MétaCan
Menu
Back to cohort

Accuracy of Published Screening Tools for Large Vessel Occlusion in Patients With Suspected Acute Ischemic Stroke: A Prospective Cohort Study

2025· article· en· W4414380541 on OpenAlexafffundabout
Francis Desmeules, Marcel Émond, Alexandra Nadeau, Pierre-Gilles Blanchard, Pier‐Alexandre Tardif, Axel Benhamed, Nicolas Capolla-Daneau, Marie‐Christine Camden, Éric Mercier

Bibliographic record

VenueAnnals of Emergency Medicine · 2025
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsCentres Intégré Universitaires de Santé et de Services SociauxThe Quebec Population Health Research NetworkUniversité Laval
FundersUniversité Laval
KeywordsProspective cohort studyOcclusionStroke (engine)Cohort studyCohortIschemic strokeMEDLINE

Abstract

fetched live from OpenAlex

STUDY OBJECTIVE: To identify the most accurate screening tool for predicting a large vessel occlusion in patients with a suspected acute ischemic stroke. METHODS: Between January 2022 and April 2023, adult patients with a suspected acute ischemic stroke for whom an emergency physician activated the stroke code (indicating potential eligibility for thrombolysis and/or thrombectomy) at the emergency department (ED) of l'Hôpital de l'Enfant-Jésus-CHU de Québec, a tertiary care center for neurologic diseases, were prospectively included. Demographic data and variables included in 8 screening tools were collected by the emergency physician prior to the head computed tomography using a standardized data collection form. The performance of each tool to identify patients with a large vessel occlusion was assessed using the accuracy with 95% confidence intervals (CIs) and the McNemar test was used to compare the performance of the tools. RESULTS: A total of 390 patients were included in the study (mean age: 72.3 years; men: 48.2%). Acute ischemic strokes was the final diagnosis in 259 patients (66.4%) of which 111 (28.5%) had a large vessel occlusion. The accuracy of Field Assessment Stroke Triage for Emergency Destination (FAST-ED) was 0.76 (95% CI 0.72 to 0.81), which was not significantly different from that of Rapid Arterial Occlusion Evaluation Scale (0.75, 95% CI 0.71 to 0.80), Los Angeles Motor Scale (0.75, 95% CI 0.71 to 0.79), or Large ARtery Intracranial Occlusion stroke scale (0.72, 95% CI 0.68 to 0.77). However, it was significantly higher than the accuracy of Conveniently-Grasped FAST, Ambulance Clinical Triage-FAST, Vision, Aphasia, Neglect assessment, and Face-Arm-Speech-Time plus severe arm or leg motor deficit. Cincinnati Prehospital Stroke Scale, when performed by either the emergency physicians or paramedics, demonstrated poor accuracy, with values of 0.34 (95% CI 0.29 to 0.39) and 0.37 (95% CI 0.32 to 0.34), respectively. CONCLUSION: This study provides valuable insights into the accuracy of various large vessel occlusion screening tools for patients in our ED setting with FAST-ED, Rapid Arterial Occlusion Evaluation Scale, and Los Angeles Motor Scale showing the highest levels of accuracy. These findings will contribute to the development of evidence-based care pathways for improving stroke diagnosis and management.

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)0.002
metaresearch head score (Gemma)0.012
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 score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.030
GPT teacher head0.352
Teacher spread0.322 · 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

Citations1
Published2025
Admission routes3
Has abstractyes

Explore more

Same venueAnnals of Emergency MedicineSame topicAcute Ischemic Stroke ManagementFrench-language works237,207