Cardiopulmonary Exercise Testing in Stroke Rehabilitation: Benefits and Clinical Utility Perceived by Physiotherapists and Individuals with Stroke
Bibliographic record
Abstract
Purpose: The purpose of this study was to understand the perceived benefits and clinical utility of cardiopulmonary exercise testing (CPET) from the perspectives of physiotherapists and patients and to explore the factors that influence adopting CPET in a stroke rehabilitation setting. Method: A qualitative descriptive study was conducted. Physiotherapists ( n = 6) participated in a focus group to discuss the use of CPET in practice. Patients ( n = 8) who had completed CPET during stroke rehabilitation participated in a semi-structured interview to explore their experiences. Thematic analysis was performed. Results: CPET increased the physiotherapists’ confidence in prescribing exercise, especially for medically complex patients. Ongoing medical management early post-stroke was a barrier to referral. Physiotherapists expressed decreased confidence in interpreting test results. Consultation with local experts facilitated the use of CPET. Patients described how CPET increased their confidence to participate in exercise. They desired more information before and after CPET to better understand the purpose and results and their relation to their rehabilitation goals. Conclusions: Both physiotherapists and patients described the benefit of having CPET available to support them as they participated in exercise in a stroke rehabilitation setting. Physiotherapists would benefit from having educational tools to support their interpretation and application of test results, and patients would benefit from improved communication and education to support their understanding of the relevance of CPET to their rehabilitation goals. Future research should explore these findings in other stroke rehabilitation settings.
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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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".