Long-term morbidity and mortality in patients without early complications after stroke or transient ischemic attack
Bibliographic record
Abstract
BACKGROUND: Secondary prevention after stroke and transient ischemic attack (TIA) has focused on high early risk of recurrence, but survivors of stroke can have substantial long-term morbidity and mortality. We quantified long-term morbidity and mortality for patients who had no early complications after stroke or TIA and community-based controls. METHODS: This longitudinal case-control study included all ambulatory or hospitalized patients with stroke or TIA (discharged from regional stroke centres in Ontario from 2003 to 2013) who survived for 90 days without recurrent stroke, myocardial infarction, all-cause admission to hospital, admission to an institution or death. Cases and controls were matched on age, sex and geographic location. The primary composite outcome was death, stroke, myocardial infarction, or admission to long-term or continuing care. We calculated 1-, 3- and 5-year rates of composite and individual outcomes and used cause-specific Cox regression to estimate long-term hazards for cases versus controls and for patients with stroke versus those with TIA. RESULTS: = 26 366), the hazard of the primary outcome was more than double at 1 year (hazard ratio [HR] 2.4, 95% confidence interval [CI] 2.3-2.5), 3 years (HR 2.2, 95% CI 2.1-2.3) and 5 years (HR 2.1, 95% CI 2.1-2.2). Hazard was highest for recurrent stroke at 1 year (HR 6.8, 95% CI 6.1-7.5), continuing to 5 years (HR 5.1, 95% CI 4.8-5.5), and for admission to an institution (HR 2.1, 95% CI 1.9-2.2). Survivors of stroke had higher mortality and morbidity, but 31.5% (1789/5677) of patients with TIA experienced an adverse event within 5 years. INTERPRETATION: Patients who survive stroke or TIA without early complications are typically discharged from secondary stroke prevention services. However, these patients remain at substantial long-term risk, particularly for recurrent stroke and admission to an institution. Novel approaches to prevention, potentially embedded in community or primary care, are required for long-term management of these initially stable but high-risk patients.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".