Admission Brain Cortical Volume
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Several markers of poststroke cognitive impairment have been reported. The role of brain cortical volume remains uncertain. The aim of this study was to evaluate the influence of brain cortical volume on cognitive outcomes using a voxel-based morphometry approach in subjects without prestroke dementia. METHODS: Ischemic stroke patients were prospectively recruited 24 to 72 hours post stroke (M0). Cognition was evaluated at M0, 3 months, and 1 year (M12) using the Montreal Cognitive Assessment, the Isaacs set test, and the Zazzo's cancellation task. A 3-T brain magnetic resonance imaging was performed at M0. Grey matter (GM) was segmented using Statistical Parametric Mapping 12 software. Association between global GM volume and cognitive score slopes between M0 and M12 was evaluated using a linear mixed model. Correlations between focal GM volumes and changes in cognitive performance were evaluated using Statistical Parametric Mapping 12. RESULTS: =0.04) independently of other clinical/radiological confounders. Subjects with lower GM volumes in the left fronto-temporo-insular cortex were more vulnerable to transient Montreal Cognitive Assessment and Isaacs set test impairment. Subjects with lower GM volumes in right temporo-insular cortex, together with basal ganglia, were more vulnerable to transient cognitive impairment on the Zazzo's cancellation task. CONCLUSIONS: Smaller cortical volumes in fronto-temporo-insular areas measured 24 to 72 hours post stroke are associated with cognitive vulnerability in the subacute stroke phase.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".