High- and low-intensity exercise do not improve cognitive function after stroke: A randomized controlled trial
Bibliographic record
Abstract
OBJECTIVE: To determine the effects of high versus low-intensity exercise on cognitive function following stroke. DESIGN: Secondary analysis from a randomized controlled trial with blinded assessors. SUBJECTS: 50-80 years old, living in the community, > 1 year post-stroke. METHODS: Participants were randomized into a high-intensity Aerobic Exercise or low-intensity non-aerobic Balance/Flexibility program. Both programs were 6 months long, with 3 60-min sessions/week. Verbal item and working memory, selective attention and conflict resolution, set shifting were assessed before and after the program. RESULTS: Forty-seven participants completed the study (22/25 in Aerobic Exercise group, 25/25 in Balance/Flexibility group). There was an improvement in verbal item memory in both groups (time effect p = 0.04), and no between-group differences in improvement in the other outcomes (p > 0.27). There was no association between pre-exercise cognitive function and post-exercise improvement. CONCLUSIONS: In contrast to a small body of previous research suggesting positive benefits of exercise on cognition post-stroke, the current study found that 6 months of high or low intensity exercise was not effective in improving cognitive function, specifically executive functions. Further research in this area is warranted to establish the effectiveness of post-stroke exercise programs on cognition, and examine the mechanisms that underlie these changes.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".