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| Progress in preoperative ECG to predict the response to cardiac resynchronization therapy |
| Cheng Yan, Zhang Chang-ying , Wang Ru-xing |
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Abstract Non-response rate remains to be high when QRS duration combined with complete left bundle branch block is used as the patient selection criteria for cardiac resynchronization therapy （CRT）. QRS duration index, R-wave and T-wave heterogeneity, fragmented QRS complex, QRS area, sum absolute QRST integral and machine learning of ECG are associated with cardiac asynchrony and degree of myocardial fibrosis, and could predict CRT response effectively. Combination of novel ECG indicators helps to predict CRT response more accurately. Machine learning has been providing a better solution for the selection of CRT candidates.
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