Dynamic CT perfusion imaging in subarachnoid hemorrhage-related vasospasm.
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Nimodipine is a therapy that reduces morbidity and mortality in patients with subarachnoid hemorrhage (SAH), though the mechanisms by which it does so are not well understood. In a rabbit model of SAH, we studied the effects of nimodipine by using functional CT imaging. We hypothesized that the nimodipine treatment group would have (1) increased mean basilar artery diameter, (2) less diminished cerebral blood flow (CBF) following vasospasm, and (3) better neurologic outcomes. METHODS: SAH was induced in 26 New Zealand White rabbits randomized to 2 groups: treated (nimodipine) or control (no treatment). CT perfusion and CT angiography were used to measure CBF and basilar artery diameter at baseline, 10, 30, and 60 minutes after SAH, and on days 3, 5, 7, 9, and 16. Neurologic assessments were performed on each day of scanning. RESULTS: Basilar artery diameter in the treated group was greater than in the control group post-SAH (P < .05). When vasospasm was >15%, CBF in the nimodipine group was significantly greater than in the control group in the brain stem, cerebellum, parieto-occipital cerebrum, and deep gray matter (P < .05). Neurologic scores in the nimodipine group were significantly better than in the control group on days 5 and 9 (P < .05). CONCLUSION: Animals treated with nimodipine showed (1) increased mean basilar artery diameter, (2) improved neurologic outcome, and (3) increased mean CBF despite no significant difference in the incidence and severity of delayed vasospasm. These data provide a basis for future studies comparing the efficacy of new treatments for SAH to that of nimodipine.
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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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".