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Record W2121880538 · doi:10.1503/cmaj.101668

Prospective validation of the ABCD2 score for patients in the emergency department with transient ischemic attack

2011· article· en· W2121880538 on OpenAlexafffundvenueabout
Jeffrey J. Perry, Mukul Sharma, Marco L.A. Sivilotti, Jane Sutherland, Cheryl Symington, Andrew Worster, Marcel Émond, Grant Stotts, Albert Jin, W. J. Oczkowski, Demetrios J. Sahlas, Heather Murray, Ariane Mackey, Steve Verreault, George A. Wells, Ian G. Stiell

Bibliographic record

VenueCanadian Medical Association Journal · 2011
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsUniversity of Ottawa
FundersCanadian Institutes of Health Research
KeywordsEmergency departmentTransient (computer programming)MedicineProspective cohort studyComputer scienceEmergency medicineMedical emergencyInternal medicinePsychiatryOperating system

Abstract

fetched live from OpenAlex

BACKGROUND: The ABCD2 score (Age, Blood pressure, Clinical features, Duration of symptoms and Diabetes) is used to identify patients having a transient ischemic attack who are at high risk for imminent stroke. However, despite its widespread implementation, the ABCD2 score has not yet been prospectively validated. We assessed the accuracy of the ABCD2 score for predicting stroke at 7 (primary outcome) and 90 days. METHODS: This prospective cohort study enrolled adults from eight Canadian emergency departments who had received a diagnosis of transient ischemic attack. Physicians completed data forms with the ABCD2 score before disposition. The outcome criterion, stroke, was established by a treating neurologist or by an Adjudication Committee. We calculated the sensitivity and specificity for predicting stroke 7 and 90 days after visiting the emergency department using the original "high-risk" cutpoint of an ABCD2 score of more than 5, and the American Heart Association recommendation of a score of more than 2. RESULTS: We enrolled 2056 patients (mean age 68.0 yr, 1046 (50.9%) women) who had a rate of stroke of 1.8% at 7 days and 3.2% at 90 days. An ABCD2 score of more than 5 had a sensitivity of 31.6% (95% confidence interval [CI] 19.1-47.5) for stroke at 7 days and 29.2% (95% CI 19.6-41.2) for stroke at 90 days. An ABCD2 score of more than 2 resulted in sensitivity of 94.7% (95% CI 82.7-98.5) for stroke at 7 days with a specificity of 12.5% (95% CI 11.2-14.1). The accuracy of the ABCD2 score as calculated by either the enrolling physician (area under the curve 0.56; 95% CI 0.47-0.65) or the coordinating centre (area under the curve 0.65; 95% CI 0.57-0.73) was poor. INTERPRETATION: This multicentre prospective study involving patients in emergency departments with transient ischemic attack found the ABCD2 score to be inaccurate, at any cut-point, as a predictor of imminent stroke. Furthermore, the ABCD2 score of more than 2 that is recommended by the American Heart Association is nonspecific.

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)0.000
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 score0.109
Threshold uncertainty score0.490

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.015
GPT teacher head0.240
Teacher spread0.224 · 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

Citations107
Published2011
Admission routes4
Has abstractyes

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