Plasma angiopoietin-2 and its association with heart failure in patients with atrial fibrillation
Bibliographic record
Abstract
AIMS: Several biomarkers are associated with clinical outcomes in patients with atrial fibrillation (AF), but a causal relationship has not been established. This study aimed to evaluate angiopoietin-2, a novel candidate biomarker of endothelial inflammation and vascular remodelling, in patients with AF. METHODS AND RESULTS: Angiopoietin-2 was measured in plasma obtained from patients with AF treated with aspirin monotherapy (exploration cohort, n = 2987) or with oral anticoagulation (validation cohort, n = 13 079). Regression models were built to assess the associations between angiopoietin-2, clinical characteristics, and outcomes. In both cohorts, plasma angiopoietin-2 was independently associated with AF on the baseline electrocardiogram and persistent/permanent AF, age, history of heart failure, female sex, tobacco use/smoking, body mass index, renal dysfunction, diabetes, and N-terminal pro-B-type natriuretic peptide (NT-proBNP). Angiopoietin-2 was independently associated with subsequent hospitalization for heart failure after adjusting for age, creatinine, and clinical characteristics in the exploration cohort [c-index 0.79, 95% confidence interval (CI) 0.75-0.82; third vs. first quartile, hazard ratio (HR) 1.74, 95% CI 1.26-2.41] and in the validation cohort (c-index 0.76, 95% CI 0.74-0.78; HR 1.58, 95% CI 1.37-1.82). In both cohorts, the association persisted when also adjusting for NT-proBNP (P ≤ 0.001). In full multivariable models also adjusted for NT-proBNP, angiopoietin-2 did not show statistically significant associations with ischaemic stroke, cardiovascular and all-cause death, or major bleeding that were consistent across the two cohorts. CONCLUSIONS: In patients with AF, plasma levels of angiopoietin-2 were independently associated with subsequent hospitalization for heart failure and provided incremental prognostic value to clinical risk factors and NT-proBNP.
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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 | 0.000 | 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".