Distinct predictive role of collateral status on clinical outcome in variant stroke subtypes of acute large arterial occlusion
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Clinical trials have shown that robust collateral flow has a relationship with good clinical outcome; however, different stroke subtypes were lumped together. This study explored the relationship between baseline collaterals and the onset-to-imaging time (OIT) and the correlation between pre-treatment collateral status and clinical outcome amongst different subtypes. METHOD: Prospectively collected data from consecutive acute ischaemic stroke patients with acute middle cerebral artery occlusion who received reperfusion therapy were reviewed. The regional leptomeningeal score (20 points) was based on the scoring extent of contrast opacification in the six Alberta Stroke Program Early CT Score (ASPECTS) cortical regions (M1-6), parasagittal anterior cerebral artery territory and the basal ganglia by perfusion-derived dynamic four-dimensional computed tomography angiography (4D CTA). Stroke subtype was determined by the TOAST classification criteria. A 3-months modified Rankin Scale score of 0-2 was defined as a good outcome. RESULTS: The analysis included 158 patients: 30 (19.0%) patients had large artery atherosclerotic stroke (LAA), 87 (55.1%) cardioembolic stroke (CE) and 41 (25.9%) stroke of undetermined etiology. Baseline collateral was negatively correlated with OIT (P = 0.0205) in the CE group after adjusting for female sex, smoking, hyperlipidemia, baseline National Institutes of Health Stroke Scale (NIHSS) and baseline mismatch ratio, but not in the LAA group. Baseline collateral showed a strong relationship with good clinical outcome after adjusting for recanalization, baseline NIHSS, age and female sex (odds ratio 1.120, confidence interval 1.013-1.238, P = 0.027) in all patients and in the CE group (odds ratio 3.223, confidence interval 1.212-8.570, P = 0.019), but not in the LAA patients. CONCLUSIONS: Based on 4D CTA, sustained good leptomeningeal collaterals may predict good outcome in CE but not in LAA patients. Moreover, the extent of collaterals was associated with OIT in the CE patients, which indicates prompt reperfusion therapy in this group of patients.
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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 | 0.001 |
| 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".