Quantifying a spectrum of clinical response in atrial tachyarrhythmias using spatiotemporal synchronization of electrograms

P. Ganesan, B. Deb, R.B. Feng, M. Rodrigo, S. Ruiperez-Campillo, A.J. Rogers, P. Clopton, P.J. Wang, S. Zeemering, U. Schotten, W.J. Rappel, S.M. Narayan*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


AIMS: There is a clinical spectrum for atrial tachyarrhythmias wherein most patients with atrial tachycardia (AT) and some with atrial fibrillation (AF) respond to ablation, while others do not. It is undefined if this clinical spectrum has pathophysiological signatures. This study aims to test the hypothesis that the size of spatial regions showing repetitive synchronized electrogram (EGM) shapes over time reveals a spectrum from AT, to AF patients who respond acutely to ablation, to AF patients without acute response. METHODS AND RESULTS: We studied n = 160 patients (35% women, 65.0 ± 10.4 years) of whom (i) n = 75 had AF terminated by ablation propensity matched to (ii) n = 75 without AF termination and (iii) n = 10 with AT. All patients had mapping by 64-pole baskets to identify areas of repetitive activity (REACT) to correlate unipolar EGMs in shape over time. Synchronized regions (REACT) were largest in AT, smaller in AF termination, and smallest in non-termination cohorts (0.63 ± 0.15, 0.37 ± 0.22, and 0.22 ± 0.18, P < 0.001). Area under the curve for predicting AF termination in hold-out cohorts was 0.72 ± 0.03. Simulations showed that lower REACT represented greater variability in clinical EGM timing and shape. Unsupervised machine learning of REACT and extensive (50) clinical variables yielded four clusters of increasing risk for AF termination (P < 0.01, χ2), which were more predictive than clinical profiles alone (P < 0.001). CONCLUSION: The area of synchronized EGMs within the atrium reveals a spectrum of clinical response in atrial tachyarrhythmias. These fundamental EGM properties, which do not reflect any predetermined mechanism or mapping technology, predict outcome and offer a platform to compare mapping tools and mechanisms between AF patient groups.

Original languageEnglish
Article numbereuad055
Number of pages9
JournalEP Europace
Issue number5
Early online date1 Mar 2023
Publication statusPublished - 19 May 2023


  • Atrial fibrillation
  • Atrial tachycardia
  • Arrhythmia mapping
  • Electrogram signal processing
  • Machine learning
  • Electrophysiological study


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