Canadian Stroke Best Practice Recommendations, 7 <sup>th</sup> Edition: Cerebral Venous Thrombosis, 2024
Bibliographic record
Abstract
edition of the Canadian Stroke Best Practice Recommendations (CSBPR) is a comprehensive summary of current evidence-based recommendations, appropriate for use by healthcare providers and system planners, and intended to drive healthcare excellence, improved outcomes and more integrated health systems. This edition includes a new module on the management of cerebral venous thrombosis (CVT). Cerebral venous thrombosis is defined as thrombosis of the veins of the brain, including the dural venous sinuses and/or cortical or deep veins. Cerebral venous thrombosis is a rare but potentially life-threatening type of stroke, representing 0.5-1.0% of all stroke admissions. The reported rates of CVT are approximately 10-20 per million and appear to be increasing over time. The risk of CVT is higher in women and often associated with oral contraceptive use and with pregnancy and the puerperium. This guideline addresses care for adult individuals who present to the healthcare system with current or recent symptoms of CVT. The recommendations cover the continuum of care from diagnosis and initial clinical assessment of symptomatic CVT, to acute treatment of symptomatic CVT, post-acute management, person-centered care, special considerations in the long-term management of CVT, including pregnancy and considerations related to CVT in special circumstances such as trauma and vaccination. This module also includes supporting materials such as implementation resources to facilitate the adoption of evidence into practice and performance measures to enable monitoring of uptake and effectiveness of recommendations.
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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 | 0.006 | 0.070 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.075 | 0.038 |
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".