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Record W1578438881 · doi:10.1161/str.45.suppl_1.wp367

Abstract W P367: Anterior Cerebral Artery Diameter Predicts Anterior Cerebral Artery Territorial Stroke.

2014· article· en· W1578438881 on OpenAlexaff
Ashkan Shoamanesh, Hesham Masoud, Katrina Weed, Kaylyn Duerfeldt, Helena Lau, José R. Romero, Aleksandra Pikula, Philip Teal, Thanh N. Nguyen, Carlos S. Kase, Viken L. Babikian

Bibliographic record

VenueStroke · 2014
Typearticle
Languageen
FieldMedicine
TopicCerebrovascular and Carotid Artery Diseases
Canadian institutionsVancouver General Hospital
Fundersnot available
KeywordsMedicineAnterior cerebral arteryCardiologyStroke (engine)Internal medicineInternal carotid arteryEtiologyMagnetic resonance imagingConcomitantRadiologyEmbolismMiddle cerebral arteryIschemia

Abstract

fetched live from OpenAlex

Background: Anterior cerebral artery strokes (ACAS) account for only 1-2% of cerebral infarctions, and typically result from embolism in western populations. The cause of the low frequency of ACAS in relation to MCA strokes (MCAS) is uncertain, but differences in arterial anatomy may affect flow-directed embolism rates. We aimed to determine whether variability in ACA A1 diameters (A1D) and A1D/MCA M1 diameter (M1D) ratios predict ACAS Methods: Consecutive patients admitted to Boston Medical Center with a diagnosis of ACAS between 01/2008-10/2012 were reviewed. Patients with an interpretable CT angiogram (CTA) or magnetic resonance angiogram (MRA) of the cerebral vasculature were eligible. Excluded were patients with ACAS ipsilateral (ipsi) to an aplastic ACA, concomitant ipsi MCAS, and those with lacunar, watershed, aneurysm clipping or local intracranial atherosclerosis as stroke etiology. Patient demographics were compiled. Ipsilateral and contralateral (contra) A1D, M1D, as well as ICA-ACA and ICA-MCA angles were measured from CTA and MRA images. Consecutive MCAS admitted between 01/2011-10/2012 served as controls. Results: The study comprised 55 individuals (27 ACA, 28 MCA) with mean age of 69 years. Stroke etiology was cardioembolism in 56%, internal carotid artery embolism in 16% and idiopathic in 27%. Patients with ACAS had larger mean ipsi A1D (2.47 vs. 2.05 mm,p<0.01), ipsi A1D/M1D ratios (0.95 vs. 0.73,p<0.001) and were more likely to have a contra aplastic/hypoplastic ACA (41 vs. 4%,<0.001). Ipsi A1D (OR per 1 mm increment: 8.52 [95% CI 1.36, 53.26]) and ipsi A1D/M1D ratio (OR per 10% increment: 1.83 [95% CI 1.15, 2.91]) remained significant following multivariate analysis. Ipsilateral M1D was protective for ACAS (OR per 1 mm increment: 0.17 [95% CI 0.03, 0.90]) after adjusting for ipsi A1D. There were no significant differences in demographic variables, stroke etiologies, terminal ICA-ACA or ICA-MCA angles between ACAS and MCAS. Conclusions: Larger ipsilateral A1D and A1D/M1D ratio are independent predictors of ACAS. These findings concur with the notion that A1D and M1D are important in determining the path of emboli that reach the terminal ICA.

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)0.002
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 score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.230
Teacher spread0.222 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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