Signal-averaged electrocardiographic late potentials in children with complete heart block

Identification of ventricular late potentials in the surface electrocardiogram during atrial, atrioventricular sequential, or single-chamber ventricular pacing

Sudden cardiac death occurs in up to 30% of patients with cardiac pacemakers, caused by ventricular arrhythmias, but in these patients noninvasive risk stratification with Holter, exercise, or standard signal-averaged electrocardiogram is limited. This study investigated whether late potential analysis during cardiac pacing is applicable. In 50 postinfarction patients with documented sustained ventricular tachycardia (VT) and in 50 patients without VT, late potential analysis during sinus rhythm was compared with the corresponding patient's analysis during temporary pacing. During sinus rhythm late potentials were seen in 48 of 50 patients with VT and in 2 of 50 patients without VT. No significant changes were observed during atrial pacing. Modified QRS alignment for signal averaging, QRS endpoint definition, and adjusted cutoff values for abnormality in time and frequency domain analysis allowed retrieval of all late potentials observed during sinus rhythm even in ventricular-paced beats and retrograde conduction. By application of an adjusted analysis to 100 selected patients with permanent pacemakers (50 patients with a history of VT, 50 patients without VT) late potentials were detectable in 44 of 50 patients with VT and in 4 of 50 without VT (sensitivity 88%, specificity 92%). Thus, considering that varying pacing modes, ventricular-paced beats, and retrograde conduction do require modifications of standard late potential analysis, this is an applicable mode for noninvasive risk stratification even in patients with cardiac pacemakers.

Signal-averaged electrocardiography in healthy children: relationship with age, sex, and anthropometry

Signal-averaged electrocardiograms (SAECGs) have been found to be influenced by sex and anthropometry in adults. The purpose of this study was to evaluate this relationship in children. Total filtered QRS duration (TQRS), duration of high-frequency, low-amplitude signals in the terminal portion of the QRS complex that were less than 40 microV (HFLA) root-mean-square voltage in the last 40 ms of the filtered QRS (RMS40) were determined by high-resolution electrocardiographic (ECG) recording (MAC 15 ECG System, Marquette Electronics, Milwaukee, WI). These parameters were correlated with age, sex, body weight, height, relative weight, body mass index, and body surface area. As HFLA and RMS40 were not normally distributed, they were logarithmically transformed for regression analysis. The best subset multiple regression procedure was used to evaluate the variables that would optimally influence SAECG measurements and to obtain regression equations for the prediction of each SAECG parameter. Although univariate analysis shows that almost all the body characteristics and age are significantly correlated with SAECGs, multiple regression analysis reveals that TQRS is significantly influenced by height (P < .0001), relative weight (P = .012), and body mass index (P = .041); HFLA is influenced by weight (P = .001), height (P = .004), and body mass index (P = .001); and RMS40 is influenced by height (P < .0001) and relative weight (P = .001). Sex is noted to significantly influence both TQRS and RMS40 (P < .0001, P = .002, respectively), while HFLA is found to be significantly related to age (P = .001). In summary, SAECGs in Chinese children are shown to be influenced by height, weight, and relative weight or body mass index, but not body surface area, while age and sex also significantly contribute to the variation of some SAECG parameters.