Canadian Stroke Best Practice Consensus Statement: <i>Acute Stroke Management during pregnancy</i>
Bibliographic record
Abstract
The Canadian Stroke Best Practice Consensus Statement Acute Stroke Management during Pregnancy is the second of a two-part series devoted to stroke in pregnancy. The first part focused on the unique aspects of secondary stroke prevention in a woman with a prior history of stroke who is, or is planning to become, pregnant. This document focuses on the management of a woman who experiences an acute stroke during pregnancy. This consensus statement was developed in recognition of the need for a specifically tailored approach to the management of this group of patients in the absence of any broad-based, stroke-specific guidelines or consensus statements, which do not exist currently. The foundation for the development of this document was the concept that maternal health is vital for fetal well-being; therefore, management decisions should be based first on the confluence of two clinical considerations: (a) decisions that would be made if the patient wasn't pregnant and (b) decisions that would be made if the patient hadn't had a stroke, then nuanced as needed. While empirical research in this area is limited, this consensus document is based on the best available literature and guided by expert consensus. Issues addressed in this document include initial emergency management, diagnostic imaging, acute stroke treatment, the management of hemorrhagic stroke, anesthetic management, post stroke management for women with a stroke in pregnancy, intrapartum considerations, and postpartum management. These statements are appropriate for healthcare professionals across all disciplines and system planners to ensure pregnant women who experience a stroke have timely access to both expert neurological and obstetric care.
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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 | 0.029 | 0.101 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.009 | 0.006 |
| Research integrity | 0.013 | 0.017 |
| Insufficient payload (model declined to judge) | 0.016 | 0.013 |
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".