<i>Canadian Stroke Best Practice Recommendations</i>: Secondary Prevention of Stroke Guidelines, Update 2014
Bibliographic record
Abstract
Every year, approximately 62,000 people with stroke and transient ischemic attack are treated in Canadian hospitals. The 2014 update of the Canadian Secondary Prevention of Stroke guideline is a comprehensive summary of current evidence-based recommendations for clinicians in a range of settings, who provide care to patients following stroke. Notable changes in this 5th edition include an emphasis on treating the highest risk patients who present within 48 h of symptom onset with transient or persistent motor or speech symptoms, who need to be transported to the closest emergency department with capacity for advanced stroke care; a recommendation for brain and vascular imaging (of the intra- and extracranial vessels) to be completed urgently using computed tomography/computed tomography angiography; prolonged cardiac monitoring for patients with suspective cardioembolic stroke but without evidence for atrial fibrillation on electrocardiogram or holter monitoring; and de-emphasizing the need for routine echocardiogram. The Canadian Stroke Best Practice Recommendations include a range of supporting materials such as implementation resources to facilitate the adoption of evidence to practice, and related performance measures to enable monitoring of uptake and effectiveness of the recommendations using a standardized approach. The guidelines further emphasize the need for a systems approach to stroke care, involving an interprofessional team, with access to specialists regardless of patient location, and the need to overcome geographical barriers to ensure equity in access within a universal health-care system.
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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 | 0.005 | 0.030 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.020 | 0.011 |
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".