Association Between Motor and Cognitive Performances in Elderly With Atrial Fibrillation: Strat-AF Study
Bibliographic record
Abstract
Background/Objective. Growing evidence suggests a close relationship between motor and cognitive abilities, but possible common underlying mechanisms are not well established. Atrial fibrillation (AF) is associated with reduced physical performance and increased risk of cognitive decline. The study aimed to assess in a cohort of elderly AF patients: 1) the association between motor and cognitive performances and 2) the influence and potential mediating role of cerebral lesions burden. Design. Strat-AF is a prospective, observational study investigating biological markers for cerebral bleeding risk stratification in AF patients on oral anticoagulants. Baseline cross-sectional data are here presented. Setting. Thrombosis Centre outpatient-clinic (Careggi-University Hospital). Participants. One-hundred and seventy patients (mean age 77.7±6.8; females 35%). Measurements. Baseline protocol included: neuropsychological battery, motor assessment (Short Physical Performance Battery - SPPB, and walking speed), and brain magnetic resonance imaging (MRI) used for the visual assessment of white matter hyperintensities, lacunar and non-lacunar infarcts, cerebral microbleeds, global cortical and medial temporal atrophies. Results. Mean Montreal Cognitive Assessment (MoCA) total score was 21.9±3.9, SPPB total score 9.5±2.2, and walking speed 0.9±0.2. In univariate analyses, both SPPB and walking speed were significantly associated with MoCA (r=.359, r=.372, respectively), Visual search (r=.361, r=.322), Stroop (r=-.272, r=-.263), Short story (r=.263, r=.310) and Semantic fluency (r=.311, r=.360). In multivariate models adjusted for demographics, heart failure, physical activity and either stroke history (Model 1) or neuroimaging markers (Model 2), both SPPB and walking speed were confirmed significantly associated with MoCA (Model 1: β=.256, β=.236; Model 2: β=.276, β=.272, respectively), Visual Search (Model 1: β=.350, β=.313; Model 2: β=.344, β=.307), semantic fluency (Model 1: β=.223, β=.261), and short story (Model 2: β=.245, β=.273). Conclusions. In our cohort of elderly AF patients, a direct association between motor and cognitive functions consistently recurred using different evaluation of the performances, without an evident mediating role of cerebral lesions burden.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".