首页> 外文期刊>The American heart journal >Electrocardiographic abnormalities and coronary artery calcium for coronary heart disease prediction and reclassification: The Multi-Ethnic Study of Atherosclerosis (MESA)
【24h】

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

机译:心电图异常和冠状动脉钙离子对冠心病的预测和重新分类:动脉粥样硬化(MESA)的多民族研究

获取原文
获取原文并翻译 | 示例
           

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 minoro 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:背景心电图(ECG)异常和冠状动脉钙(CAC)可以识别亚临床冠心病(CHD)的不同方面。我们试图确定ECG异常是否能与CAC措施一起改善所有冠心病和致命冠心病事件的风险预测。方法我们纳入了6406名来自MESA的年龄在45至84岁之间的男性和女性,他们在入组时(2000-2002年)没有心血管疾病。我们根据ST-T和Q波异常的存在对参与者进行了分层:使用明尼苏达州代码分类的任何专业,任何次要/没有专业,以及没有专业/未成年人。 CAC得分定义为以下层次之一:0、1至100、101至300,大于300。我们使用MESA特定的传统风险因子(RF)系数创建了风险预测模型,并计算了分类净重分类改进(NRI) ),并导致致命的冠心病。结果在10年的中位随访中,我们观察到将ECG异常添加到所有CHD的风险预测模型中,得出的总NRI为0.05(P = .04)。仅对于致命的冠心病,增加的ECG异常导致分类NRI为0.09(P = .02)。将ECG异常添加到包含RFs和CAC的模型中后,所有CHD事件的分类NRI均为0.02(P = .11)。我们还观察到通过CAC存在分层时,心电图异常与冠心病之间的关联存在差异。结论将心电图异常添加到RFs中可改善CHD的风险预测,但不能将其添加到CAC中则可提高风险预测。心电图异常可改善致命性冠心病的风险预测。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号