Young William J, van Duijvenboden Stefan, Ramírez Julia, Jones Aled, Tinker Andrew, Munroe Patricia B, Lambiase Pier D, Orini Michele
Clinical Pharmacology Department, William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, EC1M 6BQ, United Kingdom.
Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS trust, London, EC1A 7BE, United Kingdom.
Biomed Signal Process Control. 2021 Feb;64:102305. doi: 10.1016/j.bspc.2020.102305.
The spatial QRS-T angle (QRS-Ta) derived from the vectorcardiogram (VCG) is a strong risk predictor for ventricular arrhythmia and sudden cardiac death with potential use for mass screening. Accurate QRS-Ta estimation in the presence of ECG delineation errors is crucial for its deployment as a prognostic test. Our study assessed the effect of inaccurate QRS and T-wave marker placement on QRS-Ta estimation and proposes a robust method for its calculation. Reference QRS-Ta measurements were derived from 1,512 VCGs manually annotated by three expert reviewers. We systematically changed onset and offset timings of QRS and T-wave markers to simulate inaccurate placement. The QRS-Ta was recalculated using a standard approach and our proposed algorithm, which limits the impact of VCG marker inaccuracies by defining the vector origin as an interval preceding QRS-onset and redefines the beginning and end of QRS and T-wave loops. Using the standard approach, mean absolute errors (MAE) in peak QRS-Ta were >40% and sensitivity and precision in the detection of abnormality (>105°) were <80% and <65% respectively, when QRS-onset was delayed or QRS-offset anticipated >15 ms. Using our proposed algorithm, MAE for peak QRS-Ta were reduced to <4% and sensitivity and precision of abnormality were >94% for inaccuracies up to ±15 ms. Similar results were obtained for mean QRS-Ta. In conclusion, inaccuracies of QRS and T-wave markers can significantly influence the QRS-Ta. Our proposed algorithm provides robust QRS-Ta measurements in the presence of inaccurate VCG annotation, enabling its use in large datasets.
从向量心电图(VCG)得出的空间QRS-T角(QRS-Ta)是室性心律失常和心源性猝死的有力风险预测指标,具有用于大规模筛查的潜力。在存在心电图描记误差的情况下准确估计QRS-Ta对于将其用作预后测试至关重要。我们的研究评估了QRS和T波标记放置不准确对QRS-Ta估计的影响,并提出了一种稳健的计算方法。参考QRS-Ta测量值来自由三位专家审阅者手动注释的1512份VCG。我们系统地改变了QRS和T波标记的起始和偏移时间,以模拟不准确的放置。使用标准方法和我们提出的算法重新计算QRS-Ta,我们提出的算法通过将向量原点定义为QRS起始前的一个间隔来限制VCG标记不准确的影响,并重新定义QRS和T波环的起点和终点。使用标准方法,当QRS起始延迟或QRS偏移提前>15毫秒时,QRS-Ta峰值的平均绝对误差(MAE)>40%,检测异常(>105°)的灵敏度和精确度分别<80%和<65%。使用我们提出的算法,对于高达±15毫秒的不准确情况,QRS-Ta峰值的MAE降低到<4%,异常的灵敏度和精确度>94%。平均QRS-Ta也得到了类似的结果。总之,QRS和T波标记的不准确会显著影响QRS-Ta。我们提出的算法在VCG注释不准确的情况下提供了稳健的QRS-Ta测量值,使其能够用于大型数据集。