The r’-Wave Algorithm: A New Diagnostic Tool to Predict the Diagnosis of Brugada Syndrome after a Sodium Channel Blocker Provocation Test
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, t...
| Main Authors: | , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-03-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/23/6/3159 |
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| author | 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 |
| author_facet | 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 |
| author_sort | Giampaolo Vetta |
| collection | DOAJ |
| description | 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) (<i>p</i> < 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. |
| first_indexed | 2024-03-11T05:56:25Z |
| format | Article |
| id | doaj.art-9c6d0c92011f4b468fcff3db3614af1c |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-11T05:56:25Z |
| publishDate | 2023-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-9c6d0c92011f4b468fcff3db3614af1c2023-11-17T13:46:47ZengMDPI AGSensors1424-82202023-03-01236315910.3390/s23063159The r’-Wave Algorithm: A New Diagnostic Tool to Predict the Diagnosis of Brugada Syndrome after a Sodium Channel Blocker Provocation TestGiampaolo Vetta0Antonio Parlavecchio1Lorenzo Pistelli2Paolo Desalvo3Armando Lo Savio4Michele Magnocavallo5Rodolfo Caminiti6Anna Tribuzio7Alessandro Vairo8Diego La Maestra9Francesco Vetta10Giuseppe Dattilo11Francesco Luzza12Gianluca Di Bella13Roberta Rossini14Domenico Giovanni Della Rocca15Pasquale Crea16Cardiology Unit, Department of Clinical and Experimental Medicine, University of Messina, 98122 Messina, ItalyCardiology Unit, Department of Clinical and Experimental Medicine, University of Messina, 98122 Messina, ItalyCardiology Unit, Department of Clinical and Experimental Medicine, University of Messina, 98122 Messina, ItalyCardiology Unit, Department of Emergency and Critical Care, Hospital S. Croce e Carle, 12100 Cuneo, ItalyCardiology Unit, Department of Clinical and Experimental Medicine, University of Messina, 98122 Messina, ItalyCardiology Division, Arrhythmology Unit, S. Giovanni Calibita Hospital, Isola Tiberina, 00186 Rome, ItalyCardiology Unit, Department of Clinical and Experimental Medicine, University of Messina, 98122 Messina, ItalyDivision of Cardiology, Cardiovascular and Thoracic Department, Città della Salute e della Scienza University Hospital of Turin, 10126 Turin, ItalyDivision of Cardiology, Cardiovascular and Thoracic Department, Città della Salute e della Scienza University Hospital of Turin, 10126 Turin, ItalyCardiology Unit, Department of Clinical and Experimental Medicine, University of Messina, 98122 Messina, ItalyFaculty of Medicine and Surgery, Saint Camillus International University of Health Sciences, 00131 Rome, ItalyCardiology Unit, Department of Clinical and Experimental Medicine, University of Messina, 98122 Messina, ItalyCardiology Unit, Department of Clinical and Experimental Medicine, University of Messina, 98122 Messina, ItalyCardiology Unit, Department of Clinical and Experimental Medicine, University of Messina, 98122 Messina, ItalyCardiology Unit, Department of Emergency and Critical Care, Hospital S. Croce e Carle, 12100 Cuneo, ItalyHeart Rhythm Management Centre, Postgraduate Program in Cardiac Electrophysiology and Pacing, Universitair Ziekenhuis Brussel-Vrije Universiteit Brussel, European Reference Networks Guard-Heart, 1090 Brussels, BelgiumCardiology Unit, Department of Clinical and Experimental Medicine, University of Messina, 98122 Messina, ItalyA 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) (<i>p</i> < 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.https://www.mdpi.com/1424-8220/23/6/3159Brugada syndromeelectrocardiogramβ-angleα-angler’-waver’-wave algorithm |
| spellingShingle | 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 The r’-Wave Algorithm: A New Diagnostic Tool to Predict the Diagnosis of Brugada Syndrome after a Sodium Channel Blocker Provocation Test Sensors Brugada syndrome electrocardiogram β-angle α-angle r’-wave r’-wave algorithm |
| title | The r’-Wave Algorithm: A New Diagnostic Tool to Predict the Diagnosis of Brugada Syndrome after a Sodium Channel Blocker Provocation Test |
| title_full | The r’-Wave Algorithm: A New Diagnostic Tool to Predict the Diagnosis of Brugada Syndrome after a Sodium Channel Blocker Provocation Test |
| title_fullStr | The r’-Wave Algorithm: A New Diagnostic Tool to Predict the Diagnosis of Brugada Syndrome after a Sodium Channel Blocker Provocation Test |
| title_full_unstemmed | The r’-Wave Algorithm: A New Diagnostic Tool to Predict the Diagnosis of Brugada Syndrome after a Sodium Channel Blocker Provocation Test |
| title_short | The r’-Wave Algorithm: A New Diagnostic Tool to Predict the Diagnosis of Brugada Syndrome after a Sodium Channel Blocker Provocation Test |
| title_sort | r wave algorithm a new diagnostic tool to predict the diagnosis of brugada syndrome after a sodium channel blocker provocation test |
| topic | Brugada syndrome electrocardiogram β-angle α-angle r’-wave r’-wave algorithm |
| url | https://www.mdpi.com/1424-8220/23/6/3159 |
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