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Record W2110273043 · doi:10.1159/000331467

Fluid-Attenuated Inversion Recovery Hyperintensity in Acute Ischemic Stroke May Not Predict Hemorrhagic Transformation

2011· article· en· W2110273043 on OpenAlexaff
Bruce Campbell, Craig Costello, Søren Christensen, Martin Ebinger, Mark Parsons, Patricia Desmond, P. Alan Barber, Kenneth Butcher, Christopher Levi, Deidre Anne De Silva, Maarten G. Lansberg, Michael Mlynash, Jean‐Marc Olivot, Matús Straka, Roland Bammer, Gregory W. Albers, Geoffrey A. Donnan, Stephen M. Davis

Bibliographic record

VenueCerebrovascular Diseases · 2011
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsUniversity of Alberta
FundersNational Institute of Biomedical Imaging and BioengineeringNational Institute of Neurological Disorders and StrokeNational Medical Research CouncilNational Health and Medical Research CouncilNational Stroke Foundation
KeywordsFluid-attenuated inversion recoveryMedicineHyperintensityThrombolysisStroke (engine)LesionRadiologyIntracerebral hemorrhageMagnetic resonance imagingCardiologyInternal medicineNuclear medicinePathologySubarachnoid hemorrhage

Abstract

fetched live from OpenAlex

BACKGROUND: Fluid-attenuated inversion recovery (FLAIR) hyperintensity within an acute cerebral infarct may reflect delayed onset time and increased risk of hemorrhage after thrombolysis. Given the important implications for clinical practice, we examined the prevalence of FLAIR hyperintensity in patients 3-6 h from stroke onset and its relationship to parenchymal hematoma (PH). METHODS: Baseline DWI and FLAIR imaging with subsequent hemorrhage detection (ECASS criteria) were prospectively obtained in patients 3-6 h after stroke onset from the pooled EPITHET and DEFUSE trials. FLAIR hyperintensity within the region of the acute DWI lesion was rated qualitatively (dichotomized as visually obvious or subtle (i.e. only visible after careful windowing)) and quantitatively (using relative signal intensity (RSI)). The association of FLAIR hyperintensity with hemorrhage was then tested alongside established predictors (very low cerebral blood volume (VLCBV) and diffusion (DWI) lesion volume) in logistic regression analysis. RESULTS: There were 49 patients with pre-treatment FLAIR imaging (38 received tissue plasminogen activator (tPA), 5 developed PH). FLAIR hyperintensity within the region of acute DWI lesion occurred in 48/49 (98%) patients, was obvious in 18/49 (37%) and subtle in 30/49 (61%). Inter-rater agreement was 92% (κ = 0.82). The prevalence of obvious FLAIR hyperintensity did not differ between studies obtained in the 3-4.5 h and 4.5-6 h time periods (40% vs. 33%, p = 0.77). PH was poorly predicted by obvious FLAIR hyperintensity (sensitivity 40%, specificity 64%, positive predictive value 11%). In univariate logistic regression, VLCBV (p = 0.02) and DWI lesion volume (p = 0.03) predicted PH but FLAIR lesion volume (p = 0.87) and RSI (p = 0.11) did not. In ordinal logistic regression for hemorrhage grade adjusted for age and baseline stroke severity (NIHSS), increased VLCBV (p = 0.002) and DWI lesion volume (p = 0.003) were associated with hemorrhage but FLAIR lesion volume (p = 0.66) and RSI (p = 0.35) were not. CONCLUSIONS: Visible FLAIR hyperintensity is almost universal 3-6 h after stroke onset and did not predict subsequent hemorrhage in this dataset. Our findings question the value of excluding patients with FLAIR hyperintensity from reperfusion therapies. Larger studies are required to clarify what implications FLAIR-positive lesions have for patient selection.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.109
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.016
GPT teacher head0.218
Teacher spread0.201 · 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 teacher head, not a consensus.

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

Citations30
Published2011
Admission routes1
Has abstractyes

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