103Atrial Fibrillation and Cognition at Four Year Follow Up – Data from The Irish Longitudinal Study on Ageing (TILDA)
Bibliographic record
Abstract
Background: Atrial fibrillation (AF) is the most common sustained arrhythmia, and is associated with an increased risk of stroke, heart failure and increased mortality. Emerging evidence suggests AF may be associated with an increased risk of cognitive impairment, however results are conflicting. The aim of this study is to assess whether AF is associated with a decline in global cognition at four year follow-up. Methods: Data from waves 1 and 3 of the Irish Longitudinal Study on Ageing were used. At wave 1, participants who attended the health centre underwent ECG which were screened for AF by clinicians. Global cognition was assessed at the health centre, using the Montreal Cognitive Assessment (MOCA), and this was repeated at wave 3 (4 year follow-up period). Information on covariates was obtained via a computer aided personal interview and during the health assessment. Mixed effects poisson regression was performed to assess whether there was an increased rate of errors in MOCA at 4 year follow-up in participants with AF. Results: Participants with a baseline diagnosis of dementia, stroke or Parkinson’s disease, or who had inadequate ECG or MOCA data at wave 1, were excluded. Of those included, 3651 had a follow-up MOCA at wave 3, of whom 74 (2.05%) had AF on ECG. Results of mixed effects poisson regression found an increased rate of errors on MOCA in participants with AF at follow-up (IRR 1.16; 95% CI 1.01, 1.35; p-value 0.037), however this was no longer significant on controlling for age, sex, education, medication use, smoking status, alcohol, blood pressure, cardiovascular comorbidities, depressive symptoms and frailty (IRR 1.09; 95% CI 0.88, 1.35; p-value 0.447). Conclusion: AF was not associated with an increase rate of errors on MOCA at 4 year follow-up, adjusting for confounders, in a community dwelling population over the age of 50 in Ireland.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".