Green Michael, Ohlsson Mattias, Forberg Jakob Lundager, Björk Jonas, Edenbrandt Lars, Ekelund Ulf
Department of Theoretical Physics, Lund University, Lund, Sweden.
J Electrocardiol. 2007 Jul;40(3):251-6. doi: 10.1016/j.jelectrocard.2006.12.011. Epub 2007 Feb 8.
The purpose of this study was to determine which leads in the standard 12-lead electrocardiogram (ECG) are the best for detecting acute coronary syndrome (ACS) among chest pain patients in the emergency department.
Neural network classifiers were used to determine the predictive capability of individual leads and combinations of leads from 862 ECGs from chest pain patients in the emergency department at Lund University Hospital.
The best individual lead was aVL, with an area under the receiver operating characteristic curve of 75.5%. The best 3-lead combination was III, aVL, and V2, with a receiver operating characteristic area of 82.0%, compared with the 12-lead ECG performance of 80.5%.
Our results indicate that leads III, aVL, and V2 are sufficient for computerized prediction of ACS. The present results are likely important in situations where the 12-lead ECG is impractical and for the creation of clinical decision support systems for ECG prediction of ACS.
本研究旨在确定在急诊科胸痛患者中,标准12导联心电图(ECG)的哪些导联最适合检测急性冠状动脉综合征(ACS)。
使用神经网络分类器来确定来自隆德大学医院急诊科胸痛患者的862份心电图中各个导联及导联组合的预测能力。
最佳的单个导联是aVL,其受试者工作特征曲线下面积为75.5%。最佳的三导联组合是III、aVL和V2,受试者工作特征面积为82.0%,而12导联心电图的表现为80.5%。
我们的结果表明,III、aVL和V2导联足以用于ACS的计算机化预测。目前的结果在12导联心电图不实用的情况下以及创建用于ACS心电图预测的临床决策支持系统方面可能具有重要意义。