Levels of physical activity before and after stroke in relation to early cognitive function
Bibliographic record
Abstract
Regular physical activity is widely recommended in the primary and secondary prevention of stroke. Physical activity may enhance cognitive performance after stroke, but cognitive impairments could also hinder a person to take part in physical activity. However, a majority of previous studies have not found any association between post-stroke cognitive impairments and a person's subsequent level of activity. In this explorative, longitudinal study, we describe the intraindividual change in physical activity from before to 6 months after stroke, in relation to early screening of post-stroke cognitive impairments. Participants were recruited at 2 to 15 days after stroke, and screened for cognitive impairments using the Montreal Cognitive Assessment tool. Information on pre-stroke physical activity was retrospectively collected at hospital admittance by physiotherapists. Post-stroke physical activity was evaluated after 6 months. Of 49 participants included, 44 were followed up. The level of physical activity changed in more than half of all participants after stroke. Participants who were physically active 6 months after stroke presented with significantly less cognitive impairments. These results highlight that many stroke survivors experience a change in their physical activity level following stroke, and that unimpaired cognition may be important for a stroke survivors' ability to be physically active.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".