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Journal of Interventional Cardiac Electrophysiology

22-01-2024 | Supraventricular Tachycardia

A machine learning approach to differentiate wide QRS tachycardia: distinguishing ventricular tachycardia from supraventricular tachycardia

Authors: Zhen-Zhen Li, Wei Zhao, YangMing Mao, Dan Bo, QiuShi Chen, Pipin Kojodjojo, FengXiang Zhang

Published in: Journal of Interventional Cardiac Electrophysiology

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Abstract

Background

Differential diagnosis of wide QRS tachycardia (WQCT) has been a challenging issue. Published algorithms to distinguish ventricular tachycardia (VT) and supraventricular tachycardia (SVT) have limited diagnostic capabilities.

Methods

A total of 278 patients with WQCT from January 2010 to March 2022 were enrolled. The electrophysiological study confirmed SVT in 154 patients and VT in 65 ones. Two hundred nineteen WQCT 12-lead ECGs were randomly divided into development cohort (n = 165) and testing cohort (n = 54) data sets. The development cohort was split into a training group (n = 115) and an internal validation group (n = 50). Forty ECG features extracted from the 219 WQCT ECGs are fed into 9 iteratively trained ML algorithms. This novel ML algorithm was also compared with four published algorithms.

Results

In the development cohort, the Gradient Boosting Machine (GBM) model displayed the maximum area under curve (AUC) (0.91, 95% confidence interval (CI) 0.81–1.00). In the testing cohort, the GBM model had a higher AUC of 0.97 compared to 4 validated ECG algorithms, namely, Brugada (0.68), avR (0.62), RWPTII (0.72), and LLA algorithms (0.70). Accuracy, sensitivity, specificity, negative predictive value, and positive predictive value of the GBM model were 0.94, 0.97, 0.90, 0.94, and 0.95, respectively.

Conclusions

A GBM ML model contributes to distinguishing SVT from VT based on surface ECG features. In addition, we were able to identify important indicators for distinguishing WQCT.
Appendix
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Metadata
Title
A machine learning approach to differentiate wide QRS tachycardia: distinguishing ventricular tachycardia from supraventricular tachycardia
Authors
Zhen-Zhen Li
Wei Zhao
YangMing Mao
Dan Bo
QiuShi Chen
Pipin Kojodjojo
FengXiang Zhang
Publication date
22-01-2024
Publisher
Springer US
Published in
Journal of Interventional Cardiac Electrophysiology
Print ISSN: 1383-875X
Electronic ISSN: 1572-8595
DOI
https://doi.org/10.1007/s10840-024-01743-9