Svennberg Emma, Lindahl Bertil, Berglund Lars, Eggers Kai M, Venge Per, Zethelius Björn, Rosenqvist Mårten, Lind Lars, Hijazi Ziad
Karolinska Institutet, Dept. of Clinical Sciences, Cardiology Unit, Danderyd's University Hospital, Stockholm, Sweden.
Department of Medical Sciences, Cardiology, Uppsala University, Uppsala, Sweden; Uppsala Clinical Research Center, Uppsala University, Uppsala, Sweden.
Int J Cardiol. 2016 Nov 15;223:74-81. doi: 10.1016/j.ijcard.2016.08.001. Epub 2016 Aug 4.
Biomarkers may be of value to identify individuals at risk of developing atrial fibrillation (AF). Using a multimarker approach, this study investigated if the biomarkers; NT-proBNP, high-sensitivity cardiac troponin (hs-cTn), growth differentiation factor-15 (GDF-15), cystatin C and high-sensitivity C-reactive protein (CRP) are independent predictors for incident AF.
Blood samples were collected from 883 individuals in the Uppsala Longitudinal Study of Adult Men (ULSAM) and 978 individuals in the Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS) study. Participants were followed for 10-13years with n=113 incident AF cases in ULSAM and n=148 in PIVUS. The associations between biomarkers and incident AF were analysed in Cox proportional hazards regression models.
The hazard ratio (HR) for incident AF was significant for all five biomarkers in unadjusted analyses in both cohorts. Only NT-proBNP remained significant when adjusting for cardiovascular risk factors and the other biomarkers (HR (1SD) 2.05 (1.62-2.59) (ULSAM) and 1.56 (1.30-1.86) (PIVUS), both p<0.001). The C-index improved from 0.64 to 0.69 in ULSAM and from 0.62 to 0.68 in PIVUS, by adding NT-proBNP to cardiovascular risk factors (both p<0.001). The C-index of the CHARGE-AF risk score increased from 0.62 to 0.68 (ULSAM) and 0.60 to 0.66 (PIVUS) by addition of NT-proBNP (p<0.001).
Using a multimarker approach NT-proBNP was the strongest predictor of incident AF in two cohorts, and improved risk prediction when added to traditional risk factors. NT-proBNP significantly improved the predictive ability of the novel CHARGE-AF risk score, although the predictive value remained modest.
生物标志物可能有助于识别有发生心房颤动(AF)风险的个体。本研究采用多标志物方法,调查了生物标志物N末端脑钠肽前体(NT-proBNP)、高敏心肌肌钙蛋白(hs-cTn)、生长分化因子15(GDF-15)、胱抑素C和高敏C反应蛋白(CRP)是否为AF发生的独立预测因素。
从乌普萨拉成年男性纵向研究(ULSAM)中的883名个体和乌普萨拉老年人血管前瞻性研究(PIVUS)中的978名个体采集血样。对参与者进行了10至13年的随访,ULSAM中有113例AF发病病例,PIVUS中有148例。在Cox比例风险回归模型中分析生物标志物与AF发病之间的关联。
在两个队列的未调整分析中,所有五种生物标志物的AF发病风险比(HR)均具有统计学意义。在调整心血管危险因素和其他生物标志物后,只有NT-proBNP仍具有统计学意义(HR(1SD)2.05(1.62 - 2.59)(ULSAM)和1.56(1.30 - 1.86)(PIVUS),均p<0.001)。在ULSAM中,通过将NT-proBNP添加到心血管危险因素中,C指数从0.64提高到0.69,在PIVUS中从0.62提高到0.68(均p<0.001)。通过添加NT-proBNP,CHARGE-AF风险评分的C指数在ULSAM中从0.62提高到0.68,在PIVUS中从0.60提高到0.66(p<0.001)。
采用多标志物方法,NT-proBNP是两个队列中AF发病的最强预测因素,添加到传统危险因素中可改善风险预测。NT-proBNP显著提高了新型CHARGE-AF风险评分的预测能力,尽管预测价值仍然有限。