The interaction effect of physical activity and sleep on cognitive function in stroke
Bibliographic record
Abstract
Abstract INTRODUCTION Having a stroke increases risk for dementia two‐fold. Poor sleep quality and quantity are common after a stroke and are associated with cognitive impairment. Physical activity benefits cognitive function. Whether there is an interaction effect of physical activity and sleep on cognitive function among persons living with chronic stroke is unknown. METHODS A cross‐sectional study used baseline data acquired from 97 community‐dwelling adults aged ≥55 years, living with chronic stroke (71±9 years; n = 38, female), and enrolled in a 6‐month randomized controlled trial. We measured physical activity (i.e., moderate to vigorous physical activity [MVPA] and light physical activity [PA]) and sleep quality and quantity (i.e., efficiency, latency, duration) using wrist‐worn accelerometry. Global cognitive function was measured with the 13‐item Alzheimer's Disease Assessment Scale–Cognitive Subscale (ADAS‐Cog‐13). We assessed whether the interaction of physical activity (MVPA and light PA) with sleep quality and quantity (interaction term: physical activity * sleep) was associated with ADAS‐Cog‐13 score: (1) in the full sample and (2) among males and females separately (i.e., sex‐stratified). Significant moderations were plotted as continuous simple slopes. RESULTS In the full sample, there was a significant interaction effect between MVPA and sleep duration on the ADAS‐COG‐13 score (ß = 1.636 ± 0.787; p = 0.041). Specifically, among individuals with shorter sleep duration (i.e., one standard deviation below mean sleep duration), those with greater MVPA had better ADAS‐Cog‐13 performance. In the sex‐stratified analysis, the interaction effect of MVPA and sleep duration on cognitive function was significant in males (ß = 3.417 ± 1.374; p = 0.016) but not females. DISCUSSION Moderate to vigerous physical activity may mitigate the negative impact of shorter sleep on cognitive function among persons living with stroke, particularly males. Highlights Physical activity and sleep are associated with cognitive function following stroke. Physical activity may ameliorate the negative effects of poor sleep on cognitive function. Females suffer greater health consequences of sleep dysregulation than males. Physical activity moderates the association of sleep duration and cognitive function. Physical activity may promote cognitive function in males with short sleep duration.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| 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) | 0.003 | 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".