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Electrocardiographic abnormalities and coronary artery calcium for coronary heart disease prediction and reclassification: The Multi-Ethnic Study of Atherosclerosis (MESA)

机译:冠心病预测和重新分类的心电图异常和冠状动脉钙:动脉粥样硬化的多民族研究(MESA)

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摘要

Background Electrocardiographic (ECG) abnormalities and coronary artery calcium (CAC) identify different aspects of subclinical coronary heart disease (CHD). We sought to determine whether ECG abnormalities improve risk prediction for all CHD and fatal CHD events jointly with CAC measures. Methods We included 6,406 men and women from the MESA aged 45 to 84 years who were free of cardiovascular disease at the time of enrollment (2000-2002). We stratified participants by presence of ST-T and Q wave abnormalities: any major, any minor/no major, and no major/minor using the Minnesota Code classifications. CAC score was defined into one of the following strata: 0, 1 to 100, 101 to 300, greater than 300. We created risk prediction models using MESA-specific coefficients for traditional risk factors (RFs) and calculated categorical net reclassification improvement (NRI) for all and fatal CHD. Results Over a median follow-up of 10 years, we observed that the addition of ECG abnormalities to a risk prediction model for all CHD resulted in a categorical NRI of 0.05 (P =.04). For fatal CHD alone, the addition of ECG abnormalities resulted in categorical NRI of 0.09 (P =.02). Addition of ECG abnormalities to a model containing RFs and CAC resulted in categorical NRI of 0.02 (P =.11) for all CHD events. We also observed differences in the association between ECG abnormalities and CHD when stratifying by CAC presence. Conclusion Electrocardiographic abnormalities improved risk prediction for CHD when added to RFs but not when added to CAC. Electrocardiographic abnormalities particularly improved risk prediction for fatal CHD.
机译:背景技术心电图(ECG)异常和冠状动脉钙(CAC)识别亚临床冠心病(CHD)的不同方面。我们试图确定ECG异常是否有助于与CAC措施共同提高所有CHD和致命核武器阵容的风险预测。方法采用45至84岁的MESA中包括6,406名男女,在入学时(2000-2002)没有心血管疾病。我们通过ST-T和Q波异常的存在分层:任何主要,任何次要/无专业,也没有MINNESOTA代码分类的主要/未成年人。 CAC评分被定义为以下位置:0,1至100,101至300,大于300.我们使用MESA特定系数为传统风险因素(RFS)和计算的分类净重新分类改进(NRI)创建了风险预测模型(NRI )对于所有和致命的CHD。结果在10年的中位随访中,我们观察到向所有CHD的风险预测模型添加ECG异常导致了0.05的分类NRI(p = .04)。对于单独的致命核,ECG异常的添加导致0.09的分类NRI(p = .02)。向含有RFS和CAC的模型添加ECG异常导致所有CHD事件的分类NRI为0.02(p = .11)。我们还观察到CAC存在分层时ECG异常和CHD之间的关联之间的差异。结论当添加到RF时,心电图异常改善了CHD的CHD风险预测,但在添加到CAC时,不提高CAC。心电图异常特别提高了致命核的风险预测。

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  • 来源
    《The American heart journal》 |2014年第3期|共7页
  • 作者单位

    Department of Medicine Johns Hopkins University School of Medicine Baltimore MD United States;

    Department of Preventive Medicine Feinberg School of Medicine Northwestern University 680 N Lake;

    Division of Public Health Sciences Wake Forest School of Medicine Winston Salem NC United States;

    Division of Public Health Sciences Wake Forest School of Medicine Winston Salem NC United States;

    Columbia University Mailman School of Public Health New York NY United States;

    Department of Medicine Johns Hopkins University School of Medicine Baltimore MD United States;

    Department of Preventive Medicine Feinberg School of Medicine Northwestern University 680 N Lake;

    Department of Preventive Medicine Feinberg School of Medicine Northwestern University 680 N Lake;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 心脏、血管(循环系)疾病;
  • 关键词

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