Assessing and Comparing Multiple Metrics of Heart Rate Variability to Measure Cardiac Parasympathetic and Sympathetic Tone – Does the Math Miss a Beat?

Abstract

The relative contributions of parasympathetic and sympathetic autonomic nervous system control of cardiac activity is often assessed through non-invasive heart rate variability (HRV) metrics. There are various HRV metrics utilized to measure cardiac autonomic balance. However, the relationship between HRV metrics and cardiac autonomic tone is understudied and controversial. We assessed the internal consistency of using three specific HRV metrics of cardiac autonomic balance at rest using electrocardiography (ECG) in a larger number of healthy participants: time domain, frequency domain and Poincaré plots. Data was analyzed from a large set (n=136) of archived files from previous studies, where a 5-min segment of resting baseline ECG was previously-recorded in young, healthy men and women (ADInstruments, LabChart HRV module, v8). The three specific HRV metrics quantified from the ECG baseline were time domain (SDRR and RMSSD; ms), frequency domain (LF, HF, LF/HF; n.u.) and Poincaré plots (SD1, SD2, SD1/SD2; ms). The HRV metrics considered to be associated with cardiac parasympathetic activity are RMSSD, HF and SD1, whereas SDRR, LF and SD2 are considered to be associated with mixed cardiac parasympathetic and sympathetic activity (i.e., sympathetic influence). We correlated the three parasympathetic HVR metrics (RMSSD, HF and SD1), within-individual. We also correlated the three mixed cardiac autonomic metrics (SDRR, LF and SD2), within-individual. Regarding the three parasympathetic metrics, (a) RMSSD and SD1 were strongly, positively and significantly-correlated (r=1.0, P<0.0001), suggesting similar mathematical calculations for each and (b) both RMSSD and HF, and SD1 and HF were moderately, positively and significantly-correlated (both, rs=0.41, P<0.00001). Regarding mixed parasympathetic and sympathetic metrics, (a) SDRR and SD2 were strongly, positively and significantly-correlated (r=0.96, P<0.0001), suggesting similar mathematical calculations for each, (b) SDRR and LF were not significantly-correlated (rs=-0.1, P=0.25) and (c) SD2 and LF were no significantly correlated (rs=0.01, P=0.9). Our analysis on a large data set suggests high agreement and internal consistency between parasympathetic cardiac metrics, within-individual. However, on metrics with mixed parasympathetic and sympathetic influence, HRV metrics lacked agreement and internal consistently. These data suggest that (a) any of the three parasympathetic metrics are likely useful in assessing cardiac parasympathetic tone, but that (b) caution should be used in interpreting HRV metrics typically utilized in assessing cardiac sympathetic tone.