Anesthetic Management During Posterior Spinal Fusion in a Patient With Moyamoya
Bibliographic record
Abstract
Moyamoya disease is an arteriopathy of the vasculature of the central nervous system that predisposes patients to cerebrovascular ischemia and thrombotic strokes. It is characterized by a progressive narrowing of the intracranial component of the internal carotid arteries as well as the proximal branches of the anterior and middle cerebral arteries thereby predisposing patients to episodes of cerebrovascular insufficiency. Moyamoya disease adds an additional level of complexity to the anesthetic care of patients undergoing major surgical procedures related to concerns of maintaining adequate cerebral perfusion and oxygenation. These patients may present with a history of transient ischemic attacks or cerebrovascular accidents with resultant neurological deficits, cognitive delay and seizures at baseline. We present an 18-year-old woman with moyamoya disease who required anesthetic care during a posterior spinal fusion for a neuromuscular disorder. Physiological parameter management intraoperatively is discussed and options for anesthetic care are presented with an emphasis on the use of near infrared spectroscopy to monitor cerebral oxygenation. J Med Cases. 2018;9(6):190-193 doi: https://doi.org/10.14740/jmc3072w
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| 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".