Perfusion of the subarachnoid space in cadavers: a technique applicable for prevention of paraplegia in surgery of the thoracic aorta.
Bibliographic record
Abstract
BACKGROUND: No safe technique of subarachnoid perfusion during thoracoabdominal aneurysm surgery has been described. We tested the hypothesis that in cold cadavers, perfusion of the subarachnoid space at the lumbar level with warm solution is feasible and increases the temperature at the thoracic level without an increase in cerebrospinal fluid (CSF) pressure. METHODS: Six cadavers were used. A 5 Fr silastic catheter in the subarachnoid space between the second and third lumbar vertebra (L2-3) was used as an inflow and a 16-gauge catheter at L4-5 as an outflow. Normal saline at 38 degrees C was infused at 999 mL/h. Temperatures of inflow and outflow, of the thoracic subarachnoid space (T8), and of the cisterna magna, were recorded. CSF pressures were measured from the outflow catheter. RESULTS: Outflow temperature was 9+/-1 degrees C at 10 minutes. At 15 minutes it was 27+/-4 degrees C, and thoracic subarachnoid temperatures was 22+/-5 degrees C. There was no statistical difference between the temperatures recorded at 10 and 15 minutes. The temperature of the cisterna magna was 8.5+/-1.2 degrees C at 15 minutes, significantly higher than the baseline (p=0.01), but lower than that at the T8 level (p=0.0001). CSF pressures during the experiment did not changed significantly from baseline and remained below 10 cm H20. CONCLUSIONS: The technique described is simple to implement, and effective in changing the temperature of the subarachnoid space at the thoracic level. Whether spinal cord cooling by this technique safely reduces the risk of paraplegia remains to be established in an animal model.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".