Use of Biomarkers to Predict Specific Causes of Death in Patients With Atrial Fibrillation
Bibliographic record
Abstract
BACKGROUND: Atrial fibrillation is associated with an increased risk of death. High-sensitivity troponin T, growth differentiation factor-15, NT-proBNP (N-terminal pro-B-type natriuretic peptide), and interleukin-6 levels are predictive of cardiovascular events and total cardiovascular death in anticoagulated patients with atrial fibrillation. The prognostic utility of these biomarkers for cause-specific death is unknown. METHODS: The ARISTOTLE trial (Apixaban for the Prevention of Stroke in Subjects With Atrial Fibrillation) randomized 18 201 patients with atrial fibrillation to apixaban or warfarin. Biomarkers were measured at randomization in 14 798 patients (1.9 years median follow-up). Cox models were used to identify clinical variables and biomarkers independently associated with each specific cause of death. RESULTS: In total, 1272 patients died: 652 (51%) cardiovascular, 32 (3%) bleeding, and 588 (46%) noncardiovascular/nonbleeding deaths. Among cardiovascular deaths, 255 (39%) were sudden cardiac deaths, 168 (26%) heart failure deaths, and 106 (16%) stroke/systemic embolism deaths. Biomarkers were the strongest predictors of cause-specific death: a doubling of troponin T was most strongly associated with sudden death (hazard ratio [HR], 1.48; P<0.001), NT-proBNP with heart failure death (HR, 1.62; P<0.001), and growth differentiation factor-15 with bleeding death (HR, 1.72; P=0.028). Prior stroke/systemic embolism (HR, 2.58; P>0.001) followed by troponin T (HR, 1.45; P<0.0029) were the most predictive for stroke/ systemic embolism death. Adding all biomarkers to clinical variables improved discrimination for each cause-specific death. CONCLUSIONS: Biomarkers were some of the strongest predictors of cause-specific death and may improve the ability to discriminate among patients' risks for different causes of death. These data suggest a potential role of biomarkers for the identification of patients at risk for different causes of death in patients anticoagulated for atrial fibrillation. CLINICAL TRIAL REGISTRATION: URL: https://www.clinicaltrials.gov . Unique identifier: NCT00412984.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".