FLAIR Vascular Hyperintensities as Imaging Biomarker in Pediatric Acute Ischemic Stroke
Bibliographic record
Abstract
BACKGROUND: Fluid-attenuated inversion recovery vascular hyperintensities (FVH) are high signal intensities on magnetic resonance imaging resulting from sluggish or stagnant flow through vessels. This investigation describes the prevalence, risk factors, and outcomes associated with FVH in pediatric arterial ischemic stroke (AIS). METHODS: Retrospective review of children aged 29 days to 18 years in a single institution stroke registry from 2006 to 2022 with AIS. Magnetic resonance imaging were assessed for large vessel occlusion (LVO), FVH score, modified Alberta Stroke Program Early CT Score, and AIS volume. The association between demographic and imaging factors with the presence of and high FVH burden was assessed using Fisher exact, Pearson χ 2 , or Kruskal-Wallis tests. Wilcoxon rank-sum test evaluated the association of FVH score with the presence of LVO and poor outcome. The relationship between FVH score and age, time to magnetic resonance imaging, stroke volume, modified Alberta Stroke Program Early CT Score, Pediatric National Institutes of Health Stroke Scale, and Pediatric Stroke Outcome Measure score were assessed using Spearman correlation. A multivariable logistic regression was used to evaluate predictors of FVH. RESULTS: In total, 273 patients with AIS were screened, and 83 met the inclusion criteria. Patients were a median age of 11.6 years (range, 1 month–18 years) and 37% were female. FVH were present in 53% of the cohort. Median FVH score was 0 (interquartile range, 0–2) in those without LVO and 5.5 (interquartile range, 3–7) in those with LVO ( P <0.0001). There was a positive correlation between FVH score and Pediatric National Institutes of Health Stroke Scale ( r s =0.40; P =0.003), modified Alberta Stroke Program Early CT Score ( r s =0.62; P <0.0001), stroke volume ( r s =0.58; P <0.0001) and Pediatric Stroke Outcome Measure at 1 year ( r s =0.32; P =0.012). In the multivariable logistic regression, older age (odds ratio, 1.38 [95% CI, 1.08–1.77]; P =0.009) and the presence of LVO (odds ratio, 301.97 [95% CI, 10.89–8373.16]; P =0.001) were associated with high FVH burden. CONCLUSIONS: FVH are prevalent in children with AIS. FVH are associated with LVO, larger infarct size, and worse outcomes. Further study is needed to determine whether FVH can be used to identify patients who would benefit most from recanalization therapies.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".