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Record W4408919564 · doi:10.1161/strokeaha.124.048717

FLAIR Vascular Hyperintensities as Imaging Biomarker in Pediatric Acute Ischemic Stroke

2025· article· en· W4408919564 on OpenAlexaboutno aff
Natalie Ullman, Arastoo Vossough, Lauren A. Beslow, Rebecca Ichord, Evelyn K. Shih

Bibliographic record

VenueStroke · 2025
Typearticle
Languageen
FieldMedicine
TopicBlood Coagulation and Thrombosis Mechanisms
Canadian institutionsnot available
FundersNational Institute of Neurological Disorders and Stroke
KeywordsMedicineInterquartile rangeStroke (engine)Magnetic resonance imagingHyperintensityRetrospective cohort studyFluid-attenuated inversion recoveryRadiologyMagnetic resonance angiographyCohortInternal medicine

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.012
GPT teacher head0.270
Teacher spread0.258 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2025
Admission routes1
Has abstractyes

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