The emergence and destiny of automated methods to differentiate wide QRS complex tachycardias

Sarah LoCoco, Anthony H. Kashou, Peter A. Noseworthy, Daniel H. Cooper, Rugheed Ghadban, Adam M. May

Research output: Contribution to journalReview articlepeer-review

Abstract

Accurate differentiation of wide complex tachycardias (WCTs) into ventricular tachycardia (VT) or supraventricular wide complex tachycardia (SWCT) using non-invasive methods such as 12‑lead electrocardiogram (ECG) interpretation is crucial in clinical practice. Recent studies have demonstrated the potential for automated approaches utilizing computerized ECG interpretation software to achieve accurate WCT differentiation. In this review, we provide a comprehensive analysis of contemporary automated methods for VT and SWCT differentiation. Our objectives include: (i) presenting a general overview of the emergence of automated WCT differentiation methods, (ii) examining the role of machine learning techniques in automated WCT differentiation, (iii) reviewing the electrophysiology concepts leveraged existing automated algorithms, (iv) discussing recently developed automated WCT differentiation solutions, and (v) considering future directions that will enable the successful integration of automated methods into computerized ECG interpretation platforms.

Original languageEnglish
Pages (from-to)44-50
Number of pages7
JournalJournal of Electrocardiology
Volume81
DOIs
StatePublished - Nov 1 2023

Keywords

  • Electrocardiogram
  • Supraventricular tachycardia
  • Ventricular tachycardia
  • Wide QRS complex tachycardias

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