A Prospective Cohort Study of Patients With Transient Ischemic Attack to Identify High-Risk Clinical Characteristics
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The occurrence of a transient ischemic attack (TIA) increases an individual's risk for subsequent stroke. The objectives of this study were to determine clinical features of patients with TIA associated with impending (≤7 days) stroke and to develop a clinical prediction score for impending stroke. METHODS: We conducted a prospective cohort study at 8 Canadian emergency departments for 5 years. We enrolled patients with a new TIA. Our outcome was subsequent stroke within 7 days of TIA diagnosis. RESULTS: We prospectively enrolled 3906 patients, of which 86 (2.2%) experienced a stroke within 7 days. Clinical features strongly correlated with having an impending stroke included first-ever TIA, language disturbance, longer duration, weakness, gait disturbance, elevated blood pressure, atrial fibrillation on ECG, infarction on computed tomography, and elevated blood glucose. Variables less associated with having an impending stroke included vertigo, lightheadedness, and visual loss. From this cohort, we derived the Canadian TIA Score which identifies the risk of subsequent stroke≤7 days and consists of 13 variables. This model has good discrimination with a c-statistic of 0.77 (95% confidence interval, 0.73-0.82). CONCLUSIONS: Patients with TIA with their first TIA, language disturbance, duration of symptoms≥10 minutes, gait disturbance, atrial fibrillation, infarction on computed tomography, elevated platelets or glucose, unilateral weakness, history of carotid stenosis, and elevated diastolic blood pressure are at higher risk for an impending stroke. Patients with vertigo and no high-risk features are at low risk. The Canadian TIA Score quantifies the impending stroke risk following TIA.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".