Background: Heart rate variability (HRV) recorded over 5 min or 24 h is used increasingly to measure autonomic function and as a prognostic indicator in cardiology. Measuring HRV during a standard 10-s ECG would save time and cut costs. The aim of this study, therefore, was to discover whether indices of HRV calculated over 10 s could predict cardiac vagal tone (CVT) recorded over a 5-min period by the NeuroScope, a new instrument that selectively measures vagal tone.
Methods: A total of 50 subjects had ECGs taken at the beginning, middle and end of a 5-min measurement of CVT. Standard deviation of normal-to-normal RR interval (SDNN), root mean square of successive differences in RR intervals (rMSSD), and the average absolute difference (AAD) in RR intervals were calculated from RR intervals derived from the ECGs. Subjects were divided into a training set (n=40) and a test set (n=10).
Results: Regression equations derived from the training set predicted 5-min mean CVT in the test set with r(2) of 95.8%, 92.9% and 87.9% for AAD, rMSSD and SDNN, respectively. Indices obtained from the third ECG in each set tended to give a closer relationship with CVT than those derived from the first and second ECGs: this could be because of the greater spread of the independent variables in the third set. An underlying linear physiological phenomenon could not be excluded, however, without continuing the measurements over a longer time.
Conclusions: These results demonstrate that AAD and rMSSD calculated from a 10-s ECG can accurately predict 5-min mean CVT as measured by the NeuroScope.