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Record W2101326061 · doi:10.1161/strokeaha.115.009908

Relationship Between Lesion Topology and Clinical Outcome in Anterior Circulation Large Vessel Occlusions

2015· article· en· W2101326061 on OpenAlexaboutno aff
Srikant Rangaraju, Christopher Streib, Amin Aghaebrahim, Ashutosh P. Jadhav, Michael Frankel, Tudor G. Jovin

Bibliographic record

VenueStroke · 2015
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsnot available
FundersNational Institute of Neurological Disorders and Stroke
KeywordsMedicineOdds ratioModified Rankin ScaleConfidence intervalLogistic regressionInternal medicineStroke (engine)CardiologyInternal carotid arteryMiddle cerebral arteryRadiologyIschemiaIschemic stroke

Abstract

fetched live from OpenAlex

BACKGROUND AND PURPOSE: Diffusion-weighted imaging (DWI) Alberta Stroke Program Early CT Score (ASPECTS), a surrogate of infarct volume, predicts outcome in anterior large vessel occlusion strokes. We aim to determine whether topological information captured by DWI ASPECTS contributes additional prognostic value. METHODS: Adults with intracranial internal carotid artery, M1 or M2 middle carotid artery occlusions who underwent endovascular therapy were included. The primary outcome measure was poor clinical outcome (3-month modified Rankin Scale score, 3-6). Prognostic value of the 10 DWI ASPECTS regions in predicting poor outcome was determined by multivariable logistic regression, controlling for final infarct volume, age, and laterality. RESULTS: Two hundred and thirteen patients (mean age, 66.1±14.5 years; median National Institutes of Health Stroke Scale, 15) were included. Inter-rater reliability was good for DWI ASPECTS (deep regions, κ=0.72; cortical regions, κ=0.63). All DWI ASPECTS regions with the exception of the putamen were significant predictors (P<0.05) of poor outcome in univariate analyses. Statistical collinearity among ASPECTS regions was not observed. Using penalized multivariable logistic regression, only M4 (odds ratio, 2.82; 95% confidence interval, 1.39-5.76) and M6 (odds ratio, 2.45; 95% confidence interval, 1.15-5.3) involvement were associated with poor outcome. M6 involvement independently predicted poor outcome in right hemispheric strokes (odds ratio, 5.8; 95% confidence interval, 1.9-20.3), whereas M4 (odds ratio, 4.3; 95% confidence interval, 1.3-15.0) involvement predicted poor outcome in left hemispheric strokes adjusting for infarct volume. Topologic information modestly improved the predictive ability of a prognostic score that incorporates age, infarct volume, and hemorrhagic transformation. CONCLUSIONS: Involvement of the right parieto-occipital (M6) and left superior frontal (M4) regions affect clinical outcome in anterior large vessel occlusions over and above the effect of infarct volume and should be considered during prognostication.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.008
Threshold uncertainty score0.375

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.130
GPT teacher head0.408
Teacher spread0.279 · 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.

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

Citations60
Published2015
Admission routes1
Has abstractyes

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