Association of the CHA2D(S2)-VASc Score and Its Components With Overt and Silent Ischemic Brain Lesions in Patients With Atrial Fibrillation
Bibliographic record
Abstract
Background: Silent and overt ischemic brain lesions are common and associated with adverse outcome. Whether the CHA2DS2-VASc score and its components predict magnetic resonance imaging (MRI)-detected ischemic silent and overt brain lesions in patients with atrial fibrillation (AF) is unclear. Methods: In this cross-sectional analysis, patients with AF were enrolled in a multicenter cohort study in Switzerland. Outcomes were clinically overt, silent [in the absence of a history of stroke/transient ischemic attack (TIA)] and any MRI-detected ischemic brain lesions. Logistic regression analyses were performed to assess the relationship of the CHA2DS2-VASc score and its components with ischemic brain lesions. An adapted CHA2D-VASc score (excluding history of stroke/TIA) for the analyses of clinically overt and silent ischemic brain lesions was used. Results: Overall, 1,741 patients were included in the analysis (age 73 ± 8 years, 27.4% female). At least one ischemic brain lesion was observed in 36.8% (clinically overt: 10.5%; silent: 22.9%; transient ischemic attack: 3.4%). The CHA2D-VASc score was strongly associated with clinically overt and silent ischemic brain lesions {odds ratio (OR) [95% confidence interval (CI)] 1.32 (1.17–1.49), p < 0.001 and 1.20 (1.10–1.30), p < 0.001, respectively}. Age 65–74 years (OR 2.58; 95%CI 1.29–5.90; p = 0.013), age ≥75 years (4.13; 2.07–9.43; p < 0.001), hypertension (1.90; 1.28–2.88; p = 0.002) and diabetes (1.48; 1.00–2.18; p = 0.047) were associated with clinically overt brain lesions, whereas age 65–74 years (1.95; 1.26–3.10; p = 0.004), age ≥75 years (3.06; 1.98–4.89; p < 0.001) and vascular disease (1.39; 1.07–1.79; p = 0.012) were associated with silent ischemic brain lesions. Conclusions: A higher CHA2D-VASc score was associated with a higher risk of both overt and silent ischemic brain lesions. Clinical Trial Registration: www.ClinicalTrials.gov , identifier: NCT02105844.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".