Aerobic Training in Canadian Stroke Rehabilitation Programs
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Aerobic training (AT) is recommended for people after stroke, yet uptake and operationalization of AT in clinical practice in Canada have not been measured. We surveyed inclusion of structured AT and barriers to implementation in public inpatient/outpatient stroke rehabilitation programs across Canada. METHODS: A Web-based questionnaire was sent to 89 stroke rehabilitation program leads. RESULTS: Forty-six programs from 7 of 9 eligible Canadian provinces/territories completed the questionnaire. Seventy-eight percent of programs reported including AT, with most (75%) excluding participants with severe physical impairments, and 28% excluding those with coexisting cardiac conditions. A greater proportion of dedicated stroke rehabilitation programs prescribed AT, compared to nondedicated stroke units (68.8% vs 31.3%, P = 0.02). The top 2 challenges for programs that included and did not include AT were "insufficient time within therapy sessions" and "length of stay in rehabilitation." Programs that did not include AT ranked "not a goal of most patients" and "not an organizational/program priority" as third and fourth, whereas they were ranked eighth and thirteenth by programs with AT. Best practice recommendations were inconsistently followed for conducting preparticipation exercise testing (36.1%) and for monitoring patients from higher-risk populations, specifically people with diabetes at risk for hypoglycemia (78.8%) and hypertension (36.6%). Of programs conducting preparticipation exercise testing, 91% did not monitor electrocardiography. DISCUSSION AND CONCLUSIONS: Most stroke rehabilitation programs across Canada include AT. People with severe physical impairment and those with cardiac, metabolic, and hemodynamic comorbidities may be excluded or not appropriately monitored during exercise. More detailed guidelines and training practices are needed to address these challenges.Video Abstract available for more insights from the authors (see Video, Supplemental Digital Content 1, available at: http://links.lww.com/JNPT/A233).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".