Intracranial Atherosclerosis Disease Associated With Cognitive Impairment and Dementia: Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
BACKGROUND: Intracranial atherosclerosis disease (ICAD) alters cerebrovascular hemodynamics and brain structural integrity. Multiple studies have evaluated the link between ICAD and cognitive impairment, with mixed results. This study aims to systematically review and summarize the current evidence on this link. METHODS AND RESULTS: PubMed, EMBASE, PsycInfo, and Web of Science were searched from 2000 to 2023 without language restriction. Cross-sectional and prospective cohort studies as well as postmortem studies were included. Studies containing data on the link between ICAD, defined as at least 50% stenosis in 1 intracranial vessel, and cognitive impairment and dementia were screened by 2 independent reviewers. A total of 22 (17 observational and 5 postmortem) unique studies, comprising 11 184 individuals (average age range, 59.8-87.6 years; 45.7% women; 36.5% Asian race), were included in the systematic review. Seven of 10 cross-sectional studies and 5 of 7 prospective studies showed a significant association between ICAD and cognitive impairment. In the pooled analysis, ICAD was associated with greater cognitive impairment (measure of association, 1.87 [95% CI, 1.49-2.35]). Meta-regression analyses did not show a significant impact of age, sex, and race. All postmortem studies showed that patients with Alzheimer disease and vascular dementia had a higher burden of ICAD compared with controls. CONCLUSIONS: This study shows that ICAD is associated with cognitive impairment and dementia across age, sex, and race groups. Our findings may underscore the need to develop individualized dementia preventive care plans in patients with ICAD.
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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 | 0.010 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.025 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".