Abstract P016: Association Between Life’S Simple 7 Score And Cognitive Status In Older Adults With Atrial Fibrillation
Bibliographic record
Abstract
Introduction: The American Heart Association’s Life’s Simple 7 (LS7) score is a well-validated metric of cardiovascular health shown to be associated with cognitive status in numerous cardiac cohorts. However, little is known regarding this relationship in older adults with atrial fibrillation (AF). We aim to characterize LS7 scores in this population and examine its relationship with cognitive status. Hypothesis: We hypothesize that LS7 score is associated with cognitive status in older adults with AF. Methods: The Systematic Assessment of Geriatric Elements in AF (SAGE-AF) study is a longitudinal cohort of patients over 65 years of age who are diagnosed with AF from Massachusetts and Georgia. The LS7 components are collected through self-reported data from the baseline visit as well as medical records. Cognitive status is operationalized using the Montreal Cognitive Assessment (MoCA). Descriptive statistics were calculated and univariate logistic regression using tertiles of LS7 as exposure was used to assess the relationship between LS7 score and cognitive status. Results: A total of 1241 participants were included in study sample. Average age of the population was 76, 49% were female, and most of the sample were White (89%). Mean LS7 score was 7.92 (SD 2.05), and the tertile thresholds were 0-6, 7-9, and 10-14 (n = 302, 671, 268). Those in the lowest and middle tertiles of LS7 score were more likely than those in the highest to be cognitively impaired (lowest - OR 1.86, 95% CI 1.33 - 2.61; middle - OR 1.52, 95% CI 1.14 - 2.03) Conclusions: Most older adults with AF had LS7 scores of between 7-9 out of 14, and those with more favorable cardiovascular health were less likely to be cognitively impaired.
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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 | 0.003 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".