Roots
Bibliographic record
Abstract
The case report describes use of real-time ultrasound guidance to facilitate percutaneous ablation of cervical nerve roots in a patient with Pancoast's syndrome. Distortion of anatomy by the tumor made it difficult to perform the procedure safely using fluoroscopy. A 64-year-old right-handed male patient with carcinoma of the left lung presented with severe pain in the left shoulder and the arm. A clinical diagnosis of the left brachial plexopathy secondary to tumor involvement of C5 to C8 nerve roots was made. Radiological appearance of the cervical spine revealed distorted anatomy because of severe degeneration of the cervical spine and guarding torticollis. Diagnostic prognostic block of the C4 to C7 exiting nerve roots was done under ultrasound guidance and resulted in more than 75% reduction in pain intensity for 4 hours. Ultrasound-guided percutaneous cervical rhizotomy was performed later. At 3-month follow-up, the patient still had complete pain relief as well as improvement in quality of sleep. Ultrasound-guided cervical nerve roots ablation is a feasible approach for patients with intractable neuropathic pain secondary to Pancoast's tumor. It can be a useful alternative to fluoroscopy in patients in whom a fluoroscopy-guided approach is deemed difficult and hazardous.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".