National Heart, Lung, and Blood Institute's and Boston University's Framingham Study, Framingham, Mass, USA.
Circulation. 2010 Jan 19;121(2):200-7. doi: 10.1161/CIRCULATIONAHA.109.882241. Epub 2010 Jan 4.
Biomarkers of multiple pathophysiological pathways have been related to incident atrial fibrillation (AF), but their predictive ability remains controversial.
In 3120 Framingham cohort participants (mean age 58.4+/-9.7 years, 54% women), we related 10 biomarkers that represented inflammation (C-reactive protein and fibrinogen), neurohormonal activation (B-type natriuretic peptide [BNP] and N-terminal proatrial natriuretic peptide), oxidative stress (homocysteine), the renin-angiotensin-aldosterone system (renin and aldosterone), thrombosis and endothelial function (D-dimer and plasminogen activator inhibitor type 1), and microvascular damage (urinary albumin excretion; n=2673) to incident AF (n=209, 40% women) over a median follow-up of 9.7 years (range 0.05 to 12.8 years). In multivariable-adjusted analyses, the biomarker panel was associated with incident AF (P<0.0001). In stepwise-selection models (P<0.01 for entry and retention), log-transformed BNP (hazard ratio per SD 1.62, 95% confidence interval 1.41 to 1.85, P<0.0001) and C-reactive protein (hazard ratio 1.25, 95% confidence interval 1.07 to 1.45, P=0.004) were chosen. The addition of BNP to variables recently combined in a risk score for AF increased the C-statistic from 0.78 (95% confidence interval 0.75 to 0.81) to 0.80 (95% confidence interval 0.78 to 0.83) and showed an integrated discrimination improvement of 0.03 (95% confidence interval 0.02 to 0.04, P<0.0001), with 34.9% relative improvement in reclassification analysis. The combined analysis of BNP and C-reactive protein did not appreciably improve risk prediction over the model that incorporated BNP in addition to the risk factors.
BNP is a predictor of incident AF and improves risk stratification based on well-established clinical risk factors. Whether knowledge of BNP concentrations may be used to target individuals at risk of AF for more intensive monitoring or primary prevention requires further investigation.
多种病理生理途径的生物标志物与房颤(AF)的发生有关,但它们的预测能力仍存在争议。
在 3120 名弗雷明汉队列参与者(平均年龄 58.4±9.7 岁,54%为女性)中,我们研究了 10 种生物标志物,这些标志物代表炎症(C 反应蛋白和纤维蛋白原)、神经激素激活(B 型利钠肽[BNP]和氨基末端脑钠肽前体)、氧化应激(同型半胱氨酸)、肾素-血管紧张素-醛固酮系统(肾素和醛固酮)、血栓形成和内皮功能(D-二聚体和纤溶酶原激活物抑制剂 1)以及微血管损伤(尿白蛋白排泄;n=2673)与 9.7 年(0.05 至 12.8 年)的房颤(n=209,40%为女性)事件之间的关系。在多变量调整分析中,生物标志物谱与房颤事件相关(P<0.0001)。在逐步选择模型中(入选和保留的 P<0.01),BNP 的自然对数值(每标准差的危险比 1.62,95%置信区间 1.41 至 1.85,P<0.0001)和 C 反应蛋白(危险比 1.25,95%置信区间 1.07 至 1.45,P=0.004)被选择。BNP 的加入增加了房颤风险评分中最近结合的变量的 C 统计量,从 0.78(95%置信区间 0.75 至 0.81)到 0.80(95%置信区间 0.78 至 0.83),并显示出 0.03 的综合判别改善(95%置信区间 0.02 至 0.04,P<0.0001),在重新分类分析中相对改善了 34.9%。BNP 和 C 反应蛋白的联合分析并未明显改善基于既定临床危险因素的风险预测。关于 BNP 浓度的知识是否可用于针对房颤风险个体进行更强化的监测或一级预防,还需要进一步研究。