Epidemiology of Intracranial and Extracranial Large Artery Stenosis in a Population-Based Study of Stroke in the Middle East
Bibliographic record
Abstract
BACKGROUND: Intracranial large-artery disease (LAD) is a predominant vascular lesion found in patients with stroke of Asian, African, and Hispanic origin, whereas extracranial LAD is more prevalent among Caucasians. These patterns are not well-established in the Middle East. We aimed to characterize the incidence, risk factors, and long-term outcome of LAD strokes in a Middle-Eastern population. METHODS: The Mashhad Stroke Incidence Study is a community-based study that prospectively ascertained all cases of stroke among the 450,229 inhabitants of Mashhad, Iran between 2006 and 2007. Ischemic strokes were classified according to the TOAST criteria. Duplex-ultrasonography (98.6%), MR-angiography (8.3%), CT-angiography (11%), and digital-subtraction angiography (9.7%) were performed to identify involvements. Vessels were considered stenotic when the lumen was occluded by >50%. RESULTS: We identified 72 cases (15.99 per 100,000) of incident LAD strokes (mean age 67.6 ± 11.7). Overall, 77% had extracranial LAD (58% male, mean age 69.8 ± 10.3; 50 [89%] carotid vs. 6 [11%] vertebral artery), and the remaining 23% (56% male, mean age 60.2 ± 13.4; 69% anterior-circulation stenosis) had intracranial LAD strokes. We were unable to detect differences in case-fatality between extracranial (1-year: 28.6%; 5-year: 59.8%) and intracranial diseases (1-year: 18.8%; 5-year: 36.8%; log-rank; p = 0.1). CONCLUSION: Extracranial carotid stenosis represents the majority of LAD strokes in this population. Thus, public health strategies may best be developed in such a way that they are targeted toward the risk factors that contribute to extracranial stenosis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".