Department of Cardiology, Haydarpasa Sultan Abdulhamid Han Training and Research Hospital, Istanbul, Turkey.
Department of Medicine and Therapeutics, Faculty of Medicine, Chinese University of Hong Kong, China.
Heart Lung Circ. 2020 Nov;29(11):1603-1612. doi: 10.1016/j.hlc.2020.04.011. Epub 2020 Jun 11.
Electrocardiography (ECG) remains an irreplaceable tool in the management of the patients with myocardial infarction, with evaluation of the QRS and ST segment being the present major focus. Several ECG parameters have already been proposed to have prognostic value with regard to both in-hospital and long-term follow-up of patients. In this review, we discuss various ECG parameters other than ST segment changes, particularly with regard to their in-hospital prognostic importance. Our review not only evaluates the prognostic segments and parts of ECG, but also highlights the need for an integrative approach in big data to re-assess the parameters reported to predict in-hospital prognosis. The evolving importance of artificial intelligence in evaluation of ECG, particularly with regard to predicting prognosis, and the potential integration with other patient characteristics to predict prognosis, are discussed.
心电图(ECG)在心肌梗死患者的管理中仍然是一种不可或缺的工具,目前主要关注 QRS 和 ST 段的评估。已经提出了几种心电图参数,它们对住院期间和患者长期随访都具有预后价值。在这篇综述中,我们讨论了除 ST 段改变以外的各种心电图参数,特别是它们在住院期间预后重要性。我们的综述不仅评估了心电图的预后节段和部分,还强调了在大数据中采用综合方法重新评估报告的参数以预测住院期间预后的必要性。讨论了人工智能在心电图评估中的不断发展的重要性,特别是在预测预后方面,以及与其他患者特征相结合预测预后的潜力。