We recently proposed a Sympathetic Activity Index (SAI) based on an orthonormal Laguerre expansion of linear RR-interval autoregressive kernels. The resulting heart rate variability (HRV) series analysis may be used for the effective estimation of cardiac sympathetic outflow because the underlying model is independent from the overlapping dynamics of the sympathetic and vagus nerves in the low frequency (LF) band (0.04-0.15Hz). In this study, we perform a preliminary validation of the HRV-based SAI performance through concurrent estimates from efferent muscle sympathetic nerve activity (MSNA) recordings.
Methods: ECG and multiunit efferent postganglionic MSNA were simultaneously recorded in 12 hypertensive patients in the supine position during a 10min resting state and up to 30min sodium nitroprusside (SNP; 0.4 μg/kg per minute) administration. SNP is a direct vasodilating agent, thus expected to increase MSNA. The SAI index is estimated from the R-waves from ECG using a set of disentangling coefficients from a previous autonomic blockade study. Group-wise comparisons between sessions were performed through Wilcoxon non-parametric tests for paired data, and a combined SAI- MSNA correlation analysis was performed through Spearman coefficient.
Results: Results show a characteristic increase of the MSNA during SNP intake with respect to the resting state (MSNA-Rest: 39 ± 4.5, MSNA-SNP: 54.3 ± 5 bursts per 100 heartbeats; p< 0.001). While SAI was associatedwithasignificantSAIincreaseduringSNP(SAI-Rest: 39.07±13.46;SAI-SNP:52.66±17.76; p< 0.001), LF power did not show significant changes between sessions (SAI-Rest: 61.9 ± 36.24 [ms2]; LF-SNP: 63.45 ± 49.62 [ms2]; p<0.05). Spearman analysis highlights a significant correlation between SAI and MSNA (r=0.475; p<0.02) and a non-significant correlation between LF power and MSNA (r=-0.089; p>0.05).
Conclusions: The presented results provide a further validation step of a novel non-invasive technique for estimating autonomic cardiovascular control dynamics, and they support the use of HRV-based SAI metrics as a reliable proxy of cardiac sympathetic outflow dynamics.