Decrease of Hyperintense Vessels on Fluid-Attenuated Inversion Recovery Predicts Good Outcome in t-PA Patients
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Hyperintense vessels (HV) detected on fluid-attenuated inversion recovery (FLAIR) in patients with acute ischemic stroke (AIS) indicate cerebral hypoperfusion. However, the clinical meaning of changes in HV is yet to be clarified. Here, we investigated serial changes to HV in patients with AIS who received tissue plasminogen activator (t-PA) therapy. METHODS: We studied t-PA patients presenting with HV on FLAIR in the middle cerebral artery territory. Patients underwent brain MRI 1 h before and after t-PA infusion. HV scores (range 1-7) were evaluated according to Alberta Stroke Program Early Computed Tomography Score territories, and then by subtracting HV scores at 1 h after t-PA infusion from those on admission, with a result of >1 defined as decrease in HV score (DHV). Patients were divided into 2 groups based on the presence or absence of DHV. Multivariate logistic regression analysis was conducted to identify variables independently associated with good outcome (modified Rankin Scale score at 90 days after stroke onset of 0-1). RESULTS: A total of 118 consecutive patients were enrolled (73 men; mean age 76 ± 9.7; median initial National Institutes of Health Stroke Scale (NIHSS) 13; median initial HV score 5), of whom 52 (44%) had DHV. Patients with DHV showed a significantly lower NIHSS time course (p < 0.001) and significantly smaller infarct volume time course (p < 0.001) compared to those without DHV. Multivariate analysis showed that DHV was independently associated with good outcome (OR 3.89; 95% CI 1.55-9.77; p < 0.01). The sensitivity and specificity of DHV for good outcome were 70 and 68%, respectively. CONCLUSION: A DHV on FLAIR predicts good outcome in patients receiving t-PA.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".