Spatiotemporal Characteristics of QRS Complexes Enable the Diagnosis of Brugada Syndrome Regardless of the Appearance of a Type 1 ECG

J Cardiovasc Electrophysiol. 2016 May;27(5):563-70. doi: 10.1111/jce.12937. Epub 2016 Mar 9.


Introduction: The diagnosis of Brugada syndrome based on the ECG is hampered by the dynamic nature of its ECG manifestations. Brugada syndrome patients are only 25% likely to present a type 1 ECG. The objective of this study is to provide an ECG diagnostic criterion for Brugada syndrome patients that can be applied consistently even in the absence of a type 1 ECG.

Methods and results: We recorded 67-lead body surface potential maps from 94 Brugada syndrome patients and 82 controls (including right bundle branch block patients and healthy individuals). The spatial propagation direction during the last r' wave and the slope at the end of the QRS complex were measured and compared between patients groups. Receiver-operating characteristic curves were constructed for half of the database to identify optimal cutoff values; sensitivity and specificity for these cutoff values were measured in the other half of the database. A spontaneous type 1 ECG was present in only 30% of BrS patients. An orientation in the sagittal plane < 101º during the last r' wave and a descending slope < 9.65 mV/s enables the diagnosis of the syndrome with a sensitivity of 69% and a specificity of 97% in non-type 1 Brugada syndrome patients.

Conclusion: Spatiotemporal characteristics of surface ECG recordings can enable a robust identification of BrS even without the presence of a type 1 ECG.

Keywords: Brugada syndrome; body surface potential mapping; electrocardiography; right bundle branch block; vectorcardiography.

Publication types

  • Multicenter Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Action Potentials*
  • Adult
  • Area Under Curve
  • Brugada Syndrome / diagnosis*
  • Brugada Syndrome / physiopathology
  • Case-Control Studies
  • Electrocardiography*
  • Female
  • Heart Conduction System / physiopathology*
  • Heart Rate*
  • Humans
  • Male
  • Middle Aged
  • Predictive Value of Tests
  • ROC Curve
  • Signal Processing, Computer-Assisted
  • Spain
  • Time Factors