Can exercise training promote better sleep and reduced fatigue in people with chronic stroke? A systematic review
Bibliographic record
Abstract
Poor sleep and chronic fatigue are common in people with chronic stroke (i.e. ≥ 6 months post-stroke). Exercise training is a viable, low-cost therapy for promoting sleep and reducing fatigue; however, the effects of exercise on sleep and fatigue in people with chronic stroke are unclear. Thus, we conducted a systematic review ascertaining the effects of exercise on sleep and fatigue in people with chronic stroke. We systematically searched EMBASE, MEDLINE, AgeLine, the Cochrane Database of Systematic Reviews, CINAHL, SPORTDiscus, SCOPUS, and reference lists of relevant reviews for articles that examined the effects of exercise on sleep or fatigue in chronic stroke. Search results were limited to adults ≥ 18 years, randomized controlled trials, non-randomized trials, and pre-post studies, which were published in English and examined the effects of exercise on sleep or fatigue in people with chronic stroke. We extracted study characteristics and information on the measurement of sleep and fatigue, and assessed study quality and risk of bias using the CONSORT criteria and Cochrane risk-of-bias tool, respectively. We found two studies that examined the effects of exercise on sleep, and two that examined the effects of exercise on fatigue. All studies reported positive effects of exercise training on sleep and fatigue; however, there were concerns of bias and study quality in all studies. There is preliminary evidence that exercise promotes sleep and reduces fatigue in people with chronic stroke; however, the extent to which exercise impacts these health parameters is unclear.
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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 | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.005 |
| Insufficient payload (model declined to judge) | 0.001 | 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".