Cogliati, Chiara

Spectral analysis of skin blood flow has demonstrated low-frequency (LF, 0.03–0.15 Hz) and high-frequency (HF, 0.15–0.40 Hz) oscillations, similar to oscillations in R-R interval, systolic pressure, and muscle sympathetic nerve activity (MSNA). It is not known whether the oscillatory profile of skin blood flow is secondary to oscillations in arterial pressure or to oscillations in skin sympathetic nerve activity (SSNA). MSNA and SSNA differ markedly with regard to control mechanisms and morphology. MSNA contains vasoconstrictor fibers directed to muscle vasculature, closely regulated by baroreceptors. SSNA contains both vasomotor and sudomotor fibers, differentially responding to arousals and thermal stimuli. Nevertheless, MSNA and SSNA share certain common characteristics. We tested the hypothesis that LF and HF oscillatory components are evident in SSNA, similar to the oscillatory components present in MSNA. We studied 18 healthy normal subjects and obtained sequential measurements of MSNA and SSNA from the peroneal nerve during supine rest. Measurements were also obtained of the electrocardiogram, beat-by-beat blood pressure (Finapres), and respiration. Spectral analysis showed LF and HF oscillations in MSNA, coherent with similar oscillations in both R-R interval and systolic pressure. The HF oscillation of MSNA was coherent with respiration. Similarly, LF and HF spectral components were evident in SSNA variability, coherent with corresponding variability components of R-R interval and systolic pressure. HF oscillations of SSNA were coherent with respiration. Thus our data suggest that these oscillations may be fundamental characteristics shared by MSNA and SSNA, possibly reflecting common central mechanisms regulating sympathetic outflows subserving different regions and functions.

Background— Sympathetic and parasympathetic systems are considered the principal rapidly reacting systems that control heart rate. Methods and Results— We propose a symbolic analysis series to quantify the prevalence of sympathetic or parasympathetic cardiac modulation. This analysis decomposes the heart rate variability series in patterns lasting 3 beats and classifies them into 3 categories: nonvariable, variable, and very variable patterns referred to as 0V, 1V, and 2V patterns. First, we applied this method to experimental and pharmacological conditions characterized by sympathetic activation (tilt test, handgrip, nitroprusside, and high-dose atropine administration) or parasympathetic activation (phenylephrine and low-dose atropine administration) in 60 healthy subjects. An increase in sympathetic modulation and a vagal withdrawal elicited a significant increase in 0V patterns and a decrease in 2V patterns, whereas parasympathetic dominance induced the opposite, reflecting a reciprocal sympathovagal balance. The second part of the study considered a series of 300 beats before the onset of major arrhythmic events in patients with an implantable cardioverter-defibrillator. Symbolic analysis detected an increase in the percentage of 0V patterns before the onset of major arrhythmias compared with baseline (41.6±3.9% and 24.4±2.9%, respectively; P <0.01), indicating a sympathetic prevalence. On the other hand, the 2V patterns did not decrease before major arrhythmias, suggesting the presence of nonreciprocal autonomic modulations. Conclusions— Symbolic analysis of 3 beat sequences takes into account the different time course of sympathetic and parasympathetic cardiac modulations and seems appropriate for elucidating the neural pathophysiological mechanisms occurring during the short periods that precede acute cardiac events.