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Record W2613693561 · doi:10.1161/strokeaha.117.016745

ASPECTS (Alberta Stroke Program Early CT Score) Measurement Using Hounsfield Unit Values When Selecting Patients for Stroke Thrombectomy

2017· article· en· W2613693561 on OpenAlexaboutno aff
Maxim Mokin, Christopher T. Primiani, Adnan H. Siddiqui, Aquilla S Turk

Bibliographic record

VenueStroke · 2017
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHounsfield scaleThrombolysisStroke (engine)Middle cerebral arteryRevascularizationOcclusionCerebral infarctionNuclear medicineRadiologyCohortCardiologyInternal medicineComputed tomographyIschemiaMyocardial infarction

Abstract

fetched live from OpenAlex

BACKGROUND AND PURPOSE: The ASPECTS (Alberta Stroke Program Early CT Score) is a quantitate score that measures the extent of early ischemic changes. Our aim was to investigate how measurement of ASPECTS using Hounsfield unit (HU) values on initial noncontrast head computerized tomography (CT) correlates with the extent of final infarct on follow-up imaging. METHODS: Cases of acute stroke from the middle cerebral artery M1 occlusion in which complete recanalization (TICI [Thrombolysis in Cerebral Infarction] 3) was achieved were included for analysis. Using HU ratio (HU affected/HU control hemisphere) and HU difference (HU control-HU affected hemisphere) values, ASPECTS was measured on initial CT imaging and correlated with final ASPECTS at 24 hours. The study cohort consisted of 41 patients with acute stroke from the M1 occlusion. The mean time from stroke symptoms onset to baseline head CT imaging was 264 minutes and from CT to TICI 3 recanalization was 142 minutes. RESULTS: <0.0001) and the lowest mean and median absolute errors (1.4 and 1, respectively). CONCLUSIONS: We established a simple algorithm for rapid and accurate assessment of ASPECTS on baseline CT imaging to predict the extent of final stroke in patients with emergent large vessel occlusion who undergo endovascular revascularization.

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 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 score0.353
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.071
GPT teacher head0.318
Teacher spread0.247 · 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

Citations93
Published2017
Admission routes1
Has abstractyes

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