Heart rhythm · 2016
Systematic analysis of ECG predictors of sinus rhythm maintenance after electrical cardioversion for persistent atrial fibrillation.
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Lankveld Theo, de Vos Cees B, Limantoro Ione, Zeemering Stef, Dudink Elton, Crijns Harry J, Schotten Ulrich
Аннотация
BACKGROUND: Electrical cardioversion (ECV) is one of the rhythm control strategies in patients with persistent atrial fibrillation (AF). Unfortunately, recurrences of AF are common after ECV, which significantly limits the practical benefit of this treatment in patients with AF.
OBJECTIVES: The objectives of this study were to identify noninvasive complexity or frequency parameters obtained from the surface electrocardiogram (ECG) to predict sinus rhythm (SR) maintenance after ECV and to compare these ECG parameters with clinical predictors.
METHODS: We studied a wide variety of ECG-derived time- and frequency-domain AF complexity parameters in a prospective cohort of 502 patients with persistent AF referred for ECV.
RESULTS: During 1-year follow-up, 161 patients (32%) maintained SR. The best clinical predictor of SR maintenance was antiarrhythmic drug (AAD) treatment. A model including clinical parameters predicted SR maintenance with a mean cross-validated area under the receiver operating characteristic curve (AUC) of 0.62 ± 0.05. The best single ECG parameter was the dominant frequency (DF) on lead V6. Combining several ECG parameters predicted SR maintenance with a mean AUC of 0.64 ± 0.06. Combining clinical and ECG parameters improved prediction to a mean AUC of 0.67 ± 0.05. Although the DF was affected by AAD treatment, excluding patients taking AADs did not significantly lower the predictive performance captured by the ECG.
CONCLUSION: ECG-derived parameters predict SR maintenance during 1-year follow-up after ECV at least as good as known clinical predictors of rhythm outcome. The DF proved to be the most powerful ECG-derived predictor.
OBJECTIVES: The objectives of this study were to identify noninvasive complexity or frequency parameters obtained from the surface electrocardiogram (ECG) to predict sinus rhythm (SR) maintenance after ECV and to compare these ECG parameters with clinical predictors.
METHODS: We studied a wide variety of ECG-derived time- and frequency-domain AF complexity parameters in a prospective cohort of 502 patients with persistent AF referred for ECV.
RESULTS: During 1-year follow-up, 161 patients (32%) maintained SR. The best clinical predictor of SR maintenance was antiarrhythmic drug (AAD) treatment. A model including clinical parameters predicted SR maintenance with a mean cross-validated area under the receiver operating characteristic curve (AUC) of 0.62 ± 0.05. The best single ECG parameter was the dominant frequency (DF) on lead V6. Combining several ECG parameters predicted SR maintenance with a mean AUC of 0.64 ± 0.06. Combining clinical and ECG parameters improved prediction to a mean AUC of 0.67 ± 0.05. Although the DF was affected by AAD treatment, excluding patients taking AADs did not significantly lower the predictive performance captured by the ECG.
CONCLUSION: ECG-derived parameters predict SR maintenance during 1-year follow-up after ECV at least as good as known clinical predictors of rhythm outcome. The DF proved to be the most powerful ECG-derived predictor.