Silent brain infarcts impact on cognitive function in atrial fibrillation
Bibliographic record
Abstract
AIMS: We aimed to investigate the association of clinically overt and silent brain lesions with cognitive function in atrial fibrillation (AF) patients. METHODS AND RESULTS: We enrolled 1227 AF patients in a prospective, multicentre cohort study (Swiss-AF). Patients underwent standardized brain magnetic resonance imaging (MRI) at baseline and after 2 years. We quantified new small non-cortical infarcts (SNCIs) and large non-cortical or cortical infarcts (LNCCIs), white matter lesions (WML), and microbleeds (Mb). Clinically, silent infarcts were defined as new SNCI/LNCCI on follow-up MRI in patients without a clinical stroke or transient ischaemic attack (TIA) during follow-up. Cognition was assessed using validated tests. The mean age was 71 years, 26.1% were females, and 89.9% were anticoagulated. Twenty-eight patients (2.3%) experienced a stroke/TIA during 2 years of follow-up. Of the 68 (5.5%) patients with ≥1 SNCI/LNCCI, 60 (88.2%) were anticoagulated at baseline and 58 (85.3%) had a silent infarct. Patients with brain infarcts had a larger decline in cognition [median (interquartile range)] changes in Cognitive Construct score [-0.12 (-0.22; -0.07)] than patients without new brain infarcts [0.07 (-0.09; 0.25)]. New WML or Mb were not associated with cognitive decline. CONCLUSION: In a contemporary cohort of AF patients, 5.5% had a new brain infarct on MRI after 2 years. The majority of these infarcts was clinically silent and occurred in anticoagulated patients. Clinically, overt and silent brain infarcts had a similar impact on cognitive decline. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02105844, https://clinicaltrials.gov/ct2/show/NCT02105844.
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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) | 0.002 | 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 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".