Cerebral haemodynamics during experimental intracranial hypertension
Bibliographic record
Abstract
Intracranial hypertension is a common final pathway in many acute neurological conditions. However, the cerebral haemodynamic response to acute intracranial hypertension is poorly understood. We assessed cerebral haemodynamics (arterial blood pressure, intracranial pressure, laser Doppler flowmetry, basilar artery Doppler flow velocity, and vascular wall tension) in 27 basilar artery-dependent rabbits during experimental (artificial CSF infusion) intracranial hypertension. From baseline (∼9 mmHg; SE 1.5) to moderate intracranial pressure (∼41 mmHg; SE 2.2), mean flow velocity remained unchanged (47 to 45 cm/s; p = 0.38), arterial blood pressure increased (88.8 to 94.2 mmHg; p < 0.01), whereas laser Doppler flowmetry and wall tension decreased (laser Doppler flowmetry 100 to 39.1% p < 0.001; wall tension 19.3 to 9.8 mmHg, p < 0.001). From moderate to high intracranial pressure (∼75 mmHg; SE 3.7), both mean flow velocity and laser Doppler flowmetry decreased (45 to 31.3 cm/s p < 0.001, laser Doppler flowmetry 39.1 to 13.3%, p < 0.001), arterial blood pressure increased still further (94.2 to 114.5 mmHg; p < 0.001), while wall tension was unchanged (9.7 to 9.6 mmHg; p = 0.35).This animal model of acute intracranial hypertension demonstrated two intracranial pressure-dependent cerebroprotective mechanisms: with moderate increases in intracranial pressure, wall tension decreased, and arterial blood pressure increased, while with severe increases in intracranial pressure, an arterial blood pressure increase predominated. Clinical monitoring of such phenomena could help individualise the management of neurocritical patients.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".