Hemodynamic Features of Symptomatic Vertebrobasilar Disease
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Atherosclerotic vertebrobasilar disease is an important cause of posterior circulation stroke. To examine the role of hemodynamic compromise, a prospective multicenter study, Vertebrobasilar Flow Evaluation and Risk of Transient Ischemic Attack and Stroke (VERiTAS), was conducted. Here, we report clinical features and vessel flow measurements from the study cohort. METHODS: Patients with recent vertebrobasilar transient ischemic attack or stroke and ≥50% atherosclerotic stenosis or occlusion in vertebral or basilar arteries (BA) were enrolled. Large-vessel flow in the vertebrobasilar territory was assessed using quantitative MRA. RESULTS: The cohort (n=72; 44% women) had a mean age of 65.6 years; 72% presented with ischemic stroke. Hypertension (93%) and hyperlipidemia (81%) were the most prevalent vascular risk factors. BA flows correlated negatively with percentage stenosis in the affected vessel and positively to the minimal diameter at the stenosis site (P<0.01). A relative threshold effect was evident, with flows dropping most significantly with ≥80% stenosis/occlusion (P<0.05). Tandem disease involving the BA and either/both vertebral arteries had the greatest negative impact on immediate downstream flow in the BA (43 mL/min versus 71 mL/min; P=0.01). Distal flow status assessment, based on an algorithm incorporating collateral flow by examining distal vessels (BA and posterior cerebral arteries), correlated neither with multifocality of disease nor with severity of the maximal stenosis. CONCLUSIONS: Flow in stenotic posterior circulation vessels correlates with residual diameter and drops significantly with tandem disease. However, distal flow status, incorporating collateral capacity, is not well predicted by the severity or location of the disease.
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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 | 0.000 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".