Duke Clinical Research Institute, Duke University, Durham, NC (A.S., S.M.A.-K., R.D.L., J.H.A., C.B.G.).
Department of Medical Sciences and Cardiology, Uppsala University, Sweden (Z.H., U.A., C.H., A.S., L.W.).
Circulation. 2018 Oct 16;138(16):1666-1676. doi: 10.1161/CIRCULATIONAHA.118.034125.
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.
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.
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.
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.
URL: https://www.clinicaltrials.gov . Unique identifier: NCT00412984.
房颤与死亡风险增加相关。在接受抗凝治疗的房颤患者中，高敏肌钙蛋白 T、生长分化因子-15、NT-proBNP（氨基末端 B 型利钠肽前体）和白细胞介素 6 水平可预测心血管事件和全因心血管死亡。这些生物标志物对特定原因死亡的预后价值尚不清楚。
ARISTOTLE 试验（房颤患者中阿哌沙班预防卒中研究）将 18201 例房颤患者随机分为阿哌沙班组和华法林组。在 14798 例患者（中位随访时间 1.9 年）中随机测量了生物标志物。Cox 模型用于确定与每种特定死因独立相关的临床变量和生物标志物。
共有 1272 例患者死亡：652 例（51%）心血管死亡，32 例（3%）出血死亡，588 例（46%）非心血管/非出血死亡。心血管死亡中，255 例（39%）为心源性猝死，168 例（26%）为心力衰竭死亡，106 例（16%）为卒中/系统性栓塞死亡。生物标志物是预测特定病因死亡的最强指标：肌钙蛋白 T 加倍与猝死的相关性最强（危险比 [HR]，1.48；P<0.001），NT-proBNP 与心力衰竭死亡相关（HR，1.62；P<0.001），生长分化因子-15 与出血死亡相关（HR，1.72；P=0.028）。既往卒中/系统性栓塞（HR，2.58；P>0.001）后紧随肌钙蛋白 T（HR，1.45；P<0.0029）是预测卒中/系统性栓塞死亡的最强指标。将所有生物标志物与临床变量相结合，可提高对每种特定病因死亡的预测能力。
生物标志物是预测特定病因死亡的最强指标之一，可能有助于区分患者不同死因的风险。这些数据表明，生物标志物可能有助于识别接受抗凝治疗的房颤患者不同死因的风险。
