Mean transit time as an index of cerebral perfusion pressure in experimental systemic hypotension
Bibliographic record
Abstract
Early diagnosis of cerebrovascular disease requires the accurate identification of brain regions with compromised cerebral perfusion pressure (CPP). Current clinical measures of CPP are invasive and lack regional information. Dynamic contrast-enhanced imaging provides a means of looking at regional cerebral hemodynamics. The purpose of this study was to determine if any of the parameters associated with dynamic contrast-enhanced imaging could be used as an index for CPP under graded systemic hypotension in a rabbit model. Cerebral blood flow (CBF), cerebral blood volume, mean transit time (MTT), and cerebrovascular reserve (CVR) were measured using Computed Tomography Perfusion in three groups: normotensive (n = 14), mild hypotensive (n = 9), and moderate hypotensive (n = 6). MTT demonstrated the strongest correlation with CPP (ρ = -0.642, P < 0.05). CBF was the only other parameter to demonstrate a statistically significant correlation (ρ = 0.575, P < 0.05). CVR is gaining momentum for diagnosing cerebrovascular disease; however, the technique requires patients to be given a hemodynamic challenge, which could aggravate symptoms and even trigger stroke. The results of this study suggest that the use of MTT, not requiring hemodynamic manipulation, is more sensitive to subtle changes in CPP, as would occur in the early stages of cerebrovascular disease.
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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) | 0.000 | 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) | 0.000 | 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".