Intracranial Pressure Dysfunction Following Severe Intracerebral Hemorrhage in Middle-Aged Rats
Bibliographic record
Abstract
Abstract Rising intracranial pressure (ICP) aggravates secondary injury and heightens risk of death following intracerebral hemorrhage (ICH). Long-recognized compensatory mechanisms that lower ICP include reduced cerebrospinal fluid and venous blood volumes. Recently, we identified another compensatory mechanism in severe stroke, a decrease in cerebral parenchymal volume via widespread reductions in cell volume and extracellular space (tissue compliance). Here, we examined how age affects tissue compliance and ICP dynamics after severe ICH in rats (collagenase model). A planned comparison to historical young animal data revealed that aged SHAMs (no stroke) had significant cerebral atrophy (9% reduction, p ≤ 0.05), ventricular enlargement (9% increase, p ≤ 0.05), and smaller CA1 neuron volumes (21%, p ≤ 0.05). After ICH in aged animals, contralateral striatal neuron density and CA1 astrocyte density significantly increased (12% for neurons, 7% for astrocytes, p ≤ 0.05 vs. aged SHAMs). Unlike young animals, other regions in aged animals did not display significantly reduced cell soma volume despite a few trends. Nonetheless, overall contralateral hemisphere volume was 10% smaller in aged ICH animals compared to aged SHAMs (p ≤ 0.05). This age-dependent pattern of tissue compliance is not due to absent ICH-associated mass effect (83.2 mm3 avg. bleed volume) as aged ICH animals had significantly elevated mean and peak ICP (p ≤ 0.01), occurrence of ICP spiking events, as well as bilateral evidence of edema (e.g., 3% in injured brain, p ≤ 0.05 vs. aged SHAMs). Therefore, intracranial compliance reserve changes with age; after ICH, these and other age-related changes may cause greater fluctuation from baseline, increasing the chance of adverse outcomes like mortality.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".