Cortical Hubs and Subcortical Cholinergic Pathways as Neural Substrates of Poststroke Dementia
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: A role of neural networks in the development of poststroke dementia has not been clearly established. We hypothesized that stroke-mediated disruption of subcortical cholinergic pathway or large-scale neural networks contributes to poststroke dementia. METHODS: A matched case-control study was conducted in a predetermined cohort with acute ischemic stroke. Cases were defined as newly developed dementia diagnosed >3 months after stroke using the Korean Vascular Cognitive Impairment Harmonization Standards. Each case was matched to 2 controls for age, education, and initial stroke severity. The Cholinergic Pathways HyperIntensities Scale was applied with some modifications to characterize disruption of cholinergic pathways by acute stroke lesions. Involvement of major cortical hub locations of the default mode network, central executive network, and salience network was also investigated. RESULTS: After matching, 38 cases and 66 matched controls were included. Cholinergic Pathways HyperIntensities Scale scores were significantly higher in cases than in controls (2.2±2.9 versus 0.9±1.4). Acute ischemic lesions affecting the default mode and central executive networks were more frequently observed in cases compared with controls (36.8% versus 7.6% and 26.3% versus 6.1%, respectively). These findings remained significant in the multiple logistic regression models adjusted for various sets of potential confounders. Lesion location analysis revealed that cases were more likely to have acute lesions in the left corona radiata, hippocampal formation, and posterior parietal cortex. CONCLUSIONS: Disruption of cholinergic pathways and major hubs of large-scale neural networks might contribute to newly developed dementia after acute ischemic stroke.
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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".