Prevalence and Distribution of Intracranial Vessel Occlusion on Angiography and Its Association with Functional Outcome in Patients with Atrial Fibrillation Presenting with Ischemic Stroke
Bibliographic record
Abstract
OBJECTIVES: To determine the prevalence and distribution of intracranial vessel occlusion identified on computed tomography (CT) or magnet resonance (MR) angiography and to explore its association with functional outcome in patients with atrial fibrillation (AF) and ischemic stroke. METHODS: Multicenter cohort study enrolling consecutive patients with AF with imaging-confirmed ischemic stroke who underwent CT- or MR-angiography on admission (2014-2022). Multivariable regression was used to explore the association between intracranial vessel occlusion and poor functional outcome (modified Rankin Scale score 3-6) at 90 days. RESULTS: The analysis included 10,164 patients (median age 81.5 years, 47.8% female, median National Institutes of Health Stroke Scale score on admission 6; 14.7% on a vitamin K antagonist [VKA], 27.5% on a direct oral anticoagulant [DOAC], 57.8% not receiving oral anticoagulation). Angiography showed intracranial vessel occlusion in 5,190 patients (51.1%), affecting the anterior cerebral circulation in 87.4%. Overall, 29.2% and 29.4% of patients received thrombolysis and mechanical thrombectomy, respectively. The proportion of patients with poor functional outcome at 90 days was 60.6% and 42.7% in those with and without vessel occlusion, respectively. In multivariable analyses, vessel occlusion was associated with poor functional outcome (adjusted odds ratio [aOR]: 1.95, 95% confidence interval [CI]: 1.71-2.22) with consistent results in subgroups according to oral anticoagulation use (VKA, aOR: 1.98, 95% CI: 1.40-2.80; DOAC, aOR: 2.35, 95% CI: 1.83-3.03; none, aOR: 1.76, 95% CI: 1.49-2.09). INTERPRETATION: Intracranial vessel occlusion is common in patients with AF with ischemic stroke, mainly affects the anterior circulation and is associated with poor functional outcome. ANN NEUROL 2024;96:1115-1123.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".