Ebook: Methodology and Clinical Applications of Blood Pressure and Heart Rate Analysis
This is the fourth book in a series dealing with the methodological aspects of computer analysis of blood pressure and heart rate variability, and with the pathophysiological and clinical relevance of the information derivable from this approach. The book describes new technical developments in estimating spontaneous baroreflex sensitivity from blood pressure and heart rate beat by-beat signals and illustrates the possible diagnostic and prognostic value of the assessment of the spontaneous baroreflex function in daily-life. The latest methodological advancements in the assessment of blood pressure and heart rate variability through linear and non-linear techniques, descriptors of chaotic dynamics and time-frequency distributions are also addressed. Finally, the book focuses on the neural and non-neural physiological mechanisms responsible for blood pressure and heart rate variability and on the alterations in variability induced by the derangement of these mechanisms in case of cardiovascular or systemic diseases. The result is a comprehensive overview of the most recent progress in the area and is intended to constitute a useful reference for engineers, physiologists and clinicians working in this challenging and rapidly evolving field.
This is the fourth book of a series dealing with the computer analysis of blood pressure and heart rate variability.
The book, based on the contributions of leading experts, offers data on the latest developments in this challenging and rapidly evolving field. In particular, it provides information on the most recent technical progress in estimating spontaneous baroreflex sensitivity from the beat-to-beat analysis of blood pressure and heart rate signals and illustrates the potential diagnostic and prognostic value of this index in daily life. Furthermore, it focuses on the applications of the newest methods in the assessment of blood pressure and heart rate variability through linear and nonlinear techniques, descriptors of chaotic dynamics and time-frequency distributions. It also addresses the neural and non-neural physiological mechanisms responsible for blood pressure and heart rate time modulation and specifically focuses on the alterations in blood pressure and heart rate variability induced by the derangement of these mechanisms in case of cardiovascular or systemic diseases.
We do hope that the updated state of the art provided herein could represent a useful reference for engineers, physiologists and clinicians working in this stimulating area.
Marco Di Rienzo Gianfranco Parati
Giuseppe Mancia Antonio Pedotti Alberto Zanchetti
A new approach was developed to analyse the relationships between cardiovascular parameters using the concept of Statistical dependence and a new coefficient, Z, that expresses the dependence between two Statistical events, was defined. Using blood pressure (BP) and heart rate (HR) beat-to-beat values recorded in rats, we showed in a previous study that some BP and HR couples of values were dependent due to the activity of the baroreflex. In this study, the ability of Z analysis to estimate baroreflex sensitivity (BRS), using mean BP (MAP) and HR values was tested. Dependent (MAP, HR) couples were selected with Z coefficient and a linear regression was performed between these selected MAP and HR values. The regression slope, taken as the index of BRS, was strongly correlated to BRS estimated with a pharmacological method. In humans, using Finapres® BP recordings, BRS was estimated from systolic BP and HR values with the Z method and with spectral analysis, by Computing the average modulus gain in the 0.07 – 0.14 Hz band. The Z method exhibited a good reproducibility and results obtained with the two methods were significantly correlated. In conclusion, Z coefficient allowed to isolate some couples of BP and HR values related to baroreflex activity. In rats and in humans, it appears able to provide a new estimate of the spontaneous BRS using Z coefficient as a selective filter.
Spontaneous progressive changes in systolic blood pressure (SBP) are not invariably followed by baroreflex-driven changes in pulse interval (PI). In order to quantify this phenomenon we propose a new index, termed Baroreflex Effectiveness Index (BEI), defined as the ratio between the number of times that SBP progressive changes are followed by progressive changes in PI in the same direction and the total number of SBP changes occurring in a given time window.
In this study we applied this new index on data collected in two pilot groups of young and elderly subjects during spontaneous behaviour.
Quantification of the arterial baroreflex has been achieved with different evaluation techniques. Some measurements usually involve pharmacological or mechanical stimulation of the baroreflex, and neglect the feedforward effect of R-R interval (RR) on arterial blood pressure (ABP). The autoregressive multivariate techniques described in this study satisfy both the requirements of a non-invasive and a closed-loop evaluation of the interactions between RR and ABP. The closed-loop analysis is also able to calculate some of the indices previously used for baroreflex quantification, allowing for a direct comparison of the different approaches. Application to recordings from both a group of healthy subjects in different physiological conditions, and from a group of subjects with mild hypertension, suggests that failure to consider the feedforward effect could lead to an overestimation of the baroreflex quantification.
The appreciation of an association between the autonomic nervous System and arrhythmic mortality and a series of experimental results represents the rationale for using baroreflex sensitivity - which predominantly measures reflex vagal activity - as a clinical tool for the identification of patients at increased risk. Among different techniques, the measure of the heart rate slowing in response to a blood pressure rise induced by small intravenous boluses of phenylephrine has been the most widely used method for assessing baroreflex sensitivity both in patients with myocardial infarction and with chronic heart failure. Following small size studies, the ATRAMI (Autonomic Tone and Reflexes After Myocardial Infarction) trial, by studying 1284 myocardial infarction patients has definitely demonstrated not only that a depressed baroreflex sensitivity (< 3 msec/mmHg) is a strong risk factor for cardiac death, but also that the information gained by the analysis of autonomic markers adds to the information obtained by better recognized measures of cardiovascular outcome such as left ventricular function and ventricular arrhythmias. In these patients, the analysis of autonomic activity might be of value in the identification of patients who may need an implantable automatic defibrillator for primary prevention of sudden cardiac death. The analysis of baroreceptor reflexes is of prognostic value also in patients with chronic heart failure, particularly those with severe mitral regurgitation.
To obtain a more comprehensive explanation for the generation and interaction of the variabil-ity signais, namely heart rate variability (HRV), blood pressure variation (BPV) and instantaneous lung volume (ILV), a nonlinear closed loop model of the neuro-cardiovascular system is presented. The new model which is based on the Volterra series reprsentation is able to appropriately describe several features observed experimentally in the variability signals in the HF, LF and VLF bands. The model aggregates a set of linear and nonlinear transfer functions representing the physiology involved in producing the rhythmical fluctuations in heart rate and blood pressure normally observed in intact human. It will be shown that the combination of these transfer functions in the order dictated by the underlying physiological system enables us to investigate the HRV and BPV in a systematic manner. Before detailing the structure of the new model a conceptual discussion about the small signal and large signal cardiovascular modelling will help to gain a deeper understanding of the modelling of the variability signals and its relation with the cardiovascular system analysis.
Nonlinear dynamics are certainly involved in tlie generation and control of cardiovascular signais. The paper presents a methodological and clinical review of nonlinear dynainic analysis in heart rate variability signals (HRV) obtained from normal subjects and pathological cases. The employed methods starts both from state space reconstruction procedures (Correlation Dimension, Lyapunov Exponents, False Nearest Neighborhood, Nonlinear Noise Filtering in the space-state) and by direct estimation of time series characteristics (Self-Similarity Hurst Exponent, Approximate Entropy). Analysis parameters confirm their usefulness in ihe classification of different patient groups. Examples reported for normal subjects, patients after orthotopic heart transplant, patients who recently had an anterior myocardial infarction episode, confirm the ability of these indexes in the HRV patterns classification both in short and long temporal Windows. Moreover, preliminary results in ICU patients indicate that long period indexes seem to be strongly related to the prediction of both positive and negative patient outcome. Computation of parameters from the nonlinear dynamic approach to the cardiovascular system can be a valid help for diagnosis of pathological heart States.
The purpose of this study was to quantify the short and long-term correlation characteristics of heart rate variability with atrial fibrillation (AF). Long term analysis was performed on the entire 24-hour heart rate series by applying two independent methods: a) analysis of correlation dimension, and b) analysis of fractal scaling properties using detrended fluctuation analysis (DFA). Short term analysis was performed on non-overlapping series of 500-beat segments, spanning the entire 24 hours, by applying two complementary techniques: the DFA analysis and the autocorrelation function (ACF). We obtained consistent results among the subjects for both long and short-term analysis. DFA analysis of the 24-hours showed a two-slope “cross-over” behavior with the inflection point occurring at about 100 beats. The average slope was αl = 0.55±0.05 (below 100 beats) and α2 = 1.16±0.06 (above 100 beats). DFA analysis on the short 500-beat segments showed a single slope behavior in all subjects (α = 0.56±0.04), with the exception of a patient who underwent electrical cardioversion. The second point of the ACF follows an almost identical behavior (α = -0.49±0.03). Therefore, for time scales less than 100 beats the local beat-to-beat behavior is reminiscent of a “white noise” (uncorrelated) process. In contrast, for time scales greater than 100 beats, the heart rate scaling properties in AF are surprisingly comparable to those in sinus rhythm (long-range Organization). However, we find no evidence of low-dimensional deterministic chaos in AF.
Objective. To compare the results on short-term heart rate variability, analyzed in tlie frequency domain by use of autoregressive modeling (ARM) and by fast Fourier transform (FFT).
Methods. RR interval and respiratory activity were recorded in a population-based sample of 614 subjects, during 15 minutes in the supine position and 15 minutes in the free Standing position, under standardized laboratory conditions. The low - (LF) and high -frequency (HF) components of heart rate variability were identified by power spectral analysis, by use of FFT, witli application of two sets of frequency ranges, and by ARM according to a newly developed algoritlun; LF and HF power were expressed in both normalized (%) and absolute units (ms2).
Results. The RR interval, its variance and the HF power decreased from the supine to the Standing position (P < 0.001).The LF power increased on standing when expressed in normalized units, but decreased in absolute units, whereas the LF-to-HF ratio increased (P < 0.001). On the low side of the spectrmn, FFT slightly overestimated the LF component obtained with ARM, when the predefmed frequency range was 0.05 - 0.15 Hz (P < 0.001); the underestimation of LF in the frequency range 0.07 - 0.14 Hz was more pronounced, particularly in tiie erect position (P < 0.001). Both FFT methods overestimated (P < 0.001) the ARM HF component, more so for the 0.15-0.50 Hz range than for the 0.14 - 0.35 Hz range. Finally, we observed considerable within-subject differences between methods, which were estimated by calculation of the limits of agreement.
Conclusions. Different methods for spectral decomposition of short-term heart rate variability yield similar qualitative results, but the quantitative results differ between ARM and FFT, and within the FFT method according to the selected frequency range.
To examine whether spontaneous autoregulatory responses of the arterial vasculature can contribute to the short-term variability of arterial pressure (AP), rats were chronically instrumented for the simultaneous measurement in the conscious State of AP and of either cardiac output, mesenteric or hindquarters blood flow. Acute pharmacological removal of neurohumoral influences induced a marked increase in AP variability when the AP level was maintained with a continuous noradrenaline infusion. AP lability was especially due to the spontaneous occurrence of large depressor episodes that were accompanied by systemic and regional vasodilations. Both time- and frequency-domain analyses revealed that changes in vascular conductances lagged by ∼1 s behind AP changes, thus demonstrating the autoregulatory-like nature of these hemodynamic fluctuations. In intact animals, changes in vascular conductances were not delayed relative to AP changes, except in the mesenteric circulation, where autoregulatory-like fluctuations prevailed up to 0.1 Hz. In this circulation, most of the spontaneous variability of vascular conductance appeared as an oscillation centered at 0.1-0.15 Hz, irrespective of neurohumoral influences. We conclude that after neurohumoral blockade, autoregulatory-like responses become a major source of AP variability. Due to their unexpectedly short latency, these responses operate up to 0.15-0.2 Hz. The reflex control of AP normally overrides autoregulation, except in the mesenteric circulation.
Since chaotic phenomena of heart rate have been observed, investigations by time series analysis have been focused on the non-linear dynamics of the cardiac control system. Without the necessity to understand the functional structures of the complex regulatory network that controls heart rate, non-linear methods are a useful approach to characterize the processes inside this black box. We applied established linear and non-linear methods to obtain comprehensive information regarding heart rate control and its relation to the respiratory system. To study normal regulation under various conditions, 42 healthy children were investigated during different vigilance stages. The parameters of heart rate power spectra were estimated, the linear intensity of cardiorespiratory coupling was concluded from the coherence spectra. As to non-linear properties of heart rate, the largest Lyapunov exponents as well as the correlation dimension were determined. Similarly, the correlation dimension of the respiratory signals was evaluated. The total power of the heart rate spectrum was found to be greatest during REM, it decreased during wakefulness and was low in nonREM-sleep. These variations are mainly accounted for by low frequency power. The “complexity” of heart rate, as indicated by the correlation dimension, is diminished during sleep phases, whereas the Lyapunov exponents are less affected. The cardiorespiratory coherence is strongly modulated by vigilance with an increase during nonREM and lowest values during REM. The complexity of respiration was also affected by vigilance. A different behavior of heart rate complexity was found during REM-phases. Concluded from spectral analysis, we suggest a specific setting of autonomic heart rate regulation for each vigilance stage. A low dimensional deterministic chaos is present in heart rate time series. More independent control loops were found to be active during wakefulness. Revealed by parameters of the non-linear dynamics, different stages of vigilance determine different operating points in the cardiorespiratory coordination.
Background. Blood pressure fluctuations over the 24 hours include both fast and slow changes. While most studies have focused on the former components, recent evidence suggests that also slower blood pressure variations may have physiological and clinical relevance. A method recently proposed to quantify these slower blood pressure components is broad band spectral analysis.
Methods and Results: Broad band spectral analysis consists in the estimation of a single spectrum obtained by considering all data included in a long term recording and in the quantification of the power of all frequency components, from the slowest to the fastest ones. Application of this method to recordings obtained in animais before and after surgical baroreceptor denervation has shown that not only fast but also slow blood pressure and heart rate fluctuations are under baroreflex control. Clinical applications of broad band spectral analysis have included 1] the quantification of the age-induced changes in the different components of blood pressure and heart variability, 2] the assessment of the effects of treatment on blood pressure and heart rate fluctuations in hypertensive patients, and 3] the assessment of the prognostic value of slow heart rate fluctuations in post-myocardial infarction patients.
Conclusions: Broad band spectral analysis represents a unique tool for the quantification of all components of blood pressure and heart rate variability and for the assessment of their possible changes in diseased conditions or under the effects of treatment.
In a previous study we developed a method to estimate a person's age based on 10 s episodes of arterial pressure pulsations using a neural net technique. The pulsations were recorded in the morning in supine or semi-reclining position in rest. We wondered if the age estimation techniques would produce systematically different values under ambulatory conditions, during night or day, in other postures, over the 24 hours. We, therefore, analyzed 10 s episodes each half hour over the 24 hours in 12 previously recorded persons aged 19 to 58 years, applying the waveforms to the same neural net as previously developed. We pre-pared averages over the 24 hours, over the day, the night, the morning, and the siesta and compared them to calendar age of the persons. We found no systematic differences between the various estimates and with calendar age. We conclude that neural net estimation of a person's age based on his arterial pulse is stable during the 24 hours.
The aim of this study was to generate hemorrhage-triggered fluctuations in blood pressure (BP) at low-frequency (LF, below 0.2 Hz) in conscious rats, and to investigate with spectral analysis the relative roles of hemorrhage-activated catecholamines, the renin-angiotensin system (RAS) and arginine-vasopressin (AVP) on the generation of these fluctuations. After severe hemorrhage (20 ml/kg), the spontaneous BP recovery was characterised by the occurrence of slow fluctuations of systolic and diastolic BP centered around 0.065 Hz. The occurrence of these LF fluctuations was prevented when α1-adrenergic activity was blocked by Prazosin. These oscillations were always present in spite of inhibition of angiotensin II and were increased after inhibition of the AVP activity. In conclusion, the present results show an association between the secretion of catecholamines resulting from a severe hemorrhage and the occurrence of slow fluctuations of BP. The buffering role of AVP suggest the establishment of a hierarchy between humoral Systems in the genesis of the LF oscillations of BP, with the slow oscillations being generated by the main catecholaminergic pressor system and being dampened by the other systems.
Nitric oxidc is continuously released in the circulation where it can quickly modify the hemodynamic conditions and therefore affect blood pressure variability. Nevertheless the effect of nitric oxide on blood pressure variability has not been completely elucidated; moreover it remains unknown whether nitric oxide acts independently, in concert or in opposition with the autonomic nervous system. In order to answer these questions we studied the effects of nitric oxide synthesis inhibition in intact, sympathectomized (Sympx) and sino-aortic denervated (SAD) conscious WKY rats. Mean arterial pressure (MAP) and pulse interval (PI) were continuously recorded for 60 minutes both in absence and in presence of an 1-arginine analogue, 1-NMMA (iv bolus 100 mg.kg-1, followed by a 1.5 mg.kg-1 .min-1 infusion for 60 minutes). Data were analyzed by means of FFT power spectral analysis in the HF (3.0 to 0.8 Hz), MF (0.6 to 0.1 Hz), and LF (0.1 to 0.025 Hz) frequency bands. Sympathectomy moderately reduced MAP whereas SAD did not change it significantly. 1-NMMA increased MAP (intact: from 97.2±3.6 to 135.4±4.2 mmHg, p<0.01; Sympx: from 73.6±3.9 to 124.3±5.9 mmHg, p<0.01; SAD: from 101.0±14.5 to 141.1±19.4 mmHg, p<0.01). Spectral analysis of both MAP and PI showed a different effect of 1-NMMA in the three groups of rats: 1-NMMA reduced significantly MF power of MAP in intact rats (from 1.67±0.60 to 0.75± 0.24 mmHg2 p<0.001) and in SAD rats (from 2.90±0.80 to 1.86±0.90, p <0.05) but not in sympathectomized rats (from 0.67±0.37 to 0.60±0.32 mmHg2, p=ns). Concerning PI, 1-NMMA increased significantly LF power in sympathectomized rats and HF power in both intact and sympathectomized rats (all p<0.01) but it did not modify spectral powers in SAD rats. In conclusion our data suggest that 1) nitric oxide contributes to generate overall blood pressure variability in the mid frequency range and 2) this effect is related to an interaction between nitric oxide and sympathetic neural influences.
The human transplanted heart is a model of denervated heart, hence any fluctuation present in thc RR interval variability can be either due to reaquired innervation, or to represent the effect of some non autonomic activity, such as a direct effect of respiration on atrial stretch. Various physical and pharmacological manoeuvres on the respiratory and non-respiratory components of heart rate variability are used to assess the occurrence of reinnervation.
So far reinnervation was limited to the sympathetic branch. This could be due to the “standard” type of surgery that Ieaves most of vagal fibers intact. Our first observation of vagal reinnervation assessed by sinusoidal modulation of arterial baroreceptors by neck suction was obtained in a transplant patient (TX) who underwent a new type of surgery called “bi-caval”, characterised by a more extensive removal of the recipient atria. In a further study in “bi-caval” TX the probability of observing vagal reinnervation was similar to that of sympathetic reinnervation; in contrast, this probability with the “standard” technique is very low or zero regardless of time since transplantation, unless more extensive cutting of the recipient atria is performed. Similar to sympathetic reinnervation, vagal reinnervation progresses over time.
In conclusion, there is the possibility to increase vagal reinnervation in patients undergoing heart transplantation, namely by extensive resection of ihe recipient atria. This observation has high clinical relevance because a better control of the cardiovascular system would improve adaptation to various stimuli and to physical exercise.
We describe an integrated evaluation of central autonomic regulation, relating the simultaneously recorded electroencephalogram (EEG) and transcranial Doppler (TCD) to systemic cardiovascular indices. Signal analysis techniques included time-frequency analysis and nonlinear rescaled range analysis. The inhibition of centrally mediated autonomic rhythms can precede clinical manifestations e.g. syncope (increased slow EEG modulation, withdrawal of 0.05 Hz rhythms in BP and progressive decline in total peripheral resistance). We tested the hypothesis that partial complex seizures, which has a structural substrate with powerful autonomic manifestations, might also have autonomic alterations that precede EEG changes. We observed that sympathetic activation of slow rhythms in RRI preceded seizure onset, while parasympathetically mediated rhythms rapidly diminished at the beginning of the seizure. We used the Hurst exponent, based on the rescaled range analysis for evaluation of deterministic component in patients with orthostatic tachycardia. Data showed that the loss of variability in RRI was associated with increased values of Hurst exponent. Thus, the process become more deterministic.