Understanding how cardiorespiratory training is implemented to address cardiorespiratory fitness in adults following a stroke: a systematic review
Bibliographic record
Abstract
PURPOSE: To systematically review the evidence investigating the implementation of cardiorespiratory (CR) training in adults following a stroke and to understand how interventions are prescribed to address cardiorespiratory fitness (CRF). METHODS: Medline, CINAHL, EMBASE, EMCARE, Scopus, PEDro and ProQuest were searched from inception until January 2024. Inclusion criteria were studies that included adults following a stroke, investigated CR training interventions and used standardised CRF assessments. Commentaries, review publications and non-English studies were excluded. RESULTS: A total of 8565 studies were identified and 121 met the selection criteria. A broad range of participant demographics, stroke characteristics and clinical presentations were identified. Of the included studies, 14% selected only participants within 3-months following stroke and 5% selected only participants requiring assistance to ambulate. Different standardised CRF assessments were used, and CR training intervention parameters varied (frequency, intensity, type, time, volume and progressions). Three studies included qualitative participant perspectives regarding participation in CRF interventions. CONCLUSIONS: A variety of CR training interventions and parameters are used to address CRF following stroke, and experiences of participants is not well understood. Future studies should explore CR training interventions for improving CRF, particularly in people requiring assistance to ambulate, or within sub-acute stroke timeframes.
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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 | 0.006 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".