Defining electrocardiographic criteria to differentiate non-type 1 Brugada ECG variants from normal incomplete RBBB patterns in the young SCD-SOS cohort.


Journal

Journal of cardiovascular electrophysiology
ISSN: 1540-8167
Titre abrégé: J Cardiovasc Electrophysiol
Pays: United States
ID NLM: 9010756

Informations de publication

Date de publication:
09 2022
Historique:
received: 02 03 2022
accepted: 26 05 2022
pubmed: 1 7 2022
medline: 14 9 2022
entrez: 30 6 2022
Statut: ppublish

Résumé

We assessed the prevalence of non-type 1 Brugada pattern (T1BrP) in children and young adults from the Sudden Cardiac Death-Screening Of risk factorS cohort and the diagnostic yield of nonexpert manual and automatic algorithm electrocardiogram (ECG) measurements. Cross-sectional study. We reviewed 14 662 ECGs and identified 2226 with a rSr'-pattern in V1-V2. Among these, 115 were classified by experts in hereditary arrhythmic-syndromes as having or not non-T1BrP, and were compared with measurements of 5 ECG-derived parameters based on a triangle formed by r' -wave (d(A), d(B), d(B)/h, β-angle) and ST-ascent, assessed both automatically and manually by nonexperts. We estimated intra- and interobserver concordance for each criterion, calculated diagnostic accuracy and defined the most appropriate cut-off values. A rSr'-pattern in V1-V2 was associated with higher PQ interval and QRS duration, male gender, and lower body mass index (BMI). The manual measurements of non-T1BrP criteria were moderately reproducible with high intraobserver and moderate interobserver concordance coefficients (ICC: 0.72-0.98, and 0.63-0.76). Criteria with higher discriminatory capacity were: distance d(B) (0.72; 95% confidence interval [CI]: 0.65-0.80) and ST-ascent (0.87; 95% CI: 0.82-0.92), which was superior to the 4 r'-wave criteria together (area under curve [AUC: 0.74]). We suggest new cut-offs with improved combination of sensitivity and specificity: d(B) ≥ 1.4 mm and ST-ascent ≥ 0.7 mm (sensitivity: 1%-82%; specificity: 71%-84%), that can be automatically measured to allow classification in four morphologies with increasing non-T1BrP probability. rSr'-pattern in precordial leads V1-V2 is a frequent finding and the detection of non-T1BrP by using the aforementioned five measurements is reproducible and accurate. In this study, we describe new cut-off values that may help untrained clinicians to identify young individuals who may require further work-up for a potential Brugada Syndrome diagnosis.

Identifiants

pubmed: 35771489
doi: 10.1111/jce.15615
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

2083-2091

Commentaires et corrections

Type : CommentIn

Informations de copyright

© 2022 Wiley Periodicals LLC.

Références

Brugada J, Campuzano O, Arbelo E, Sarquella-Brugada G, Brugada R. Present status of Brugada syndrome: JACC State-of-the-Art review. J Am Coll Cardiol. 2018;72(9):1046-1059.
Priori SG, Blomström-Lundqvist C, Mazzanti A, et al. 2015 ESC guidelines for the management of patients with ventricular arrhythmias and the prevention of sudden cardiac death. Eur Heart J. 2015;36(41):2793-2867.
Bayés De Luna A, Brugada J, Baranchuk A, et al. Current electrocardiographic criteria for diagnosis of Brugada pattern: a consensus report. J Electrocardiol. 2012;45(5):433-442.
Serra G, Baranchuk A, Bayes-De-Luna A, et al. New electrocardiographic criteria to differentiate the Type-2 Brugada pattern from electrocardiogram of healthy athletes with r′-wave in leads V1/V2. Europace. 2014;16(11):1639-1645.
Providência R, Silva J, Seca L, et al. Screening for warning signs of sudden cardiac death in the young: the SCD-SOS questionnaire. Rev Port Cardiol. 2010;29(7-8):1191-1205.
Luna AB, Garcia-Niebla J, Baranchuk A. New electrocardiographic features in Brugada syndrome. Curr Cardiol Rev. 2014;10(3):175-180.
Rautaharju PM, Surawicz B, Gettes LS, et al. AHA/ACCF/HRS recommendations for the standardization and interpretation of the electrocardiogram: part IV: The ST segment, T and U waves, and the QT interval: a scientific statement from the American Heart Association Electrocardiography and Arrhythmias Committee, Council on Clinical Cardiology; the American College of Cardiology Foundation; and the Heart Rhythm Society: endorsed by the International Society for Computerized Electrocardiology. Circulation. 2009;119:e241-e250.
Baranchuk A, Nguyen T, Ryu MH, et al. Brugada phenocopy: new terminology and proposed classification. Ann Noninvasive Electrocardiol. 2012;17(4):299-314.
Bussink BE, Holst AG, Jespersen L, Deckers JW, Jensen GB, Prescott E. Right bundle branch block: prevalence, risk factors, and outcome in the general population: results from the Copenhagen City Heart Study. Eur Heart J. 2013;34(2):138-146.
Chevallier S, Forclaz A, Tenkorang J, et al. New electrocardiographic criteria for discriminating between Brugada types 2 and 3 patterns and incomplete right bundle branch block. J Am Coll Cardiol. 2011;58(22):2290-2298.
Liao Y, Emidy LA, Dyer A, et al. Characteristics and prognosis of incomplete right bundle branch block: an epidemiologic study. J Am Coll Cardiol. 1986;7(3):492-499.
Pecini R, Cedergreen P, Theilade S, Haunsø S, Theilade J, Jensen GB. The prevalence and relevance of the Brugada-type electrocardiogram in the Danish general population: data from the Copenhagen City Heart Study. Europace. 2010;12:982-986.
Nishizaki M, Sugi K, Izumida N, Kamakura S. Classification and assessment of computerized diagnostic criteria for Brugada-type electrocardiograms. Hear Rhythm. 2010;7(11):1660-1666.
Baranchuk A, Enriquez A, García-Niebla J, Bayés-Genís A, Villuendas R, Bayés De Luna A. Differential diagnosis of rSr′ pattern in leads V1-V2. comprehensive review and proposed algorithm. Ann Noninvasive Electrocardiol. 2015;20(1):7-17.
Antzelevitch C. Molecular biology and cellular mechanisms of Brugada and long QT syndromes in infants and young children. J Electrocardiol. 2001;34:177-181.
Hermida JS, Lemoine JL, Aoun FB, Jarry G, Rey JL, Quiret JC. Prevalence of the Brugada syndrome in an apparently healthy population. Am J Cardiol. 2000;86(1):91-94.
Shahrzad S, Khoramshahi M, Aslani A, Fazelifar AF, Haghjoo M. Clinical and electrocardiographic predictors of positive response to the intravenous sodium channel blockers in patients suspected of the Brugada syndrome. Int J Cardiol. 2013;165(2):285-290.

Auteurs

Mafalda Carrington (M)

Cardiology Department, Hospital do Espírito Santo de Évora, Évora, Portugal.

Antonio Creta (A)

Cardiology Department, Barts Heart Centre, Barts Health NHS Trust, London, UK.

William J Young (WJ)

Cardiology Department, Barts Heart Centre, Barts Health NHS Trust, London, UK.
William Harvey Research Institute, Queen Mary University of London, London, UK.

Maria Carrington (M)

IE Business School, Madrid, Spain.

Jorge Henriques (J)

Department of Computer Science and Engineering, Centro de Informática e Sistemas, Universidade de Coimbra, Coimbra, Portugal.

Rogério Teixeira (R)

Cardiology Department, Centro Hospitalar Universitário de Coimbra, Coimbra, Portugal.
Faculdade de Medicina, Universidade de Coimbra, Coimbra, Portugal.

Lino Gonçalves (L)

Cardiology Department, Centro Hospitalar Universitário de Coimbra, Coimbra, Portugal.
Faculdade de Medicina, Universidade de Coimbra, Coimbra, Portugal.

Pier D Lambiase (PD)

Cardiology Department, Barts Heart Centre, Barts Health NHS Trust, London, UK.

Rui Providência (R)

Cardiology Department, Barts Heart Centre, Barts Health NHS Trust, London, UK.
Institute of Health Informatics Research, University College London, London, UK.

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