Association of biomarkers of inflammation with hospitalization for heart failure and death in patients with atrial fibrillation
Bibliographic record
Abstract
Abstract Background Hospitalization for heart failure and death are among the most common adverse clinical outcomes in patients with atrial fibrillation (AF). The underlying mechanisms are poorly understood. Purpose We hypothesised that inflammation, quantified by plasma levels of C-reactive protein (CRP) and interleukin 6 (IL-6), is independently associated with hospitalization for heart failure and death in a large, contemporary cohort of AF patients. Methods Patients with established AF and 65 years of age or older were enrolled in two large, prospective, multicentre cohort studies in Switzerland. Plasma levels of high-sensitivity (hs) CRP and IL-6 were measured from frozen EDTA plasma samples obtained at baseline. Using these two biomarkers, we calculated an inflammation score ranging from 0 to 4 (1 point for each biomarker between the 50th and 75th percentile, 2 points for each biomarker above the 75th percentile). We constructed multivariable Cox proportional hazards models to quantify the associations of hs-CRP, IL-6 and the inflammation score with time to first hospitalization for heart failure and time to all-cause mortality, respectively. Results A total of 3,784 patients with AF (median age 72 years, 28% women, 24% with a prior history of heart failure and 84% anticoagulation use at baseline) were followed for a median (interquartile range [IQR]) of 4.0 (2.9–5.1) years. The median (IQR) plasma levels of hs-CRP and IL-6 at baseline were 1.64 (0.81–3.69) mg/L and 3.42 (2.14–5.60) pg/mL, respectively. The incidence rates of hospitalization for heart failure and death were 3.04 and 2.80 per 100 person-years, respectively. After multivariable adjustment, both biomarkers were significantly associated with the risk of hospitalization for heart failure (per increase in 1 standard deviation [SD], adjusted hazard ratio [aHR] 1.22, 95% confidence interval [CI] 1.11–1.34 for log-transformed hs-CRP, and aHR 1.48, 95% CI 1.35–1.62 for log-transformed IL-6) and death (per increase in 1 SD, aHR 1.40, 95% CI 1.27–1.54 for log-transformed hs-CRP, and aHR 1.67, 95% CI 1.53–1.81 for log-transformed IL-6). Incidence rates of hospitalization for heart failure increased from 1.34 to 7.31 per 100 person-years across categories of the inflammation score (Figure 1). A strong relationship persisted after multivariable adjustment. Similar findings were observed for all-cause mortality. Conclusions Inflammation is a strong predictor of hospitalization for heart failure and death in patients with AF. Targeting inflammation may be a promising treatment strategy to improve outcomes in these patients at high risk for adverse outcomes. Figure 1 Funding Acknowledgement Type of funding source: Foundation. Main funding source(s): Swiss National Science Foundation
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".