Canadian Stroke Best Practice Recommendations Rehabilitation, Recovery, and Community Participation Following Stroke, Part Two: Delivery of Stroke Rehabilitation to Optimize Functional Recovery, 7th Edition Update 2025
Bibliographic record
Abstract
ABSTRACT: The Canadian Stroke Best Practice Recommendations 7 th edition update of the Rehabilitation, Recovery and Community Participation module is presented in three parts. This publication, Part Two of the series, reflects the growing and changing body of research evidence available to guide direct stroke rehabilitation therapies, screening, assessment, interventions, and strategies. Topics in this module include rehabilitation of upper and lower extremity, aerobic function, balance, mobility, activities of daily living, spasticity, fall risk, communication, dysphagia, nutrition, central pain, visual and visual-perceptual issues, and bladder and bowel function. This module provides guidance in the delivery of coordinated and seamless systems of care that support timely access to rehabilitation therapies, building on progress achieved during initial recovery, enabling people to achieve as much independence as possible and successfully resume social roles and leisure activities. Successful recovery, transitions and community participation require integrated and coordinated people-centered efforts by all members of care teams involved, and the broader community. These recommendations were developed with active involvement of people with lived experience of stroke throughout the care continuum. Evidence for effective rehabilitation therapies and support for individuals with stroke and their families continues to emerge and gaps in knowledge should drive future research.
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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 | 0.011 | 0.041 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.007 | 0.003 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.019 | 0.009 |
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".