Assessing baroreflex gain from spontaneous variability in conscious dogs: role of causality and respiration.

A double exogenous autoregressive (XXAR) causal parametric model was used to estimate the baroreflex gain (alpha(XXAR)) from spontaneous R-R interval and systolic arterial pressure (SAP) variabilities in conscious dogs. This model takes into account 1) effects of current and past SAP variations on the R-R interval (i.e., baroreflex-mediated influences), 2) specific perturbations affecting R-R interval independently of baroreflex circuit (e.g., rhythmic neural inputs modulating R-R interval independently of SAP at frequencies slower than respiration), and 3) influences of respiration-related sources acting independently of baroreflex pathway (e.g., rhythmic neural inputs modulating R-R interval independently of SAP at respiratory rate, including the effect of stimulation of low-pressure receptors). Under control conditions, alpha(XXAR) = 14.7 +/- 7.2 ms/mmHg. It decreases after nitroglycerine infusion and coronary artery occlusion, even though the decrease is significant only after nitroglycerine, and it is completely abolished by total arterial baroreceptor denervation. Moreover, alpha(XXAR) is comparable to or significantly smaller than (depending on the experimental condition) the baroreflex gains derived from sequence, power spectrum [at low frequency (LF) and high frequency (HF)], and cross-spectrum (at LF and HF) analyses and from less complex causal parametric models, thus demonstrating that simpler estimates may be biased by the contemporaneous presence of regulatory mechanisms other than baroreflex mechanisms.

[1]  J. Bigger,et al.  Baroreflex sensitivity and heart-rate variability in prediction of total cardiac mortality after myocardial infarction , 1998, The Lancet.

[2]  J Strackee,et al.  Hemodynamic fluctuations and baroreflex sensitivity in humans: a beat-to-beat model. , 1987, The American journal of physiology.

[3]  R. Cohen,et al.  Power spectrum analysis of heart rate fluctuation: a quantitative probe of beat-to-beat cardiovascular control. , 1981, Science.

[4]  F Iellamo,et al.  Investigating feed-forward neural regulation of circulation from analysis of spontaneous arterial pressure and heart rate fluctuations. , 1999, Circulation.

[5]  G. Breithardt,et al.  Heart rate variability: standards of measurement, physiological interpretation and clinical use. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. , 1996 .

[6]  A. Malliani,et al.  Cardiovascular variability signals: towards the identification of a closed-loop model of the neural control mechanisms , 1988, IEEE Transactions on Biomedical Engineering.

[7]  H. Akaike A new look at the statistical model identification , 1974 .

[8]  S. Vatner,et al.  Bainbridge reflex in conscious, unrestrained, and tranquilized baboons. , 1981, The American journal of physiology.

[9]  R. Cohen,et al.  Hemodynamic regulation: investigation by spectral analysis. , 1985, The American journal of physiology.

[10]  P. Reddy,et al.  Respiratory sinus arrhythmia in the denervated human heart. , 1989, Journal of applied physiology.

[11]  M. Turiel,et al.  Power Spectral Analysis of Heart Rate and Arterial Pressure Variabilities as a Marker of Sympatho‐Vagal Interaction in Man and Conscious Dog , 1986, Circulation research.

[12]  L. Zetterberg Estimation of parameters for a linear difference equation with application to EEG analysis , 1969 .

[13]  A Pedotti,et al.  A new approach to analysis of the arterial baroreflex. , 1985, Journal of hypertension. Supplement : official journal of the International Society of Hypertension.

[14]  J C Collins,et al.  Modeling of arterial and cardiopulmonary baroreflex control of heart rate. , 1997, The American journal of physiology.

[15]  Lennart Ljung,et al.  Identification of processes in closed loop - identifiability and accuracy aspects , 1977, Autom..

[16]  A. Malliani,et al.  Changes in Autonomic Regulation Induced by Physical Training in Mild Hypertension , 1988, Hypertension.

[17]  H. Robbe,et al.  Assessment of baroreceptor reflex sensitivity by means of spectral analysis. , 1987, Hypertension.

[18]  Giuseppe Baselli,et al.  Models for the analysis of cardiovascular variability signals , 1995 .

[19]  A. Malliani,et al.  Heart rate variability. Standards of measurement, physiological interpretation, and clinical use , 1996 .

[20]  G. Pickering,et al.  Reflex Regulation of Arterial Pressure during Sleep in Man: A Quantitative Method of Assessing Baroreflex Sensitivity , 1969, Circulation research.

[21]  L E Lamb,et al.  Effects of lower body negative pressure on the cardiovascular system. , 1965, The American journal of cardiology.

[22]  J. Hirsch,et al.  Respiratory sinus arrhythmia in humans: how breathing pattern modulates heart rate. , 1981, The American journal of physiology.

[23]  D L Eckberg,et al.  Fundamental relations between short-term RR interval and arterial pressure oscillations in humans. , 1996, Circulation.

[24]  S Cerutti,et al.  Spectral and cross-spectral analysis of heart rate and arterial blood pressure variability signals. , 1986, Computers and biomedical research, an international journal.

[25]  Soederstroem ON THE CONVERGENCE PROPERTIES OF THE GENERALIZED LEAST SQUARES IDENTIFICATION METHOD. , 1972 .

[26]  G. Baselli,et al.  Spectral decomposition in multichannel recordings based on multivariate parametric identification , 1997, IEEE Transactions on Biomedical Engineering.

[27]  S Cerutti,et al.  Analysis of short-term oscillations of R-R and arterial pressure in conscious dogs. , 1990, The American journal of physiology.

[28]  G. Preiss,et al.  Patterns of sympathetic neuron activity associated with Mayer waves. , 1974, The American journal of physiology.