Hyperintense Vessels, Collateralization, and Functional Outcome in Patients With Stroke Receiving Endovascular Treatment
Bibliographic record
Abstract
Background and Purpose— Fluid-attenuated inversion recovery hyperintense vessels (FHV) are frequently observed on magnetic resonance imaging in acute stroke patients with proximal vessel occlusion. Whether FHV can serve as a surrogate for the collateral status and predict functional outcome of patients is still a matter of debate. Methods— Acute ischemic stroke patients with M1-middle cerebral artery occlusion who received magnetic resonance imaging before endovascular treatment in 3 hospitals in Germany between January 2007 and June 2016 were eligible. Quantification of FHV was performed using an FHV–Alberta Stroke Program Early CT Score (ASPECTS) rating system. Functional outcome was evaluated with the modified Rankin Scale 3 months after stroke. Collateral status of patients was graded on baseline angiography using the American Society of Interventional and Therapeutic Neuroradiology grading system. Odds for good outcome (modified Rankin Scale score, 0–2) were determined using logistic regression analyses. Results— Overall, 116 patients were analyzed (median age, 74; interquartile range [IQR], 64–79; median National Institutes of Health Stroke Scale, 14; IQR, 10–19). The median FHV-ASPECTS was 2 (IQR, 1–3). Good collateral status (American Society of Interventional and Therapeutic Neuroradiology grade 3–4) on angiography was more frequently observed in patients with FHV-ASPECTS ≤2 (83% versus 57%; P =0.025). Patients with an FHV-ASPECTS ≤2 had a better functional outcome after 3 months (median modified Rankin Scale score, 2; IQR, 0–5), compared with patients with an FHV-ASPECTS >2 (median modified Rankin Scale score, 4; IQR, 3–6; P =0.015). In multiple regression analyses, FHV-ASPECTS ≤2 was independently associated with good functional outcome (adjusted odds ratio, 5.3; 95% confidence interval, 1.5–18.2). Conclusions— Low FHV-ASPECTS is associated with both better collateral status and better 3-month functional outcome in acute stroke patients with M1 vessel 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 | 0.003 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".