Does cerebral large-artery disease contribute to cognitive impairment?
Why this work is in the frame
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Bibliographic record
Abstract
Although many patients with cerebral large-artery disease (CLAD) show impaired cognitive performance, the risk factors remain unclear in this population. The objective of this study was to evaluate cognitive impairment and its risk factors in patients with CLAD. We recruited non-demented patients with CLAD from our hospital. CLAD was defined as occlusion or stenosis of over 50% in the carotid artery or middle cerebral artery. We collected patients' biographical data and vascular lesion and imaging data, including periventricular hyperintensity (PVH) and cerebral perfusion. The patients were divided into two groups: cognitive impairment-plus (CoI +) and normal (CoI −) groups, according to their Montreal Cognitive Assessment (MoCA) scores, with a cut-off value of 26. The factors associated with cognitive impairment were examined. Of the 176 patients with CLAD (mean age 70.2 ± 8.3, 40 female), 136 (77.2%) were classified as cognitively impaired. Multivariate analysis indicated that the CoI + group was associated with older age (odds ratio (OR): 1.09, P = 0.011), drinking habit (OR: 7.15, P = 0.003), increased PVH (OR: 3.46, P = 0.003), and decreased cerebral perfusion (OR: 0.897, P = 0.007). Analyses of the MoCA subscores indicated that attention, memory, and orientation were impaired in the CoI + group. Impaired cognition was observed in some of the non-demented patients with CLAD. Older age, drinking habit, severe PVH and decreased cerebral perfusion contributed to their poor cognitive performance. Strict treatment of atherosclerosis and intervention for CLAD might be necessary to prevent cognitive decline in these patients.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.002 | 0.001 |
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 it