Predicting obstructive coronary artery disease using carotid ultrasound parameters: A nomogram from a large real-world clinical data
Predicting obstructive coronary artery disease using carotid ultrasound parameters: A nomogram from a large real-world clinical data
复制标题
使用颈动脉超声参数预测阻塞性冠状动脉疾病：来自大量真实临床数据的列线图
DOI：
10.1111/eci.12956
复制
发表时间：
2018-08-01
影响因子：
5.5
通讯作者：
Zhong, Li
中科院分区：
文献类型：
--
作者：
Wu, Na;Chen, Xinghua;Zhong, Li
背景颈动脉超声是冠状动脉疾病（CAD）风险评估的一种无创工具。关于颈动脉超声参数构成动脉粥样硬化的最佳测量尚无共识。我们研究了哪种颈动脉超声参数和临床危险因素（CRF）模型对CAD的预测价值最高。材料和方法我们连续招募了2431例疑似CAD的患者，并进行了冠状动脉造影和颈动脉超声检查，测量了颈动脉内膜-中膜厚度（CIMT）、斑块总数和不同类型斑块的面积。结果斑块总数对冠心病的增量预测能力高于CRF(曲线下面积[AUC] 0.752 vs 0.701，净重分类指数[NRI]=0.514， P
BackgroundCarotid ultrasound is a noninvasive tool for risk assessment of coronary artery disease (CAD). There is no consensus on which carotid ultrasound parameter constitutes the best measurement of atherosclerosis. We investigated which model of carotid ultrasound parameters and clinical risk factors (CRF) has the highest predictive value for CAD.Materials and methodsWe enrolled 2431 consecutive patients who have suspected CAD and underwent coronary angiography and carotid ultrasound with measurements of carotid intima-media thickness (CIMT), total number of plaques and areas of different types of plaques classified by echogenicity.ResultsTotal number of plaques demonstrated the highest incremental prediction ability to predict CAD over CRF (area under the curve [AUC] 0.752 vs 0.701, net reclassification index [NRI]=0.514, P