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

IF 2.6 3区 医学 Q2 PERIPHERAL VASCULAR DISEASE
Angiology Pub Date : 2024-09-01 Epub Date: 2023-05-18 DOI:10.1177/00033197231177413
Mustafa Cetin, Chyngyz Maksutov, Eldarbek Isakulov, Yusuf Hosoglu
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引用次数: 0

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, P < .001] and [AUC: .654, P < .001], respectively). When AAC was added to ASCVD risk and SCORE2, it increased their predictive value for significant CAD in the ROC curve analysis (P = .003, and P = .019, respectively). In addition, significant net reclassification improvement (NRI) values were obtained by adding AAC to ASCVD and SCORE2 risk models ([NRI = .10, P = .04], and [NRI = .19, P = .04], respectively). These results suggest that the predictive value of ASCVD and SCORE2 increases when AAC is combined.

SCORE2 和 ASCVD 风险评分结合胸片主动脉弓钙化对预测重大冠状动脉疾病的效果。
本研究使用动脉粥样硬化性心血管疾病(ASCVD)和系统性冠状动脉风险评估(SCORE2)风险模型结合主动脉弓钙化(AAC)对接受冠状动脉造影术的患者进行了 10 年动脉粥样硬化性心血管疾病(ASCVD)风险评估,以确定哪些患者是重大冠状动脉疾病(CAD)的高风险人群。在入组的 402 名患者中,有 48 名患者的冠状动脉造影检查结果正常,被列为第一组;131 名患者的冠状动脉狭窄程度分别为[AUC:.654,P < .001]和[AUC:.654,P < .001]]。当将 AAC 加入 ASCVD 风险和 SCORE2 时,在 ROC 曲线分析中增加了它们对显著 CAD 的预测值(分别为 P = .003 和 P = .019)。此外,将 AAC 添加到 ASCVD 和 SCORE2 风险模型中还可获得明显的净再分类改善(NRI)值(分别为 [NRI = .10, P = .04] 和 [NRI = .19, P = .04])。这些结果表明,结合 AAC 后,ASCVD 和 SCORE2 的预测价值会增加。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Angiology
Angiology 医学-外周血管病
CiteScore
5.50
自引率
14.30%
发文量
180
审稿时长
6-12 weeks
期刊介绍: A presentation of original, peer-reviewed original articles, review and case reports relative to all phases of all vascular diseases, Angiology (ANG) offers more than a typical cardiology journal. With approximately 1000 pages per year covering diagnostic methods, therapeutic approaches, and clinical and laboratory research, ANG is among the most informative publications in the field of peripheral vascular and cardiovascular diseases. This journal is a member of the Committee on Publication Ethics (COPE). Average time from submission to first decision: 13 days
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