Physical activity and brain health in patients with atrial fibrillation
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Vascular brain lesions, such as ischemic infarcts, are common among patients with atrial fibrillation (AF) and are associated with impaired cognitive function. The role of physical activity (PA) in the prevalence of brain lesions and cognition in AF has not been investigated. METHODS: Patients from the multicenter Swiss-AF cohort study were included in this cross-sectional analysis. We assessed regular exercise (RE; at least once weekly) and minutes of weekly PA using a validated questionnaire. We studied associations with ischemic infarcts, white matter hyperintensities, cerebral microbleeds, and brain volume on brain magnetic resonance imaging and with global cognition measured with a cognitive construct (CoCo) score. RESULTS: Among 1490 participants (mean age = 72 ± 9 years), 730 (49%) engaged in RE. In adjusted regression analyses, RE was associated with a lower prevalence of ischemic infarcts (odds ratio [OR] = 0.78, 95% confidence interval [CI] = 0.63-0.98, p = 0.03) and of moderate to severe white matter hyperintensities (OR = 0.78, 95% CI = 0.62-0.99, p = 0.04), higher brain volume (β-coefficient = 10.73, 95% CI = 2.37-19.09, p = 0.01), and higher CoCo score (β-coefficient = 0.08, 95% CI = 0.03-0.12, p < 0.001). Increasing weekly PA was associated with higher brain volume (β-coefficient = 1.40, 95% CI = 0.65-2.15, p < 0.001). CONCLUSIONS: In AF patients, RE was associated with a lower prevalence of ischemic infarcts and of moderate to severe white matter disease, with larger brain volume, and with better cognitive performance. Prospective studies are needed to investigate whether these associations are causal. Until then, our findings suggest that patients with AF should be encouraged to remain 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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".