Autonomic control of heart rate is well known in adult subjects, but limited data are available on the development of the heart rate control during childhood and adolescence. Continuous 12-lead electrocardiograms were recorded in 1045 healthy children and adolescents (550 females) aged 4 to 19 years during postural manoeuvres involving repeated 10-min supine, unsupported sitting, and unsupported standing positions. In each position, heart rate was measured, and heart rate variability indices were evaluated (SDNN, RMSSD, and high (HF) and low (LF) frequency components were obtained). Quasi-normalized HF frequency components were defined as qnHF = HF/(HF + LF). These measurements were, among others, related to age using linear regressions. In supine position, heart rate decreases per year of age were significant in both sexes but lower in females than in males. In standing position, these decreases per year of age were substantially lowered. RMSSD and qnHF indices were independent of age in supine position but significantly decreased with age in sitting and standing positions. Correspondingly, LF/HF proportions showed steep increases with age in sitting and standing positions but not in the supine position. The study suggests that baseline supine parasympathetic influence shows little developmental changes during childhood and adolescence but that in young children, sympathetic branch is less responsive to vagal influence. While vagal influences modulate cardiac periods in young and older children equally, they are less able to suppress the sympathetic influence in younger children.

Background/Objective: The relationship between heart rate and heart rate variability (HRV) indices has been repeatedly studied in adults but limited data are available on the relationship in paediatric populations. Methods: Continuous 12-lead electrocardiograms were recorded in 1016 healthy children and adolescents (534 females) aged 4 to 19 years during postural manoeuvres with rapid changes between 10-min positions of supine → sitting → standing → supine → standing → sitting → supine. In each position, the averaged RR interval was measured together with four HRV indices, namely the SDNN, RMSSD, quasi-normalised high-frequency components (qnHF), and the proportions of low- and high-frequency components (LF/HF). In each subject, the slope of the linear regression between the repeated HRV measurements and the corresponding RR interval averages was calculated. Results: The intra-subject regression slopes, including their confidence intervals, were related to the age and sex of the subjects. The SDNN/RR, RMSSD/RR, and qnHF/RR slopes were significantly steeper (p < 0.001) and the (LF/HF)/RR slopes were significantly shallower (p < 0.001) in younger children compared to older children and adolescents. Conclusions: The study suggests that sympathetic and vagal influences on heart rate are present in both younger and older children. With advancing age, the sympatho-vagal balance gradually develops and allows the vagal control to suppress the sympathetic drive towards higher heart rates seen in younger age children.

QT interval variability, mostly expressed by QT variability index (QTVi), has repeatedly been used in risk diagnostics. Physiologic correlates of QT variability expressions have been little researched especially when measured in short 10-second electrocardiograms (ECGs). This study investigated different QT variability indices, including QTVi and the standard deviation of QT interval durations (SDQT) in 657,287 10-second ECGs recorded in 523 healthy subjects (259 females). The indices were related to the underlying heart rate and to the 10-second standard deviation of RR intervals (SDRR). The analyses showed that both QTVi and SDQT (as well as other QT variability indices) were highly statistically significantly (p < 0.00001) influenced by heart rate and that QTVi showed poor intra-subject reproducibility (coefficient of variance approaching 200%). Furthermore, sequential analysis of regression variance showed that SDQT was more strongly related to the underlying heart rate than to SDRR, and that QTVi was influenced by the underlying heart rate and SDRR more strongly than by SDQT (p < 0.00001 for these comparisons of regression dependency). The study concludes that instead of QTVi, simpler expressions of QT interval variability, such as SDQT, appear preferable for future applications especially if multivariable combination with the underlying heart rate is used.

Background/Objectives: One of the topics of electrocardiographic risk factor studies is investigations of beat-to-beat QT interval variability. The seminal study that reported QT variability as a prognostic risk factor introduced the so-called QT variability index (QTVi). QTVi quantification relies not only on the variance of QT intervals but also on correction factors, including RR interval variance, heart rate, and overall QT interval duration. This study investigated the influence of all the measured factors on QTVi values. Methods: Long-term electrocardiograms (ECGs) were obtained from 251 healthy subjects (mean age 33.6 ± 9.1 years, 108 females) during repeated postural tests that involved supine, sitting, and standing positions maintained for 10 or 15 min. During each position, a 5-min ECG segment with a stable heart rate and without any ectopic disturbances was found. In these segments, standard deviations of normal-to-normal RR (NN) interval durations (SDNN) and of beat-to-beat QT interval durations (SDQT) were measured together with the means of NN and QT intervals. QTVi was subsequently calculated. For each subject, results obtained during each postural position were averaged. Results: In multivariable regression models, evaluated separately in female and male sex-subgroups of the population, QTVi values were significantly dependent on SDQT, SDNN, and mean NN intervals (all p < 0.001) but practically independent of mean QT interval durations. Conclusions: QTVi is significantly influenced by factors that are unrelated to the beat-to-beat changes in QT interval durations. This needs to be considered when interpreting QTVi values. In future studies, multivariable statistical models are needed to ensure that QTVi findings are independent of associated heart rate variability indices.