Complexity of cardiovascular regulation in small animals

Aubert, André; Vandeput, Steven; Beckers, F.; Liu, Jiexin; Verheyden, Bart; Huffel, Sabine Van

doi:10.1098/rsta.2008.0276

Cited by 22 publications

(20 citation statements)

References 76 publications

(119 reference statements)

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“…She was a pioneer (Akselrod et al 1981) Within the set of contributions demonstrating the importance of quantification of cardiovascular complexity, Huikuri et al (2009) review the studies assessing complexity indices over heart period variability in humans and elucidate the physiological and clinical information that can be extracted from them. Aubert et al (2009) Within the set of contributions exploring the complexity of specific cardiovascular control mechanisms, Couderc (2009) reviews the mechanisms influencing the timing and the morphology of the T wave and affecting the relationship between heart period and ventricular repolarization duration, Di Rienzo et al (2009) deal with the time scales, nonlinearities and complexity of the baroreflex, i.e. the most important reflex mechanism for the maintenance of blood pressure homeostasis, and Panerai (2009) challenges the complexity of human cerebral regulation.…”

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confidence: 99%

Addressing the complexity of cardiovascular regulation

Porta

Rienzo

Wessel

et al. 2009

Phil. Trans. R. Soc. A.

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The cardiovascular system plays a key role in complex living organisms since it provides supplies for maintaining vital functions and, contemporaneously, gets rid of waste materials. It is formed by highly specialized subsystems that interact with each other to accomplish tasks (e.g. the optimization of arterial and pulmonary circulation) and even compete for resources as in, for example, the maintenance of the cerebral circulation during a massive haemorrhage. Subsystems have their own local regulatory mechanisms (e.g. mechanisms regulating blood flow in proximal microvascular districts) that interact with central neural commands reflecting the activity of the vasomotor and respiratory autonomous oscillators, with reflex neural commands occurring in response to changes in some controlled variables (e.g. arterial pressure) and with humoral factors. All these regulatory mechanisms act rhythmically, producing incessant adjustments in cardiovascular variables visible from beat-to-beat recordings. These variations are referred to as 'cardiovascular variability' and occur over a wide frequency range including very slow rhythms (e.g. ultradian periodicities) and oscillations even faster than heart rate. The magnitude of these variations depends on the gross amount of the activities of the autonomous central oscillators, on the resonance of the closed-loop mechanisms, on the gain of the relationship between variables and on the possibility that a network of distributed oscillators with negligible activities becomes entrained or remains sparse.The presence of multiple regulatory mechanisms contemporaneously active over different time scales and capable of varying over time the relationships among variables generates the dynamic complexity of cardiovascular variables. This complexity also depends on the presence of mechanisms favouring synchronization among the activities of subsystems according to n : m coupling ratios (i.e. n cycles of activity of one subsystem correspond to m cycles of the other), thus reducing dimensionality of the cardiovascular system, and on the amount of information exchanged among subsystems (i.e. on their degree of isolation).Current evidence suggests that the assessment of the complexity of cardiovascular regulation could provide important information about the underlying regulatory mechanisms. In particular, it has been shown that a modification of complexity indices, resulting from depressed organ function, a loss of interaction among subsystems, an overwhelming action of a subsystem over others and an impairment of regulatory mechanisms, is a clear hallmark of a pathological situation. Interestingly, since the complexity of cardiovascular regulation can be evaluated from variables that are routinely and non-invasively estimated during the most common medical examinations, this assessment does not require additional procedures and devices. On the contrary, it necessitates

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confidence: 99%

Addressing the complexity of cardiovascular regulation

Porta

Rienzo

Wessel

et al. 2009

Phil. Trans. R. Soc. A.

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“…All rats initially had ECG monitoring during 20 min (week 0) under ketamine anaesthesia (50 mg/kg, intraperitonealy) and were subsequently monitored in a similar way weekly for 5 weeks (weeks [1][2][3][4][5]. By the end of the third week, one rat died and the other rats presented signs of overt heart failure, namely lethargy, laboured breathing, cachexia, vein and liver engorgement, pleural effusion and ascites, as well as significant changes in linear and nonlinear HR indices [20].…”

Section: Animal Modelmentioning

confidence: 99%

“…Spectral analysis, in particular, allows the identification of two distinct peaks, linked to the activities of the two branches of the autonomic nervous system [41]. However, the application of these methods to animal studies, needs to be adapted to every situation [2], considering results heralded from previous research, that may be used as guidelines, although it should be noted that different experimental settings may lead to significant differences in HRV parameters.…”

Section: Introductionmentioning

confidence: 99%

“…Nonlinear methods have also been applied to HRV analysis [1,2]. The two main categories of these methods are: (i) indices that describe the scaling behaviour of a system; (ii) indices that describe the complexity of a system.…”

Section: Introductionmentioning

confidence: 99%

“…The analysis of a system in the phase space enables the assessment of its complexity. The correlation dimension indicates the dimension of the phase space, Lyapunov exponents provide the sensitivity of the system to initial conditions and approximate entropy (ApEn) is a measure of the system complexity [2].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Comparison of different methods of heart rate entropy analysis during acute anoxia superimposed on a chronic rat model of pulmonary hypertension

Gonçalves

Henriques‐Coelho

Rocha

et al. 2013

Medical Engineering & Physics

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a b s t r a c tAcute life-threatening situations are particularly critical when superimposed on chronic diseases. The objective of this study was the assessment of heart rate (HR) dynamics during episodes of acute anoxia superimposed on a rat model of chronic pulmonary hypertension. In 10 adult Wistar rats, five weeks after pulmonary hypertension induction with Monocrotaline, we analysed eight 1-min HR segments, during episodes of baseline, mechanical ventilation and acute anoxia, using linear indices, approximate entropy (ApEn), sample entropy (SampEn) and multiscale entropy (MSE). The transition from baseline or mechanical ventilation to early anoxia was identified through almost all indices, but SampEn(2,0.6) was the index that better identified all the transitions. MSE presented limited performance, possibly due to the non-stationary nature and short duration of the acute anoxia episodes. A systematic evaluation of all computed HR indices may help to identify which indices or combination of indices more adequately discriminates and monitors critical acute events superimposed on chronic clinical conditions.

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Monitoring of Autonomic Activity by Cardiovascular Variability: How to Measure?

Aubert¹,

Verheyden²

2019

Stress Challenges and Immunity in Space

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Complexity of cardiovascular regulation in small animals

Cited by 22 publications

References 76 publications

Addressing the complexity of cardiovascular regulation

Addressing the complexity of cardiovascular regulation

Comparison of different methods of heart rate entropy analysis during acute anoxia superimposed on a chronic rat model of pulmonary hypertension

Monitoring of Autonomic Activity by Cardiovascular Variability: How to Measure?

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