Plesinger Filip, van Stipdonk Antonius M W, Smisek Radovan, Halamek Josef, Jurak Pavel, Maass Alexander H, Meine Mathias, Vernooy Kevin, Prinzen Frits W
Institute of Scientific Instruments of the Czech Academy of Sciences, Brno, Czech Republic.
Department of Cardiology, Maastricht University Medical Center, Maastricht, the Netherlands.
J Electrocardiol. 2020 Nov-Dec;63:159-163. doi: 10.1016/j.jelectrocard.2019.07.003. Epub 2019 Jul 9.
Cardiac resynchronization therapy (CRT) is an established treatment in patients with heart failure and conduction abnormalities. However, a significant number of patients do not respond to CRT. Currently employed criteria for selection of patients for this therapy (QRS duration and morphology) have several shortcomings. QRS area was recently shown to provide superior association with CRT response. However, its assessment was not fully automated and required the presence of an expert.
Our objective was to develop a fully automated method for the assessment of vector-cardiographic (VCG) QRS area from electrocardiographic (ECG) signals.
Pre-implantation ECG recordings (N = 864, 695 left-bundle-branch block, 589 men) in PDF files were converted to allow signal processing. QRS complexes were found and clustered into morphological groups. Signals were converted from 12‑lead ECG to 3‑lead VCG and an average QRS complex was built. QRS area was computed from individual areas in the X, Y and Z leads. Practical usability was evaluated using Kaplan-Meier plots and 5-year follow-up data.
The automatically calculated QRS area values were 123 ± 48 μV.s (mean values and SD), while the manually determined QRS area values were 116 ± 51 ms; the correlation coefficient between the two was r = 0.97. The automated and manual methods showed the same ability to stratify the population (hazard ratios 2.09 vs 2.03, respectively).
The presented approach allows the fully automatic and objective assessment of QRS area values.
Until this study, assessing QRS area values required an expert, which means both additional costs and a risk of subjectivity. The presented approach eliminates these disadvantages and is publicly available as part of free signal-processing software.
心脏再同步治疗（CRT）是心力衰竭合并传导异常患者的既定治疗方法。然而，相当数量的患者对CRT无反应。目前用于选择该治疗患者的标准（QRS波时限和形态）存在若干缺点。最近研究表明，QRS面积与CRT反应的相关性更强。然而，其评估尚未完全自动化，需要专家在场。
我们的目标是开发一种从心电图（ECG）信号中全自动评估心电向量图（VCG）QRS面积的方法。
将PDF文件中的植入前ECG记录（N = 864，695例左束支传导阻滞，589例男性）进行转换，以便进行信号处理。找到QRS波群并将其聚类为形态学组。将信号从12导联ECG转换为3导联VCG，并构建平均QRS波群。根据X、Y和Z导联中的各个面积计算QRS面积。使用Kaplan-Meier曲线和5年随访数据评估实际可用性。
自动计算的QRS面积值为123±48μV·s（平均值和标准差），而手动确定的QRS面积值为116±51ms；两者之间的相关系数为r = 0.97。自动和手动方法对人群分层的能力相同（风险比分别为2.09和2.03）。
所提出的方法允许对QRS面积值进行全自动和客观评估。
在本研究之前，评估QRS面积值需要专家，这意味着会产生额外费用以及存在主观性风险。所提出的方法消除了这些缺点，并作为免费信号处理软件的一部分公开提供。
