Prognostic Value of CT Angiography in Patients with Suspected Vertebrobasilar Ischemia
Bibliographic record
Abstract
BACKGROUND: The outcome of vertebrobasilar ischemia depends on the clinical presentation and the presence or absence of vascular occlusion. The aim of our study was to analyze the CT angiography (CTA) predictors of outcome in patients with suspected vertebrobasilar ischemia. METHODS: We studied patients with suspected acute vertebrobasilar ischemia between April 2002 and January 2006 and had CTA done within 24 hours of symptom onset. We reviewed the final diagnosis and 3-month follow-up and analyzed the clinical and CTA predictors of outcome. RESULTS: Of the 133 patients, 21(15%), 18 (13%), and 16 (12%) had occlusion of basilar artery (BA), vertebral artery (VA), and posterior cerebral artery (PCA) respectively. The final diagnosis was stroke in 98 (73.6%), transient ischemic attack (TIA) in 10 (7.5%), and nonischemic in 25 (18.8%). No vascular occlusion was seen on CTA in patients with TIA and nonischemic diagnosis. At 3-month follow-up, we found a mortality rate of 10.6% and good functional outcome in 71.4%. The predictors of death in the multivariable analysis were the presence of BA occlusion (odds ratio[OR] 6.7, 95% CI, 1.4-30.6) and baseline National Institutes of Health Stroke Scale (NIHSS) (OR 1.14, 95% CI, 1.06-1.2). When patients with basilar occlusion were excluded, the presence of VA occlusion (OR 6.5, 95% CI, 1.34-31.4), age (OR 1.09, 95% CI, 1.03-1.14), and baseline NIHSS (OR 1.1, 95% CI, 1.03-1.18) predicted poorer outcome. CONCLUSIONS: The presence or absence of a vascular occlusion is a critical factor for prognosis in suspected acute vertebrobasilar ischemia and is correlated with the location of occlusion.
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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 | 0.007 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".