Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands.
Eur J Prev Cardiol. 2012 Aug;19(4):698-705. doi: 10.1177/1741826711414623. Epub 2011 Jun 22.
Non-invasive measures of atherosclerosis, such as carotid intima-media thickness (cIMT), may improve global cardiovascular risk prediction. The aim of this study was to determine whether common carotid IMT in addition to traditional risk factors improves risk classification in a general population of older people.
A group of 3580 non-diabetic people aged 55-75 years and free of cardiovascular disease at baseline were followed for a median time of 12.2 years. Compared to models based on Framingham risk factors, we studied the ability of common cIMT measurement to better classify people into categories of low (<10%), intermediate (10-20%) and high (>20%) 10-year risk of hard coronary heart disease (CHD) and stroke. In older men, addition of cIMT to Framingham risk factors did not improve prediction of hard CHD or stroke. In older women, addition of cIMT to Framingham risk factors significantly improved risk classification. cIMT improved the C-statistic of the model for hard CHD from 0.711 to 0.719 and for stroke from 0.712 to 0.721, at good calibration. Reclassification was least in the majority of women classified as low risk (4% (n = 76) for hard CHD and 3% (n = 62) for stroke) and most substantial in women at intermediate risk (43% (n = 70) for hard CHD and 28% (n = 76) for stroke). The net reclassification improvement in women was 8.2% (p = 0.03) for hard CHD and 8.0% (p = 0.06) for stroke.
cIMT had some additional value beyond traditional risk factors in the cardiovascular risk stratification of older women, but not of older men.
颈动脉内膜中层厚度(cIMT)等非侵入性动脉粥样硬化指标可能改善整体心血管风险预测。本研究旨在确定在一般老年人群中,在传统危险因素的基础上增加颈总动脉 IMT 是否能改善风险分类。
本研究纳入了 3580 名无糖尿病、基线时无心血管疾病且年龄在 55-75 岁之间的人群,中位随访时间为 12.2 年。与基于弗雷明汉风险因素的模型相比,我们研究了测量颈总动脉 cIMT 来更好地将人群分为低(<10%)、中(10-20%)和高(>20%)10 年发生硬冠状动脉心脏病(CHD)和卒中风险人群的能力。在老年男性中,cIMT 与弗雷明汉风险因素的联合应用并未改善硬 CHD 或卒中的预测。在老年女性中,cIMT 与弗雷明汉风险因素的联合应用显著改善了风险分类。cIMT 使硬 CHD 模型的 C 统计量从 0.711 提高到 0.719,使卒中模型的 C 统计量从 0.712 提高到 0.721,且校准良好。再分类在大多数被归类为低危的女性中最少(硬 CHD 为 4%(n=76),卒中为 3%(n=62)),在中危女性中最大(硬 CHD 为 43%(n=70),卒中为 28%(n=76))。女性的净再分类改善为硬 CHD 8.2%(p=0.03),卒中 8.0%(p=0.06)。
在老年女性的心血管风险分层中,cIMT 在传统危险因素之外具有一定的附加价值,但在老年男性中则没有。