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在预测严重冠状动脉疾病方面,联合使用主动脉弓钙化的 SCORE2 和 ASCVD 风险评分与胸部 X 线摄影的效果。

Effectiveness of SCORE2 and ASCVD Risk Scores in Combination With Aortic Arch Calcification on Chest Radiograph in Predicting Significant Coronary Artery Disease.

机构信息

Cardiology Department, School of Medicine, Sanko University, Gaziantep, Turkey.

Ersin Arslan Education and Research Hospital, Cardiology Department, Adiyaman University Training and Research Hospital, Adıyaman, Turkey.

出版信息

Angiology. 2024 Sep;75(8):734-741. doi: 10.1177/00033197231177413. Epub 2023 May 18.

Abstract

The present study evaluated 10-year atherosclerotic cardiovascular disease (ASCVD) risk using ASCVD and Systematic Coronary Risk Evaluation (SCORE2) risk models in combination with aortic arch calcification (AAC) to identify those at high risk for significant coronary artery disease (CAD) in patients undergoing coronary angiography. Of the 402 patients enrolled, 48 had normal coronary angiograms and served as group 1. The 131 patients with CAD with stenosis of <70% as group 2 and 223 patients with CAD with stenosis of ≥70% as group 3. ASCVD and SCORE2 risk scores, and the presence of AAC differed significantly among these groups. For prediction of significant CAD, the area under the curve (AUC) of ASCVD and SCORE2 risk scores in receiver operating characteristic (ROC) curve analysis were statistically similar ([AUC: .647, < .001] and [AUC: .654, < .001], respectively). When AAC was added to ASCVD risk and SCORE2, it increased their predictive value for significant CAD in the ROC curve analysis ( = .003, and = .019, respectively). In addition, significant net reclassification improvement (NRI) values were obtained by adding AAC to ASCVD and SCORE2 risk models ([NRI = .10, = .04], and [NRI = .19, = .04], respectively). These results suggest that the predictive value of ASCVD and SCORE2 increases when AAC is combined.

摘要

本研究通过结合主动脉弓钙化(AAC)评估了使用 ASCVD 和系统性冠状动脉风险评估(SCORE2)风险模型预测 10 年动脉粥样硬化性心血管疾病(ASCVD)风险,以识别接受冠状动脉造影检查的患者中那些有严重冠状动脉疾病(CAD)风险的患者。在纳入的 402 例患者中,48 例冠状动脉造影正常,作为第 1 组。131 例 CAD 患者狭窄程度<70%为第 2 组,223 例 CAD 患者狭窄程度≥70%为第 3 组。这些组之间的 ASCVD 和 SCORE2 风险评分以及 AAC 的存在差异有统计学意义。在接受者操作特征(ROC)曲线分析中,用于预测严重 CAD,ASCVD 和 SCORE2 风险评分的曲线下面积(AUC)在统计学上无显著差异([AUC:.647, <.001]和[AUC:.654, <.001])。当将 AAC 添加到 ASCVD 风险和 SCORE2 中时,ROC 曲线分析中它们对严重 CAD 的预测价值增加(=.003,和=.019,分别)。此外,通过将 AAC 添加到 ASCVD 和 SCORE2 风险模型中,可以获得显著的净重新分类改善(NRI)值([NRI =.10, =.04],和[NRI =.19, =.04],分别)。这些结果表明,当结合 AAC 时,ASCVD 和 SCORE2 的预测价值增加。

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