Risks and Benefits of Thrombolysis in the Elderly
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Stroke incidence continues to rise exponentially with age even as temporal trends in some population risk factors increase and others decline. In general, older patients with stroke have worse outcomes compared to their younger counterparts. Stroke severity, concurrent medical problems, prestroke disability, and less-aggressive acute and chronic management are a few contributing factors to account for this poor prognosis. Acute thrombolysis therapy is the only proven treatment in acute ischemic stroke. However, elderly patients have mostly been excluded from acute revascularization studies, due predominantly to their overall poor prognosis and the fear of hemorrhagic complications from these treatments. Despite this, there is no evidence to suggest that the risk benefit ratio of thrombolysis treatment is substantially different in the elderly than in younger ischemic stroke patients. SUMMARY OF REVIEW: In this review, we briefly examine the stroke risk factor profile and outcome in the elderly and review the current evidence regarding intravenous and intra-arterial revascularization treatments. CONCLUSION: We feel that carefully selected patients who meet eligibility criteria for thrombolysis should not be denied this therapy on the basis of age alone.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".