Long-Term Outcomes of Ischemic Stroke of Undetermined Mechanism: A Population-Based Prospective Cohort
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Little is known about the short- and long-term outcomes of ischemic stroke of undetermined mechanism (ISUM). METHODS: Subjects were recruited from the Mashhad Stroke Incidence Study. Ischemic stroke (IS) was classified on the basis of the TOAST criteria. We further categorized patients with ISUM into ISUMneg (negative clinical/test results for large artery, small artery) and ISUMinc (incomplete investigations). Cox proportional hazard models and the competing-risk regression model were used to compare 1 and 5 years mortality (all-causes) and recurrent rate among IS subtypes. RESULTS: Overall, 1-year mortality was higher in those with ISUMinc than in ISUMneg (adjusted hazard ratio [aHR] 1.6, 95% CI 1.01-2.8; p = 0.04) and in other stroke subtypes. Cardioembolic stroke was associated with the greatest risk of stroke recurrence at one year (aHR 4.9, 95% CI 1.8-12.9; p = 0.001) and 5 years (HR 2.1, 95% CI 1.1-3.7; p = 0.01) as compared to ISUMneg. CONCLUSIONS: The classification of ISUM as a single group may lead to over- or underestimation of mortality and recurrence in this major category of IS. A better definition of ISUM is necessary to predict death and recurrence accurately.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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) | 0.001 | 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".