Atrial fibrillation as a risk factor for cognitive impairment: a semi-systematic review
Bibliographic record
Abstract
It is unclear if atrial fibrillation (AF) is an independent risk factor for cognitive impairment. This review evaluates the available evidence and provides an overview of the association between AF and cognitive function. Electronic database searches, January 1990 to December 2012, identified 271 studies comparing the incidence of cognitive impairment and/or dementia in patients with/without AF. Cognitive function was diagnosed by a physician using the mini-mental state examination (MMSE) or other established diagnostic criteria. Studies with <20 participants and without direct comparison to controls in sinus rhythm were excluded. There were no restrictions on the basis of age, language or study design. Full texts of 11 studies were obtained. Eight studies (three cross-sectional, two case-control and three prospective cohorts) reported an association between cognitive decline and AF. Among cross-sectional studies, patients with AF had a 1.7 (95% CI 1.2-2.5) to 3.3 (95% CI 1.6-6.5) greater risk of cognitive impairment, and a 2.3-fold (95% CI 1.4-3.7) increased risk of dementia, compared to patients in sinus rhythm. There was marked heterogeneity in the design, size and quality of studies and reporting of the data which precluded formal meta-analysis. Eight studies reported an association between AF and cognitive impairment and/or dementia, but the magnitude of risk varied. Further large-scale prospective studies are needed to establish whether AF is a risk factor for cognitive decline, utilizing objective measures of cognitive function and neuropsychological testing, and to investigate the potential benefit of anticoagulation on reducing cognitive impairment and development of dementia.
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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 | 0.007 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.011 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".