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Pacing Clin Electrophysiol ; 26(10): 1955-60, 2003 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-14516335

RESUMO

Treatment of arrhythmogenic right ventricular dysplasia (ARVD) is mostly based on the prevention of sudden cardiac death that results from arrhythmias. A clinical history suggestive of ARVD requires careful evaluation including electrophysiological study. The potential ability to identify those patients who will have inducible VT with electrophysiological study will enable better risk stratification and selection of vulnerable patients for electrophysiologically guided therapy. The purpose of the study was to evaluate the predictive ability of signal-averaged electrocardiography (SAECG) to predict inducibility of VT in patients with ARVD. The patient population consisted of 31 ARVD patients diagnosed with McKenna's criteria who underwent electrophysiological study. Electrophysiological study was considered positive if sustained monomorphic VT was induced. The sensitivity, specificity, and predictive accuracy of various SAECG criteria for inducibility of sustained monomorphic VT were also calculated. Twenty-one patients had inducible VT. The filtered QRS duration (fQRS), duration of signal <40 uV (LAS40), and root mean square voltage in the last 40 ms of QRS duration (RMS40) in ARVD patients induced versus noninduced were 122 +/- 21 and 103 +/- 8 ms (P=0.007), 45 +/- 20 and 28 +/- 14 ms (P=0.02), 19 +/- 19 and 32 +/- 22 uV (0.03), respectively. The ejection fractions were comparable in both groups. fQRS duration > or =110 ms had sensitivity of 91%, specificity of 90%, and a total predictive accuracy of 90% in predicting inducibility of VT in these patients. Filtered QRS duration on SAECG is predictive of electrophysiological study outcome in ARVD. Further studies will be needed to determine if SAECG results can predict the development of ventricular arrhythmias during follow-up.


Assuntos
Displasia Arritmogênica Ventricular Direita/fisiopatologia , Eletrocardiografia , Taquicardia Ventricular/fisiopatologia , Adulto , Distribuição de Qui-Quadrado , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Valor Preditivo dos Testes , Curva ROC , Processamento de Sinais Assistido por Computador , Estatísticas não Paramétricas
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