Stroke Prevention What Are the Options?
Bibliographic record
Abstract
Stroke is a leading cause of morbidity andmortality, accounting for 7 % of all deaths in Canada or 2,400 events for every million Canadians per year.1 Patients recovering from even a mild stroke or a recent transient ischemic attack (TIA) are at high risk of stroke recurrence, physical and intellectual disability, long-term institutionaliza-tion and death. Primary and secondary stroke prevention strategies remain critical for reducing the over-all burden of atherothrombotic disease. What are the major risk factors to consider? All patients who have suffered a stroke or TIA should receive the best possible management of any risk factors present. 1. Hypertension Treating any degree of blood pressure (BP) ele-vation, including mild hypertension, has been shown to significantly reduce stroke risk. Recent evidence suggests blockade of the renin-angiotensin system with either angio-tensin receptor blockers (ARBs) or angiotensin-converting enzyme (ACE) inhibitors may pro-vide benefits in stroke prevention beyond BP control. The Losartan Intervention For End point reduction in hypertension (LIFE) study, for
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.042 | 0.010 |
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".