Endovascular Therapy for Acute Basilar Artery Occlusion: Prognosis Prediction Value from Clinical to Imaging Variables
Bibliographic record
Abstract
PURPOSE: Acute basilar artery occlusion (BAO) correlates with high risks of disability and mortality, and the best imaging and treatment strategies for BAO remain controversial. This study evaluated the association between baseline imaging, clinical variables, and clinical outcomes of patients with BAO undergoing endovascular therapy (EVT). METHODS: Data from 75 patients with BAO who had EVT at a single center were retrospectively analyzed. Baseline National Institutes of Health Stroke Scale (NIHSS) scores, clinical baseline data, and various known scores and perfusion deficit volumes on non-contrast computed tomography (NCCT), CT angiography source images (CTA-SI), and CT perfusion (CTP) were collected to explore effective predictive factors for prognosis. The functional outcome of the analysis was satisfactory (90-day modified Rankin Scale score ≤3). Predictors of functional outcomes were assessed through receiver operating characteristic analyses and binary logistic regression. RESULTS: Among the 75 patients who fulfilled the inclusion criteria, 29 achieved a good outcome (39%) and 46 (61%) achieved a poor outcome. The Critical Area Perfusion Score (CAPS), pons midbrain index (PMI), time to maximum (Tmax) >6 s, Tmax >10 s, and reduction in CBF compared with normal brain tissue (rCBF) <30%, cerebral blood flow (CBF), cerebral blood volume (CBV), and mean transit time (MTT) Posterior Circulation Alberta Stroke Program Early CT Score (pc-ASPECTS) were independent predictors of favorable prognosis. The CAPS was the best predictor of good clinical outcomes, with an area under the curve of 0.862 (95% confidence interval [CI], 0.772-0.952). Combined diagnosis with the baseline NIHSS score improved the prognosis prediction accuracy. CONCLUSIONS: In patients with stroke that resulted in BAO after EVT, CAPS, PMI, Tmax >6 s, Tmax >10 s, rCBF <30% volume, and CBV pc-ASPECTS were excellent predictors of higher risk of disability and mortality. Furthermore, CAPS had the best accuracy, and overall predictive value could be improved when combined with the baseline NIHSS score for diagnosis.
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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 | 0.001 | 0.000 |
| 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".