Alberto Porta

Power spectrum analysis of heart rate variability to assess the changes in sympathovagal balance during graded orthostatic tilt.

BACKGROUND The powers of the low-frequency (LF) and high-frequency (HF) oscillations characterizing heart rate variability (HRV) appear to reflect, in their reciprocal relationship, changes in the state of the sympathovagal balance occurring during numerous physiological and pathophysiological conditions. However, no adequate information is available on the quantitative resolution of this methodology. METHODS AND RESULTS We studied 22 healthy volunteers (median age, 46.5 years) who were subjected after a rest period to a series of passive head-up tilt steps randomly chosen from the following angles: 15 degrees, 30 degrees, 45 degrees, 60 degrees, and 90 degrees. From the continuous ECG, after appropriate analog-to-digital conversion, a personal computer was used to compute, with an autoregressive methodology, time and frequency domain indexes of RR interval variability. Spectral and cross-spectral analysis with the simultaneously recorded respiratory signal excluded its contribution to LF. Age was significantly correlated to variance and to the absolute values in milliseconds squared of very-low-frequency (VLF), LF, and HF components. The tilt angle was correlated to both LF and HF (expressed in normalized units [nu]) and to the LF-to-HF ratio (r = .78, -.72, and .68; respectively). Lower levels of correlation were found with HF (in ms2) and RR interval. No correlation was present between tilt angle and variance, VLF, or LF (in ms2). Individual analysis confirmed that the use of nu provided the greatest consistency of results. CONCLUSIONS Spectral analysis of HRV, using nu or LF-to-HF ratio, appears to be capable of providing a noninvasive quantitative evaluation of graded changes in the state of the sympathovagal balance.

Relationship Between Spectral Components of Cardiovascular Variabilities and Direct Measures of Muscle Sympathetic Nerve Activity in Humans

BACKGROUND Spectral analysis of RR interval and systolic arterial pressure variabilities may provide indirect markers of the balance between sympathetic and vagal cardiovascular control. METHODS AND RESULTS We examined the relationship between power spectral measurements of variabilities in RR interval, systolic arterial pressure, and muscle sympathetic nerve activity (MSNA) obtained by microneurography over a range of blood pressures. In eight healthy human volunteers, MSNA, RR interval, intra-arterial pressure, and respiration were measured during blood pressure reductions induced by nitroprusside and during blood pressure increases induced by phenylephrine. Both low-frequency (LF; 0.10 +/- 0.01 Hz) and high-frequency (HF; 0.23 +/- 0.01 Hz) components were detected in MSNA variability. Increasing levels of MSNA were associated with a shift of the spectral power toward its LF component. Decreasing levels of MSNA were associated with a shift of MSNA spectral power toward the HF component. Over the range of pressure changes, the LF component of MSNA variability was positively and tightly correlated with LF components of RR interval (in normalized units; P < 10(-6)) and of systolic arterial pressure variability (both in millimeters of mercury squared and normalized units; P < 5 x 10(-5) and P < 5 x 10(-6), respectively). The HF component of MSNA variability was positively and tightly correlated with the HF component (in normalized units) of RR-interval variability (P < 3 x 10(-4)) and of systolic arterial pressure variability (P < .01). CONCLUSIONS During sympathetic activation in normal humans, there is a predominance in the LF oscillation of blood pressure, RR interval, and sympathetic nerve activity. During sympathetic inhibition, the HF component of cardiovascular variability predominates. This relationship is best seen when power spectral components are normalized for total power. Synchronous changes in the LF and HF rhythms of both RR interval and MSNA during different levels of sympathetic drive are suggestive of common central mechanisms governing both parasympathetic and sympathetic cardiovascular modulation.

Entropy, entropy rate, and pattern classification as tools to typify complexity in short heart period variability series

An integrated approach to the complexity analysis of short heart period variability series (/spl sim/300 cardiac beats) is proposed and applied to healthy subjects during the sympathetic activation induced by head-up tilt and during the driving action produced by controlled respiration (10, 15, and 20 breaths/min, CR10, CR15, and CR20 respectively). The approach relies on: 1) the calculation of Shannon entropy (SE) of the distribution of patterns lasting three beats; 2) the calculation of a regularity index based on an entropy rate (i.e., the conditional entropy); 3) the classification of frequent deterministic patterns (FDPs) lasting three beats. A redundancy reduction criterion is proposed to group FDPs in four categories according to the number and type or of heart period changes: a) no variation (0V); b) one variation (1V); and c) two like variations (2LV); 4) two unlike variations (2UV). The authors found that: 1) the SE decreased during tilt due to the increased percentage of missing patterns; 2) the regularity index increased during tilt and CR10 as patterns followed each other according to a more repetitive scheme; and 3) during CR10, SE and regularity index were not redundant as the regularity index significantly decreased while SE remained unchanged. Concerning pattern analysis the authors found that: a) at rest mainly three classes (0V, 1V, and 2LV) were detected; b) 0V patterns were more likely during tilt; c) 1V and 2LV patterns were more frequent during CR10; and d) 2UV patterns were more likely during CR20. The proposed approach based on quantification of complexity allows a full characterization of heart period dynamics and the identification of experimental conditions known to differently perturb cardiovascular regulation.

Oscillatory Patterns in Sympathetic Neural Discharge and Cardiovascular Variables During Orthostatic Stimulus

BACKGROUND We tested the hypothesis that a common oscillatory pattern might characterize the rhythmic discharge of muscle sympathetic nerve activity (MSNA) and the spontaneous variability of heart rate and systolic arterial pressure (SAP) during a physiological increase of sympathetic activity induced by the head-up tilt maneuver. METHODS AND RESULTS Ten healthy subjects underwent continuous recordings of ECG, intra-arterial pressure, respiratory activity, central venous pressure, and MSNA, both in the recumbent position and during 75 degrees head-up tilt. Venous samplings for catecholamine assessment were obtained at rest and during the fifth minute of tilt. Spectrum and cross-spectrum analyses of R-R interval, SAP, and MSNA variabilities and of respiratory activity provided the low (LF, 0.1 Hz) and high frequency (HF, 0.27 Hz) rhythmic components of each signal and assessed their linear relationships. Compared with the recumbent position, tilt reduced central venous pressure, but blood pressure was unchanged. Heart rate, MSNA, and plasma epinephrine and norepinephrine levels increased, suggesting a marked enhancement of overall sympathetic activity. During tilt, LF(MSNA) increased compared with the level in the supine position; this mirrored similar changes observed in the LF components of R-R interval and SAP variabilities. The increase of LF(MSNA) was proportional to the amount of the sympathetic discharge. The coupling between LF components of MSNA and R-R interval and SAP variabilities was enhanced during tilt compared with rest. CONCLUSIONS During the sympathetic activation induced by tilt, a similar oscillatory pattern based on an increased LF rhythmicity characterized the spontaneous variability of neural sympathetic discharge, R-R interval, and arterial pressure.

Chronic orthostatic intolerance: a disorder with discordant cardiac and vascular sympathetic control.

BACKGROUND Chronic orthostatic intolerance (COI) is a debilitating autonomic condition in young adults. Its neurohumoral and hemodynamic profiles suggest possible alterations of postural sympathetic function and of baroreflex control of heart rate (HR). METHODS AND RESULTS In 16 COI patients and 16 healthy volunteers, intra-arterial blood pressure (BP), ECG, central venous pressure (CVP), and muscle sympathetic nerve activity (MSNA) were recorded at rest and during 75 degrees tilt. Spectral analysis of RR interval and systolic arterial pressure (SAP) variabilities provided indices of sympathovagal modulation of the sinoatrial node (ratio of low-frequency to high-frequency components, LF/HF) and of sympathetic vasomotor control (LFSAP). Baroreflex mechanisms were assessed (1) by the slope of the regression line obtained from changes of RR interval and MSNA evoked by pharmacologically induced alterations in BP and (2) by the index alpha, obtained from cross-spectral analysis of RR and SAP variabilities. At rest, HR, MSNA, LF/HF, and LFSAP were higher in COI patients, whereas BP and CVP were similar in the two groups. During tilt, BP did not change and CVP fell by the same extent in the 2 groups; the increase of HR and LF/HF was more pronounced in COI patients. Conversely, the increase of MSNA was lower in COI than in control subjects. Baroreflex sensitivity was similar in COI and control subjects at rest; tilt reduced alpha similarly in both groups. CONCLUSIONS COI is characterized by an overall enhancement of noradrenergic tone at rest and by a blunted postganglionic sympathetic response to standing, with a compensatory cardiac sympathetic overactivity. Baroreflex mechanisms maintain their functional responsiveness. These data suggest that in COI, the functional distribution of central sympathetic tone to the heart and vasculature is abnormal.

Heart rate variability explored in the frequency domain: a tool to investigate the link between heart and behavior.

The neural regulation of circulatory function is mainly effected through the interplay of the sympathetic and vagal outflows. This interaction can be explored by assessing cardiovascular rhythmicity with appropriate spectral methodologies. Spectral analysis of cardiovascular signal variability, and in particular of RR period (heart rate variability, HRV), is a widely used procedure to investigate autonomic cardiovascular control and/or target function impairment. The oscillatory pattern which characterizes the spectral profile of heart rate and arterial pressure short-term variability consists of two major components, at low (LF, 0.04-0.15Hz) and high (HF, synchronous with respiratory rate) frequency, respectively, related to vasomotor and respiratory activity. With this procedure the state of sympathovagal balance modulating sinus node pacemaker activity can be quantified in a variety of physiological and pathophysiological conditions. Changes in sympathovagal balance can be often detected in basal conditions, however a reduced responsiveness to an excitatory stimulus is the most common feature that characterizes numerous pathophysiological states. Moreover the attenuation of an oscillatory pattern or its impaired responsiveness to a given stimulus can also reflect an altered target function and thus can furnish interesting prognostic markers. The dynamic assessment of these autonomic changes may provide crucial diagnostic, therapeutic and prognostic information, not only in relation to cardiovascular, but also non-cardiovascular disease. As linear methodologies fail to provide significant information in conditions of extremely reduced variability (e.g. strenuous exercise, heart failure) and in presence of rapid and transients changes or coactivation of the two branches of autonomic nervous system, the development of new non-linear approaches seems to provide a new perspective in investigating neural control of cardiovascular system.

Symbolic Dynamics of Heart Rate Variability A Probe to Investigate Cardiac Autonomic Modulation

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.

Model for the assessment of heart period and arterial pressure variability interactions and of respiration influences

A model which assesses the closed-loop interaction between heart period (HP) and arterial pressure (AP) variabilities and the influence of respiration on both is applied to evaluate the sources of low frequency (LF∼0·1 Hz) and high frequency (HF, respiratory rate ∼0·25 Hz) in conscious dogs (n=18) and humans (n=5). A resonance of AP closed-loop regulation is found to amplify LF oscillations. In dogs, the resonance gain increases slightly during baroreceptor unloading (mild hypotension obtained with nitroglycerine (NTG) i.v. infusion, n=8) and coronary artery occlusion ((CAO), n=6), and it is abolished by ganglionic transmission blockade ((ARF), Arfonad i.v. infusion, n=3). In humans, this gain is considerably increased by passive tilt. Different, possibly central, sources of LF oscillations are also evaluated, finding a strong rhythmic modulation of HP during CAO. At HF, a direct respiratory arrhythmia is dominant in dogs at control, while it is considerably reduced during CAO. On the contrary, in humans, a strong influence of respiration on AP is shown which induces a reflex respiratory arrhythmia. An index of the gain of baroreceptive response, αcl, was decreased by NTG and CAO, and virtually abolished by chronic arterial baroreceptive denervation (TABD, n=4) and ARF.

Central Vagotonic Effects of Atropine Modulate Spectral Oscillations of Sympathetic Nerve Activity

BACKGROUND Low-dose atropine causes bradycardia either by acting on the sinoatrial node or by its effects on central muscarinic receptors increasing vagal activity. Any central muscarinic effects of high-dose atropine on RR interval are masked by peripheral muscarinic blockade at the sinoatrial node, which causes tachycardia. Effects of central parasympathetic activation on sympathetic activity are not known. METHODS AND RESULTS Using power spectral analysis of RR interval, intra-arterial blood pressure, respiration, and muscle sympathetic nerve activity (MSNA), we examined the effects of both low (2 microgram/kg IV) and high (15 microgram/kg IV) doses of atropine. After low-dose atropine, RR increased by 9+/-1% (P<0.0001), the low-frequency (LF) component (in normalized units, NU) of RR variability decreased by -32+/-8%, and the high-frequency (HF)NU component increased (+74+/-19%); hence, LF/HF of RR variability fell by 52+/-10% (all P<0.01). Although overall MSNA did not change, LFNU of MSNA decreased (-15+/-5%), HFNU of MSNA increased (+31+/-3%), and LF/HF of MSNA fell (-41+/-8%) (all P<0.01). After high-dose atropine, LFNU of MSNA decreased (-17+/-12%), HFNU of MSNA increased (+22+/-3%), and LF/HF of MSNA fell (-51+/-21%) (all P<0.02). CONCLUSIONS Increasing central parasympathetic activity with low-dose atropine is associated with an increase in the HF and a decrease in the LF oscillations of both RR interval and MSNA variability. High-dose atropine similarly induces an increase in the HF and a decrease in the LF components of MSNA variability. Thus, central parasympathetic activation is able to modulate the oscillatory characteristics of sympathetic nerve traffic to peripheral blood vessels.

Spectral decomposition in multichannel recordings based on multivariate parametric identification

A method of spectral decomposition in multichannel recordings is proposed, which represents the results of multivariate (MV) parametric identification in terms of classification and quantification of different oscillating mechanisms. For this purpose, a class of MV dynamic adjustment (MDA) models in which a MV autoregressive (MAR) network of causal interactions is fed by uncorrelated autoregressive (AR) processes is defined. Poles relevant to the MAR network closed-loop interactions (cl-poles) and poles relevant to each AR input are disentangled and accordingly classified. The autospectrum of each channel can be divided into partial spectra each relevant to an input. Each partial spectrum is affected by the cl-poles and by the poles of the corresponding input; consequently, it is decomposed into the relevant components by means of the residual method. Therefore, different oscillating mechanisms, even at similar frequencies, are classified by different poles and quantified by the corresponding components. The structure of MDA models is quite flexible and can be adapted to various sets of available signals and a priori hypotheses about the existing interactions; a graphical layout is proposed that emphasizes the oscillation sources and the corresponding closed-loop interactions. Application examples relevant to cardiovascular variability are briefly illustrated.