Serial measurement of interleukin‐6 and risk of mortality in anticoagulated patients with atrial fibrillation: Insights from ARISTOTLE and RE‐LY trials
Bibliographic record
Abstract
BACKGROUND: The inflammatory biomarker interleukin-6 (IL-6) is associated with mortality in atrial fibrillation (AF). OBJECTIVE: To investigate if repeated IL-6 measurements improve the prognostication for stroke or systemic embolism, major bleeding, and mortality in anticoagulated patients with AF. METHODS: IL-6 levels by ELISA were measured at study entry and at 2 months in 4830 patients in the Apixaban for Reduction in Stroke and Other Thromboembolic Events in Atrial Fibrillation (ARISTOTLE) trial with 1.8 years median follow-up. In the Randomized Evaluation of Long-Term Anticoagulation Therapy (RE-LY) trial, IL-6 was measured at study entry, 3, 6, and 12 months in 2559 patients with 2.0 years median follow-up. Associations between a second IL-6 measurement and outcomes, adjusted for baseline IL-6, clinical variables, and other cardiovascular biomarkers, were analyzed by Cox regression. RESULTS: Median IL-6 levels were 2.0 ng/L (interquartile range [IQR] 1.30-3.20) and 2.10 ng/L (IQR 1.40-3.40) at the two time-points in ARISTOTLE, and, in RE-LY, 2.5 ng/L (IQR 1.6-4.3), 2.5 ng/L (IQR 1.6-4.2), 2.4 ng/L (IQR 1.6, 3.9), and 2.4 ng/L (IQR 1.5, 3.9), respectively. IL-6 was associated with mortality; hazard ratios per 50% higher IL-6 at 2 or 3 months, respectively, were 1.32 (95% confidence interval, 1.23-1.41; P < .0001) in ARISTOTLE, and 1.11 (1.01-1.22, P = .0290) in RE-LY; with improved C index from 0.74 to 0.76 in ARISTOTLE, but not in the smaller RE-LY cohort. There were no consistent associations with second IL-6 and stroke or systemic embolism, or major bleeding. CONCLUSIONS: Persistent systemic inflammatory activity, assessed by repeated IL-6 measurements, is associated with mortality independent of established clinical risk factors and other strong cardiovascular biomarkers in anticoagulated patients with AF.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".