Coronary artery calcium score and risk classification for coronary heart disease prediction.
Coronary artery calcium score and risk classification for coronary heart disease prediction.
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DOI：
10.1001/jama.2010.461
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发表时间：
2010-04-28
影响因子：
120.7
通讯作者：
Greenland, Philip
中科院分区：
文献类型：
--
作者：
Polonsky, Tamar S.;McClelland, Robyn L.;Jorgensen, Neal W.;Bild, Diane E.;Burke, Gregory L.;Guerci, Alan D.;Greenland, Philip
冠状动脉钙化评分（CACS）已被证明可以预测未来的冠心病（CHD）事件。然而，将CACS添加到传统的CHD危险因素中在多大程度上改善了风险分类尚不清楚。确定将CACS添加到基于传统风险因素的预测模型中是否改善了风险分类。CACS是通过计算机断层扫描对来自多种族动脉粥样硬化研究（梅萨）的6,814名参与者进行测量的，MESA是一项基于人群的队列研究，没有已知的心血管疾病。招募时间为2000年7月至2002年9月;后续行动延长至2008年5月。糖尿病患者被排除在主要分析之外。采用考克斯比例风险模型将冠心病事件的5年风险估计值分为0-<3%、3-<10%和≥10%。模型1使用年龄、性别、烟草使用、收缩压、抗高血压药物使用、总胆固醇和高密度脂蛋白胆固醇以及种族/民族。模型2使用这些风险因素加上CACS。我们计算了净重新分类改进（NRI），并比较了模型2与模型1的风险分布。在5.8年的中位随访期间，发生了209起CHD事件，其中122起为心肌梗死、CHD死亡或心脏骤停复苏。与模型1相比，模型2导致风险预测的显著改善（NRI=0.25，95%置信区间0.16-0.34，P<0.001）。使用模型1，69%的队列被归类为最高或最低风险类别，而模型2为77%。使用模型2，另外23%经历过事件的人被重新分类为高风险，另外13%没有事件的人被重新分类为低风险。在梅萨队列中，将CACS添加到基于传统风险因素的预测模型中显着改善了风险分类，并将更多的人置于最极端的风险类别中。
Coronary artery calcium score (CACS) has been shown to predict future coronary heart disease (CHD) events. However, the extent to which adding CACS to traditional CHD risk factors improves classification of risk is unclear. To determine whether adding CACS to a prediction model based on traditional risk factors improves classification of risk. CACS was measured by computed tomography on 6,814 participants from the Multi-Ethnic Study of Atherosclerosis (MESA), a population-based cohort without known cardiovascular disease. Recruitment spanned July 2000 to September 2002; follow-up extended through May 2008. Participants with diabetes were excluded for the primary analysis. Five-year risk estimates for incident CHD were categorized as 0-<3%, 3-<10%, and ≥10% using Cox proportional hazards models. Model 1 used age, gender, tobacco use, systolic blood pressure, antihypertensive medication use, total and high-density lipoprotein cholesterol, and race/ethnicity. Model 2 used these risk factors plus CACS. We calculated the net reclassification improvement (NRI) and compared the distribution of risk using Model 2 versus Model 1. Incident CHD events Over 5.8 years median follow-up, 209 CHD events occurred, of which 122 were myocardial infarction, death from CHD, or resuscitated cardiac arrest. Model 2 resulted in significant improvements in risk prediction compared to Model 1 (NRI=0.25, 95% confidence interval 0.16-0.34, P<0.001). With Model 1, 69% of the cohort was classified in the highest or lowest risk categories, compared to 77% with Model 2. An additional 23% of those who experienced events were reclassified to high risk, and an additional 13% without events were reclassified to low risk using Model 2. In the MESA cohort, addition of CACS to a prediction model based on traditional risk factors significantly improved the classification of risk and placed more individuals in the most extreme risk categories.
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影响因子：
39.2
作者：
Janes H;Pepe MS;Gu W
通讯作者：
Gu W
影响因子：
--
作者：
Kim, Kwang Pyo;Einstein, Andrew J.;de Gonzalez, Amy Berrington
通讯作者：
de Gonzalez, Amy Berrington
影响因子：
120.7
作者：
Greenland, P;LaBree, L;Detrano, RC
通讯作者：
Detrano, RC
影响因子：
158.5
作者：
Detrano, Robert;Guerci, Alan D.;Kronmal, Richard A.
通讯作者：
Kronmal, Richard A.
DOI：
10.1016/0735-1097(90)90282-t
发表时间：
1990-03-15
影响因子：
24
作者：
AGATSTON, AS;JANOWITZ, WR;DETRANO, R
通讯作者：
DETRANO, R