Using multimarker screening to identify biomarkers associated with cardiovascular death in patients with atrial fibrillation
Bibliographic record
Abstract
AIMS: Atrial fibrillation (AF) is associated with higher mortality. Biomarkers may improve the understanding of key pathophysiologic processes in AF that lead to death. Using a new multiplex analytic technique, we explored the association between 268 biomarkers and cardiovascular (CV) death in anticoagulated patients with AF. METHODS AND RESULTS: A case-cohort design with 1.8- to 1.9-year follow-up. The identification cohort included 517 cases and 4057 randomly selected patients from ARISTOTLE. The validation cohort included 277 cases and 1042 randomly selected controls from RE-LY. Plasma collected at randomization was analysed with conventional immunoassays and the OLINK proximity extension assay panels: CVDII, CVDIII, and Inflammation. Association between biomarkers and CV death was evaluated using Random Survival Forest, Boruta, and adjusted Cox-regression analyses. The biomarkers most strongly and consistently associated with CV death were as follows (hazard ratio for inter-quartile comparison [95% CI]): N-terminal pro-B-type natriuretic peptide [NT-proBNP; 1.63 (1.37-1.93)], cardiac troponin T [cTnT-hs; 1.60 (1.35-1.88)], interleukin-6 [IL-6; 1.29 (1.13-1.47)], growth differentiation factor-15 [GDF-15; 1.30 (1.10-1.53)], fibroblast growth factor 23 [FGF-23; 1.21 (1.10-1.33)], urokinase receptor [uPAR; 1.38 (1.16-1.64)], trefoil factor 3 [TFF3; 1.27 (1.10-1.46)], tumour necrosis factor receptor 1 [TNFR1; 1.21 (1.01-1.45)], TNF-related apoptosis-inducing ligand receptor 2 [TRAILR2; 1.18 (1.04-1.34)], and cathepsin L1 [CTSL1; 1.22 (1.07-1.39)]. CONCLUSION: In this comprehensive screening of 268 biomarkers in anticoagulated patients with AF, the underlying mechanisms most strongly associated with CV death were cardiorenal dysfunction (NT-proBNP, cTnT-hs, CTSL1, TFF3), oxidative stress (GDF-15), inflammation (IL-6, GDF-15), calcium balance, vascular and renal dysfunction (FGF-23), fibrinolysis (suPAR), and apoptosis (TNFR1, TRAILR2). These findings provide novel insights into pathophysiologic aspects associated with CV death in AF. CLINICALTRIALS.GOV IDENTIFIER: NCT00412984 and NCT00262600.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".