Impact of global cerebral atrophy on clinical outcome after subarachnoid hemorrhage
Bibliographic record
Abstract
OBJECT: Atrophy in specific brain areas correlates with poor neuropsychological outcome after subarachnoid hemorrhage (SAH). Few studies have compared global atrophy in SAH with outcome. The authors examined the relationship between global brain atrophy, clinical factors, and outcome after SAH. METHODS: This study was a post hoc exploratory analysis of the Clazosentan to Overcome Neurological Ischemia and Infarction Occurring After Subarachnoid Hemorrhage (CONSCIOUS-1) trial, a randomized, double-blind, placebo-controlled trial of 413 patients with aneurysmal SAH. Patients with infarctions or areas of encephalomalacia on CT, and those with large clip/coil artifacts, were excluded. The 97 remaining patients underwent CT at baseline and 6 weeks, which was analyzed using voxel-based volumetric measurements. The percentage difference in volume between time points was compared against clinical variables. The relationship with clinical outcome was modeled using univariate and multivariate analysis. RESULTS: Older age, male sex, and systemic inflammatory response syndrome (SIRS) during intensive care stay were significantly associated with brain atrophy. Greater brain atrophy was significantly associated with poor outcome on the modified Rankin scale (mRS), severity of deficits on the National Institutes of Health Stroke Scale (NIHSS), worse executive functioning, and lower EuroQol Group-5D (EQ-5D) score. Adjusted for confounders, brain atrophy was not significantly associated with Mini-Mental State Examination and Functional Status Examination scores. Brain atrophy was not associated with angiographic vasospasm or delayed ischemic neurological deficit. CONCLUSIONS: Worse mRS score, NIHSS score, executive functioning, and EQ-5D scores were associated with greater brain atrophy and older age, male sex, and SIRS burden. These data suggest outcome is associated with factors that cause global brain injury independent of focal brain injury.
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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 | 0.001 | 0.002 |
| 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 | 0.000 |
| 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".