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

Abstract

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 μV (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.