Automatically optimized vectorcardiographic features are associated with recurrence of atrial fibrillation after electrical cardioversion

自动优化的向量心电图特征与电复律后房颤复发相关。

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Abstract

Electrical cardioversion presents one of the treatment options for atrial fibrillation (AF). However, the early recurrence rate is high, reaching ~40% three months after the procedure. Features based on vectorcardiographic signals were explored to find association with early recurrence of AF. Eighty-four patients with non-paroxysmal AF referred to electrical cardioversion were prospectively studied; early AF recurrence was present in 40 (47.6%). Patients underwent 24-h Holter ECG monitoring three months after the procedure to assess AF recurrence. Pre-procedural 12-lead ECGs (10 s, 1 kHz) were recorded and automatically analyzed. We explored associations of VCG-based features with early AF recurrence. Two features were strongly associated with AF recurrence: (1) a mean VCG (y-axis) signal slope in a window starting 145 ms before QRS center, lasting for 190 ms (AUC 0.778, p < 0.001), and (2) a mean VCG (z-axis) signal slope in a window starting 60 ms after QRS center, lasting for 465 ms (AUC 0.744, p < 0.001). These features showed higher association to the outcome than eighteen baseline clinical features. Our approach revealed features based on a slope of vectorcardiographic signals. This work also suggests that state of ventricles strongly affects the AF recurrence after electrical cardioversion.

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