CT Perfusion-Derived Mean Transit Time Predicts Early Mortality and Delayed Vasospasm after Experimental Subarachnoid Hemorrhage
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: There are limited indicators available to predict cerebral vasospasm in patients with subarachnoid hemorrhage (SAH). The purpose of this study was to determine if CT perfusion-derived hemodynamic parameters are predictors of vasospasm severity and outcome after experimental SAH. MATERIALS AND METHODS: SAH was induced in 25 New Zealand white rabbits. Cerebral blood flow (CBF), cerebral blood volume (CBV), and mean transit time (MTT) were measured with CT perfusion before SAH, within 1 hour after SAH, and on days 2, 4, 7, 9, and 16 after SAH. Basilar artery diameter, measured with CT angiography and neurologic scoring, was also obtained on the same days. Differences between animals with moderate-severe delayed vasospasm (>/=24% basilar artery narrowing) and mild delayed vasospasm (<24% basilar artery narrowing) were investigated with repeated measures analysis of variance. Multiple linear regression analysis was used to investigate the relationship between CT perfusion parameters (CBF, CBV, MTT), basilar artery diameter, and neurologic score. RESULTS: MTT increase <1 hour after SAH independently predicted mortality within 48 hours of SAH (P < .05). MTT and neurologic deficits were significantly greater with moderate-severe than with mild vasospasm (P < .05). MTT on day 2, but not CBF or CBV, was a significant predictor of subsequent moderate-severe delayed vasospasm (P < .05). CONCLUSION: In the rabbit model of experimental SAH, the CT-derived hemodynamic parameter MTT on day 0 predicted early mortality, and MTT on day 2 predicted development of moderate-severe delayed vasospasm. MTT was also significantly correlated with arterial diameter and neurologic score.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".