背景:在慢性和非传染性疾病中,心血管疾病是导致死亡的首要原因。通常用于外周和颈动脉粥样硬化的诊断工具,如踝肱指数(ABI)和颈动脉超声检查(CU),可能作为冠状动脉疾病(CAD)诊断的替代指标。
方法:我们报告了一项涉及50例择期有创冠状动脉造影(ICA)患者的横断面研究。患者接受ABI和CU进行颈动脉内膜中层厚度(CIMT)和颈动脉粥样硬化斑块筛查(CAPS)。还评估了临床和人口统计学变量。CAD被定义为在至少一个冠状动脉中大于50%的狭窄。
结果:在逻辑回归分析中,仅CAPS显示CAD预测的曲线下面积(AUC)有统计学意义:0.812(95%CI,p<0.001).ABI和CIMT没有显示出统计学上显著的表现。对于多变量逻辑回归分析,包括变量\“性别,\“\”血脂异常,\"\"吸烟,\"\"包年,“和CAPS更好地预测了CAD。该模型的AUC为0.912(95%CI,p=0.002)。
结论:颈动脉粥样硬化斑块的筛查可能会增强传统的CAD风险分层策略。需要纵向研究和更大的受试者样本才能推断我们的发现。
BACKGROUND: Cardiovascular disease represents the foremost cause of death among chronic and non-transmissible diseases. Diagnostic tools commonly used for peripheral and carotid atherosclerosis, such as ankle-brachial index (ABI) and carotid ultrasonography (CU), may contribute as surrogates for the diagnosis of coronary arterial disease (CAD).
METHODS: We report a cross-sectional study of 50 patients referred to elective invasive coronary angiography (ICA). Patients were submitted to ABI and CU-for carotid intima-media thickness (CIMT) and carotid atherosclerotic plaque screening (CAPS). Clinical and demographic variables were also evaluated. CAD was defined as greater than 50% stenosis in at least one coronary artery.
RESULTS: In logistic regression analysis, only CAPS showed a statistically significant area under the curve (AUC) for CAD prediction: 0.812 (95% CI, p <0.001). ABI and CIMT did not show statistically significant performance. For multivariate logistic regression analysis, the model including variables \"gender,\" \"dyslipidemia,\" \"smoking,\" \"pack-years,\" and CAPS predicted CAD better. The AUC for this model was 0.912 (95% CI, p = 0.002).
CONCLUSIONS: The screening for carotid atherosclerotic plaques may enhance traditional risk stratification strategies for CAD. Longitudinal studies and bigger samples of subject are needed to allow extrapolation of our findings.