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Record W2131212015 · doi:10.3174/ajnr.a0975

Accuracy of the Alberta Stroke Program Early CT Score during the First 3 Hours of Middle Cerebral Artery Stroke: Comparison of Noncontrast CT, CT Angiography Source Images, and CT Perfusion

2008· article· en· W2131212015 on OpenAlexaboutno aff
Ke Lin, Otto Rapalino, James S. Babb, K Siller, Bidyut K. Pramanik

Bibliographic record

VenueAmerican Journal of Neuroradiology · 2008
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineRadiologyStroke (engine)Middle cerebral arteryAngiographyPerfusionPerfusion scanningCerebral angiographyNuclear medicineCardiologyIschemia

Abstract

fetched live from OpenAlex

BACKGROUND AND PURPOSE: The Alberta Stroke Program Early CT Score (ASPECTS) is a reliable method of delineating the extent of middle cerebral artery (MCA) stroke. Our aim was to retrospectively compare the accuracy of ASPECTS on noncontrast CT, CT angiography (CTA) source images, and CT perfusion maps of cerebral blood volume (CBV) during the first 3 hours of middle cerebral artery (MCA) stroke. MATERIALS AND METHODS: First-time patients with MCA stroke who presented <3 hours from symptom onset and were evaluated by noncontrast CT/CTA/CT perfusion, had confirmed acute nonlacunar MCA infarct on diffusion-weighted MR imaging (DWI) within 7 days, and had follow-up angiography were included. Patients were excluded for persistent MCA occlusion or stenosis. Two raters through consensus assigned an ASPECTS on the noncontrast CT, CTA source images, and the section-selective (2 x 12 mm coverage) CT perfusion CBV maps. ASPECTS on follow-up DWI served as the reference standard. For each CT technique, the detection rates of regional infarction, the mean ASPECTS, and the linear correlation to final ASPECTS were determined and compared. P values <.05 were considered significant. RESULTS: Twenty-eight patients satisfied the criteria with DWI performed at a mean of 50.3 hours (range, 22-125 hours) post-CT imaging. Of 280 ASPECTS regions, 100 were infarcted on DWI. The accuracy of noncontrast CT, CTA source images, and CT perfusion CBV for detecting regional infarct was 80.0%, 84.3%, and 96.8%, respectively (P < .0001). The mean ASPECTSs of noncontrast CT, CTA source images, CT perfusion CBV, and DWI were 8.4 +/- 1.8, 8.0 +/- 1.8, 6.8 +/- 1.9, and 6.5 +/- 1.8, respectively. The mean noncontrast CT and CTA source image ASPECTS was different from that of DWI (P < .05). Correlation of noncontrast CT, CTA source images, and CT perfusion CBV ASPECTS with final ASPECTS was r(2) = 0.34, r(2) = 0.42, and r(2) = 0.91, respectively. CONCLUSION: In a retrospective cohort of MCA infarcts imaged <3 hours from stroke onset, ASPECTS was most accurately determined on CT perfusion CBV maps.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.753

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.014
GPT teacher head0.246
Teacher spread0.232 · 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

Citations106
Published2008
Admission routes1
Has abstractyes

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