Literature DB >> 17982013

Estimation of the total peripheral resistance baroreflex impulse response from spontaneous hemodynamic variability.

Xiaoxiao Chen1, Jong-Kyung Kim, Javier A Sala-Mercado, Robert L Hammond, Rafat I Elahi, Tadeusz J Scislo, Gokul Swamy, Donal S O'Leary, Ramakrishna Mukkamala.   

Abstract

We previously developed a mathematical analysis technique for estimating the static gain values of the arterial total peripheral resistance (TPR) baroreflex (G(A)) and the cardiopulmonary TPR baroreflex (G(C)) from small, spontaneous beat-to-beat fluctuations in arterial blood pressure, cardiac output, and stroke volume. Here, we extended the mathematical analysis so as to also estimate the entire arterial TPR baroreflex impulse response [h(A)(t)] as well as the lumped arterial compliance (AC). The extended technique may therefore provide a linear dynamic characterization of TPR baroreflex systems during normal physiological conditions from potentially noninvasive measurements. We theoretically evaluated the technique with respect to realistic spontaneous hemodynamic variability generated by a cardiovascular simulator with known system properties. Our results showed that the technique reliably estimated h(A)(t) [error = 30.2 +/- 2.6% for the square root of energy (E(A)), 19.7 +/- 1.6% for absolute peak amplitude (P(A)), 37.3 +/- 2.5% for G(A), and 33.1 +/- 4.9% for the overall time constant] and AC (error = 17.6 +/- 4.2%) under various simulator parameter values and reliably tracked changes in G(C). We also experimentally evaluated the technique with respect to spontaneous hemodynamic variability measured from seven conscious dogs before and after chronic arterial baroreceptor denervation. Our results showed that the technique correctly predicted the abolishment of h(A)(t) [E(A) = 1.0 +/- 0.2 to 0.3 +/- 0.1, P(A) = 0.3 +/- 0.1 to 0.1 +/- 0.0 s(-1), and G(A) = -2.1 +/- 0.6 to 0.3 +/- 0.2 (P < 0.05)] and the enhancement of G(C) [-0.7 +/- 0.44 to -1.8 +/- 0.2 (P < 0.05)] following the chronic intervention. Moreover, the technique yielded estimates whose values were consistent with those reported with more invasive and/or experimentally difficult methods.

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Year:  2007        PMID: 17982013     DOI: 10.1152/ajpheart.00852.2007

Source DB:  PubMed          Journal:  Am J Physiol Heart Circ Physiol        ISSN: 0363-6135            Impact factor:   4.733


  2 in total

1.  Modelling and disentangling physiological mechanisms: linear and nonlinear identification techniques for analysis of cardiovascular regulation.

Authors:  Jerry Batzel; Giuseppe Baselli; Ramakrishna Mukkamala; Ki H Chon
Journal:  Philos Trans A Math Phys Eng Sci       Date:  2009-04-13       Impact factor: 4.226

2.  CVSim: An Open-Source Cardiovascular Simulator for Teaching and Research.

Authors:  Thomas Heldt; Ramakrishna Mukkamala; George B Moody; Roger G Mark
Journal:  Open Pacing Electrophysiol Ther J       Date:  2010
  2 in total

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