Stereotactic mesencephalotomy for palliative care pain control: A case report, literature review and plea to rediscover this operation
Bibliographic record
Abstract
Introduction Stereotactic mesencephalotomy is an ablative procedure which lesions the pain pathways (spinothalamic and trigeminothalamic tracts) at the midbrain level to treat medically refractory, nociceptive, contralateral pain. Sparsely reported in contemporary English language literature, this operation is at risk of being lost from the modern-day neurosurgical practice. Methods We present a case report and brief review of the literature on stereotactic mesencephalotomy. A 17-year-old girl with cervical cord glioblastoma and medically refractory unilateral head and neck pain was treated with contralateral stereotactic mesencephalotomy. The lesion was placed at the level of the inferior colliculus, half way between the lateral edge of the aqueduct and lateral border of the midbrain. Results The patient had no head and neck pain immediately after the procedure and remained pain-free for the remainder of her life (five months). She was weaned off her pre-operative narcotics and was able to leave hospital, meeting her palliative care goals. Conclusions Cancer-related unilateral head and neck nociceptive pain in the palliative care setting can be successfully treated with stereotactic mesencephalotomy. We believe that stereotactic mesencephalotomy is the treatment of choice for a small number of patients typified by our case. The authors make a plea to the palliative care and neurosurgical communities to rediscover this operation.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".