Incident Atrial Fibrillation, Dementia and the Role of Anticoagulation: A Population-Based Cohort Study
Bibliographic record
Abstract
INTRODUCTION: Atrial fibrillation (AF) is associated with dementia. Anticoagulation may modify this relationship, but it is unclear if this is due to stroke reduction alone. METHODS: Age- and sex-matched individuals from the U.K. Clinical Practice Research Datalink (2008-2016) with and without an incident diagnosis of AF were followed for a new dementia diagnosis. We estimated adjusted hazard ratios (aHRs) for incident dementia diagnosis in the AF cohort, overall and stratified by anticoagulation status, using the matched non-AF cohorts as reference. We performed a sensitivity analysis excluding individuals with stroke/transient ischaemic attack (TIA) before the observation period. RESULTS: Over 193,082 person-years (mean follow-up 25.7 ± 0.1 months), 347/15,276 AF (2.3%) and 1,085/76,096 non-AF (1.4%) were newly diagnosed with dementia (aHR, 1.31, 95% confidence interval, 1.15-1.49). The AF group had more co-morbidity and higher rates of dementia, both with and without anticoagulation, than non-AF. When those with history of stroke/ TIA before the observation period were excluded and those with incident stroke/TIA during the observation period were censored, AF individuals not on anticoagulation had significantly higher rates of dementia compared with non-AF, aHR 1.30 (1.06-1.58). CONCLUSION: Our findings support the hypothesis that AF is a distinct risk factor for dementia, independent of stroke/TIA and other vascular risk factors. In those without stroke/TIA, risk of dementia is increased only in those who are not on anticoagulation, suggesting anticoagulation is protective presumably through reduction of sub-clinical embolic events. Further prospective research is needed to better ascertain the role of anticoagulation amongst targeted therapeutic strategies to reduce cognitive decline in AF.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".