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Record W2139177271 · doi:10.1161/strokeaha.110.592303

The Pattern of Leptomeningeal Collaterals on CT Angiography Is a Strong Predictor of Long-Term Functional Outcome in Stroke Patients With Large Vessel Intracranial Occlusion

2010· article· en· W2139177271 on OpenAlexaboutno aff
Fabrício Oliveira Lima, Karen L. Furie, Gisele Sampaio Silva, Michael H. Lev, Erica C. Camargo, Aneesh B. Singhal, Gordon J. Harris, Elkan F. Halpern, Walter J. Koroshetz, Wade S. Smith, Albert J. Yoo, Raul G. Nogueira

Bibliographic record

VenueStroke · 2010
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsnot available
FundersNational Institute of Neurological Disorders and StrokeAgency for Healthcare Research and Quality
KeywordsMedicineModified Rankin ScaleStroke (engine)Interquartile rangeCollateral circulationInternal medicineCardiologyAtrial fibrillationMiddle cerebral arteryUnivariate analysisAngiographyOcclusionMultivariate analysisRadiologyIschemiaIschemic stroke

Abstract

fetched live from OpenAlex

BACKGROUND AND PURPOSE: The role of noninvasive methods in the evaluation of collateral circulation has yet to be defined. We hypothesized that a favorable pattern of leptomeningeal collaterals, as identified by CT angiography, correlates with improved outcomes. METHODS: Data from a prospective cohort study at 2 university-based hospitals where CT angiography was systematically performed in the acute phase of ischemic stroke were analyzed. Patients with complete occlusion of the intracranial internal carotid artery and/or the middle cerebral artery (M1 or M2 segments) were selected. The leptomeningeal collateral pattern was graded as a 3-category ordinal variable (less, equal, or greater than the unaffected contralateral hemisphere). Univariate and multivariate analyses were performed to define the independent predictors of good outcome at 6 months (modified Rankin Scale score ≤2). RESULTS: One hundred ninety-six patients were selected. The mean age was 69±17 years and the median National Institute of Health Stroke Scale score was 13 (interquartile range, 6 to 17). In the univariate analysis, age, baseline National Institute of Health Stroke Scale score, prestroke modified Rankin Scale score, Alberta Stroke Programme Early CT score, admission blood glucose, history of hypertension, coronary artery disease, congestive heart failure, atrial fibrillation, site of occlusion, and collateral pattern were predictors of outcome. In the multivariate analysis, age (OR, 0.95; 95% CI, 0.93 to 0.98; P=0.001), baseline National Institute of Health Stroke Scale (OR, 0.75; 0.69 to 0.83; P<0.001), prestroke modified Rankin Scale score (OR, 0.41; 0.22 to 0.76; P=0.01), intravenous recombinant tissue plasminogen activator (OR, 4.92; 1.83 to 13.25; P=0.01), diabetes (OR, 0.31; 0.01 to 0.98; P=0.046), and leptomeningeal collaterals (OR, 1.93; 1.06 to 3.34; P=0.03) were identified as independent predictors of good outcome. CONCLUSIONS: Consistent with angiographic studies, leptomeningeal collaterals on CT angiography are also a reliable marker of good outcome in ischemic stroke.

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)0.000
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 score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.247
Teacher spread0.239 · 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

Citations353
Published2010
Admission routes1
Has abstractyes

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