The r’-Wave Algorithm: A New Diagnostic Tool to Predict the Diagnosis of Brugada Syndrome after a Sodium Channel Blocker Provocation Test
Giampaolo Vetta,
Antonio Parlavecchio,
Lorenzo Pistelli,
Paolo Desalvo,
Armando Lo Savio,
Michele Magnocavallo,
Rodolfo Caminiti,
Anna Tribuzio,
Alessandro Vairo,
Diego La Maestra,
Francesco Vetta,
Giuseppe Dattilo,
Francesco Luzza,
Gianluca Di Bella,
Roberta Rossini,
Domenico Giovanni Della Rocca,
Pasquale Crea
Affiliations
Giampaolo Vetta
Cardiology Unit, Department of Clinical and Experimental Medicine, University of Messina, 98122 Messina, Italy
Antonio Parlavecchio
Cardiology Unit, Department of Clinical and Experimental Medicine, University of Messina, 98122 Messina, Italy
Lorenzo Pistelli
Cardiology Unit, Department of Clinical and Experimental Medicine, University of Messina, 98122 Messina, Italy
Paolo Desalvo
Cardiology Unit, Department of Emergency and Critical Care, Hospital S. Croce e Carle, 12100 Cuneo, Italy
Armando Lo Savio
Cardiology Unit, Department of Clinical and Experimental Medicine, University of Messina, 98122 Messina, Italy
Michele Magnocavallo
Cardiology Division, Arrhythmology Unit, S. Giovanni Calibita Hospital, Isola Tiberina, 00186 Rome, Italy
Rodolfo Caminiti
Cardiology Unit, Department of Clinical and Experimental Medicine, University of Messina, 98122 Messina, Italy
Anna Tribuzio
Division of Cardiology, Cardiovascular and Thoracic Department, Città della Salute e della Scienza University Hospital of Turin, 10126 Turin, Italy
Alessandro Vairo
Division of Cardiology, Cardiovascular and Thoracic Department, Città della Salute e della Scienza University Hospital of Turin, 10126 Turin, Italy
Diego La Maestra
Cardiology Unit, Department of Clinical and Experimental Medicine, University of Messina, 98122 Messina, Italy
Francesco Vetta
Faculty of Medicine and Surgery, Saint Camillus International University of Health Sciences, 00131 Rome, Italy
Giuseppe Dattilo
Cardiology Unit, Department of Clinical and Experimental Medicine, University of Messina, 98122 Messina, Italy
Francesco Luzza
Cardiology Unit, Department of Clinical and Experimental Medicine, University of Messina, 98122 Messina, Italy
Gianluca Di Bella
Cardiology Unit, Department of Clinical and Experimental Medicine, University of Messina, 98122 Messina, Italy
Roberta Rossini
Cardiology Unit, Department of Emergency and Critical Care, Hospital S. Croce e Carle, 12100 Cuneo, Italy
Domenico Giovanni Della Rocca
Heart Rhythm Management Centre, Postgraduate Program in Cardiac Electrophysiology and Pacing, Universitair Ziekenhuis Brussel-Vrije Universiteit Brussel, European Reference Networks Guard-Heart, 1090 Brussels, Belgium
Pasquale Crea
Cardiology Unit, Department of Clinical and Experimental Medicine, University of Messina, 98122 Messina, Italy
A diagnosis of Brugada syndrome (BrS) is based on the presence of a type 1 electrocardiogram (ECG) pattern, either spontaneously or after a Sodium Channel Blocker Provocation Test (SCBPT). Several ECG criteria have been evaluated as predictors of a positive SCBPT, such as the β-angle, the α-angle, the duration of the base of the triangle at 5 mm from the r’-wave (DBT- 5 mm), the duration of the base of the triangle at the isoelectric line (DBT- iso), and the triangle base/height ratio. The aim of our study was to test all previously proposed ECG criteria in a large cohort study and to evaluate an r’-wave algorithm for predicting a BrS diagnosis after an SCBPT. We enrolled all patients who consecutively underwent SCBPT using flecainide from January 2010 to December 2015 in the test cohort and from January 2016 to December 2021 in the validation cohort. We included the ECG criteria with the best diagnostic accuracy in relation to the test cohort in the development of the r’-wave algorithm (β-angle, α-angle, DBT- 5 mm, and DBT- iso.) Of the total of 395 patients enrolled, 72.4% were male and the average age was 44.7 ± 13.5 years. Following the SCBPTs, 24.1% of patients (n = 95) were positive and 75.9% (n = 300) were negative. ROC analysis of the validation cohort showed that the AUC of the r’-wave algorithm (AUC: 0.92; CI 0.85–0.99) was significantly better than the AUC of the β-angle (AUC: 0.82; 95% CI 0.71–0.92), the α-angle (AUC: 0.77; 95% CI 0.66–0.90), the DBT- 5 mm (AUC: 0.75; 95% CI 0.64–0.87), the DBT- iso (AUC: 0.79; 95% CI 0.67–0.91), and the triangle base/height (AUC: 0.61; 95% CI 0.48–0.75) (p < 0.001), making it the best predictor of a BrS diagnosis after an SCBPT. The r’-wave algorithm with a cut-off value of ≥2 showed a sensitivity of 90% and a specificity of 83%. In our study, the r’-wave algorithm was proved to have the best diagnostic accuracy, compared with single electrocardiographic criteria, in predicting the diagnosis of BrS after provocative testing with flecainide.
