Canadian stroke best practice recommendations: <i>Management of Spontaneous Intracerebral Hemorrhage</i>, 7th Edition Update 2020
Bibliographic record
Abstract
Spontaneous intracerebral hemorrhage is a particularly devastating type of stroke with greater morbidity and mortality compared with ischemic stroke and can account for half or more of all deaths from stroke. The seventh update of the Canadian Stroke Best Practice Recommendations includes a new stand-alone module on intracerebral hemorrhage, with a focus on elements of care that are unique or affect persons disproportionately relative to ischemic stroke. Prior to this edition, intracerebral hemorrhage was included in the Acute Stroke Management module and was limited to its management during the first 12 h. With the growing evidence on intracerebral hemorrhage, a separate module focused on this topic across the care continuum was added. In addition to topics related to initial clinical management, neuroimaging, blood pressure management, and surgical management, new sections have been introduced addressing topics surrounding inpatient complications such as venous thromboembolism, seizure management, and increased intracranial pressure, rehabilitation as well as issues related to secondary management including lifestyle management, maintaining a normal blood pressure and antithrombotic therapy, are addressed. The Canadian Stroke Best Practice Recommendations (CSBPR) are intended to provide up-to-date evidence-based guidelines for the prevention and management of stroke and to promote optimal recovery and reintegration for people who have experienced stroke, including patients, families, and informal caregivers.
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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 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.061 | 0.040 |
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".