Long-term neurological, vascular, and mortality outcomes after stroke
Bibliographic record
Abstract
Background Despite improved survival and short-term (90-day) outcomes of ischemic stroke patients, only sparse data exist describing the sustained benefits of acute stroke care interventions and long-term prognosis of stroke survivors. Aim We review the contemporary literature assessing long-term (5 years or more) outcomes after stroke and acute stroke treatment. Summary of review Acute stroke unit care and intravenous thrombolysis have sustained benefits over longer follow-up, but few data exist on the long-term outcome after endovascular thrombectomy (EVT). A large proportion of stroke survivors face challenges of residual disability and neuropsychiatric sequelae (especially affective disorders and epilepsy) which affects their quality of life and is associated with poorer prognosis due to increase in stroke recurrences/mortality. Nearly, a quarter of stroke survivors have a recurrent stroke at 5 years, and nearly double that at 10 years. Mortality after recurrent stroke is high, and half of the stroke survivors are deceased at 5 years after stroke and three fourth at 10 years. Long-term all-cause mortality is largely due to conditions other than stroke. Both stroke recurrence and long-term mortality are affected by several modifiable risk factors, and thus amenable to secondary prevention strategies. Conclusions There is a need for studies reporting longer term effects of acute interventions, especially EVT. Better preventive strategies are warranted to reduce the vascular and non-vascular mortality long after stroke.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 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".