Intracranial Atherosclerotic Stenosis is Related to Post-stroke Cognitive Impairment: A Cross-sectional Study of Minor Stroke
Bibliographic record
Abstract
BACKGROUND: Intracranial Atherosclerotic Stenosis (ICAS) is an important risk factor for cognitive impairment. However, it is unclear whether patients with ICAS are more likely to develop cognitive impairment after an acute, non-disabling ischemic stroke (minor stroke). OBJECTIVE: We aimed to investigate the association between ICAS and post-stroke cognitive impairment. METHODS: In this cross-sectional study, patients with acute, non-disabling ischemic stroke underwent two cognitive tests and imaging evaluation for ICAS, within two weeks after the stroke. To determine the association between ICAS and post-stroke cognitive impairment, we performed a multivariate logistic regression analysis adjusted for several demographic and vascular risk factors. RESULTS: Of the 164 patients with minor stroke in this study, 98 (59.76%) were diagnosed with poststroke cognitive impairment (Montreal Cognitive Assessment score<26). After adjusting for potential confounders, we found that patients with ICAS were more likely to develop cognitive impairment after an acute, non-disabling ischemic stroke, compared to patients without ICAS (Odds Ratio: 2.13; 95% Confidence Interval: 1.07-4.26), and underperformed in the tests of visuospatial and executive function. CONCLUSION: In this cross-sectional study of a population that has experienced a minor stroke, our findings demonstrated a positive association between ICAS and post-stroke cognitive impairment.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.001 | 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".