杜克临床评分和 Agatston 评分联合对阻塞性冠状动脉疾病的预测价值增加。
Incremental predictive value for obstructive coronary artery disease by combination of Duke Clinical Score and Agatston score.
机构信息
Department of Cardiology, Graduate School of Medicine, Juntendo University, Tokyo, Japan
Department of Cardiology, Jukokai Central Hospital, Miyoshi, Aichi, Japan.
出版信息
Eur Heart J Cardiovasc Imaging. 2016 May;17(5):550-6. doi: 10.1093/ehjci/jev233. Epub 2015 Sep 28.
AIMS
Recent study suggests that algorithms such as the Duke Clinical score (DCS) may overestimate the pretest probability. The Agatston score representing the grade of coronary artery calcification can be simply calculated from low-radiation exposure ECG-gated plain CT. In this study, we investigated whether or not more superior diagnostic performance for obstructive coronary artery disease (CAD) can be obtained by combining DCS with the Agatston score.
METHODS AND RESULTS
Of 3939 consecutive patients suspected of having stable angina without known CAD who underwent Coronary Computed Tomography Angiography (CCTA) as well as calculation of the DCS and Agatston score at our hospital, 3688 patients were selected as subjects. Obstructive CAD was defined as >50% diameter stenosis on CCTA; we investigated the diagnostic performance based on the area under the curve (AUC) of a receiver operating characteristic (ROC) curve, Net Reclassification Improvement (NRI), and Integrated Discrimination Improvement (IDI). The AUCs of ROCs prepared using the DCS alone and combination of the DCS and Agatston score were 0.7137 and 0.8057, respectively, showing that the diagnostic performance of the combination was significantly superior to DCS alone (P < 0.001). NRI was 0.8132 and IDI was 0.1374, showing that the diagnostic performance was improved by the combination of the DCS and Agatston score compared with DCS alone (P < 0.001). NRI (0.3522) and IDI (0.0287) were improved compared with those of the Agatston score alone (P < 0.001).
CONCLUSION
The combination of the DCS and Agatston score improved the diagnostic performance for obstructive CAD compared with DCS alone and Agatston score.
目的
最近的研究表明，杜克临床评分（DCS）等算法可能会高估预测概率。代表冠状动脉钙化程度的 Agatston 评分可以通过低辐射暴露的心电图门控平扫 CT 简单计算。在这项研究中，我们研究了将 DCS 与 Agatston 评分相结合是否可以获得更好的阻塞性冠心病（CAD）诊断性能。
方法和结果
在我院接受冠状动脉计算机断层扫描血管造影（CCTA）检查以及 DCS 和 Agatston 评分计算的 3939 例连续疑似稳定型心绞痛且无已知 CAD 的患者中，选择 3688 例患者作为研究对象。阻塞性 CAD 的定义为 CCTA 上的>50% 直径狭窄；我们根据接受者操作特征（ROC）曲线的曲线下面积（AUC）、净重新分类改善（NRI）和综合判别改善（IDI）来研究诊断性能。仅使用 DCS 和 DCS 与 Agatston 评分组合制备的 ROC 的 AUC 分别为 0.7137 和 0.8057，表明组合的诊断性能明显优于单独使用 DCS（P <0.001）。NRI 为 0.8132，IDI 为 0.1374，表明与单独使用 DCS 相比，DCS 和 Agatston 评分的组合提高了诊断性能（P <0.001）。与单独使用 Agatston 评分相比，NRI（0.3522）和 IDI（0.0287）有所改善（P <0.001）。
结论
与单独使用 DCS 相比，DCS 与 Agatston 评分的组合改善了阻塞性 CAD 的诊断性能。
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