Abstract 12946: Higher Burden of Atrial Fibrillation is Independently Associated With Lower Cognitive Function: The Atherosclerosis Risk in Communities (ARIC) Study
Bibliographic record
Abstract
Background: Atrial fibrillation (AF) is associated with greater cognitive decline and increased risk of dementia. However, it is unknown whether AF burden (% of time a person is in AF) is associated with cognition. We aimed to assess the cross-sectional association of AF burden with cognitive test scores in the ARIC study, a community-based prospective cohort study in the USA. Methods: We included 325 (mean age, 76.9 ± 5.2 years; 52.9% female) participants who underwent cognitive tests (Table) and ≥2 days of heart rhythm recording using the Zio ® Patch (a non-invasive, leadless, 2-week continuous ECG recording device by iRhythm Techonologies, Inc.) in July 2013-March 2014. We used multivariable linear regression to assess the association of AF burden (dichotomized at the median) with standardized z-scores of cognitive tests. Results: The mean wear and analysis time of the Zio ® Patch were 13.1 ± 2.1 and 12.7 ± 2.3 days, respectively. Of 325 participants, 13 (4.0%) had a prior ischemic stroke. There were 26 (8%) participants with AF recorded (median AF burden among participants with AF, 51%), of whom 4 (15.4%) had a prior ischemic stroke. Compared with absence of AF, higher AF burden was independently associated with lower MMSE, DWR, and AN scores, but not DSS and CTP. Conclusions: Higher burden of AF is independently associated with lower cognitive function, specifically memory and verbal function. This association needs to be confirmed prospectively and further research is needed to elucidate its mechanism.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".