Nonlinear dynamics of heart rate variability in response to orthostatism and hemodialysis in chronic renal failure patients: recurrence analysis approach

Characterization of heart rate variability in end-stage renal disease patients after kidney transplantation with recurrence quantification analysis

Heart rate variability (HRV) is a noninvasive approach to studying the autonomic modulation of heart rate in experimental settings, such as active standing sympathetic stimulation. It is known that patients with end-stage renal disease during active standing have few changes in HRV dynamics, which are improved after hemodialysis. However, it is unknown whether the response to active standing is recovered after definitive treatment with kidney transplantation. This work aims to assess the change in HRV dynamics in the supine position and active standing through time and frequency-based metrics, as well as recurrence plot quantitative analysis (RQA). We studied HRV dynamics by obtaining 5-minute electrocardiographic recordings from kidney transplant recipients who underwent an active standing test. The mean duration of heartbeats and their standard deviation diminished in active standing, compared with the supine position. Also, the low-frequency component of HRV and the presence of diagonal and vertical structures in RQA were predominant. A larger estimated glomerular filtration rate was significantly correlated with broader HRV in the supine position and during active standing. The narrower HRV during active standing may indicate a sympathetic response to external stimuli, which is expected in a functional cardiovascular system, and may be influenced by renal function.

Baroreflex Sensitivity Assessment Using the Sequence Method with Delayed Signals in End-Stage Renal Disease Patients

Impaired baroreflex sensitivity (BRS) is partially responsible for erratic blood pressure fluctuations in End-Stage Renal Disease (ESRD) patients on chronic hemodialysis (HD), which is related to autonomic nervous dysfunction. The sequence method with delayed signals allows for the measurement of BRS in a non-invasive fashion and the investigation of alterations in this physiological feedback system that maintains BP within healthy limits. Our objective was to evaluate the modified delayed signals in the sequence method for BRS assessment in ESRD patients without pharmacological antihypertensive treatment and compare them with those of healthy subjects. We recruited 22 healthy volunteers and 18 patients with ESRD. We recorded continuous BP to obtain a 15-min time series of systolic blood pressure and interbeat intervals during the supine position (SP) and active standing (AS) position. The time series with delays from 0 to 5 heartbeats were used to calculate the BRS, number of data points, number of sequences, and estimation error. The BRS from the ESRD patients was smaller than in healthy subjects (p < 0.05). The BRS estimation with the delayed sequences also increased the number of data points and sequences and decreased the estimation error compared to the original time series. The modified sequence method with delayed signals may be useful for the measurement of baroreflex sensitivity in ESRD patients with a shorter recording time and maintaining an estimation error below 0.01 in both the supine and active standing positions. With this framework, it was corroborated that baroreflex sensitivity in ESRD is decreased when compared with healthy subjects.

Heart Rate Fractality Disruption as a Footprint of Subthreshold Depressive Symptoms in a Healthy Population

OBJECTIVE

Psychopathology (and depression in particular) is a cardiovascular risk factor independent from any co-occurring pathology. This link is traced back to the mind-heart-body connection, whose underlying mechanisms are still not completely known. To study psychopathology in relation to the heart, it is necessary to observe the autonomic nervous system, which mediates among the parts of that connection. Its gold standard of evaluation is the study of heart rate variability (HRV). To investigate whether any association exists between the HRV parameters and sub-threshold depressive symptoms in a sample of healthy subjects.

METHOD

In this cross-sectional study, two short-term HRV recordings (5 min - supine and sitting) have been analyzed in 77 healthy subjects. Here we adopted a three-fold approach to evaluate HRV: a set of scores belonging to the time domain; to the frequency domain (high, low, and very low frequencies) and a set of 'nonlinear' parameters. The PHQ-9 (Patient Health Questionnaire-9) scale was used to detect depressive symptoms.

RESULTS

Depressive symptoms were associated only with a parameter from the non-linear approach and specifically the long-term fluctuations of fractal dimensions (DFA-α2). This association remained significant even after controlling for age, gender, BMI (Body-Mass-Index), arterial hypertension, anti-hypertensive drugs, dyslipidemia, and smoking habits. Moreover, the DFA-α2 was not affected by the baroreflex (postural change), unlike other autonomic markers.

CONCLUSIONS

Fractal analysis of HRV (DFA-α2) allows then to predict depressive symptoms below the diagnostic threshold in healthy subjects regardless of their health status. DFA-α2 may be considered as an imprint of subclinical depression on the heart rhythm.

Recurrence Quantitative Analysis of Wavelet-Based Surrogate Data for Nonlinearity Testing in Heart Rate Variability

Exploring the presence of nonlinearity through surrogate data testing provides insights into the nature of physical and biological systems like those obtained from heart rate variability (HRV). Short-term HRV time series are of great clinical interest to study autonomic impairments manifested in chronic diseases such as the end stage renal disease (ESRD) and the response of patients to treatment with hemodialysis (HD). In contrast to Iterative Amplitude Adjusted Fourier Transform (IAAFT), the Pinned Wavelet Iterative Amplitude Adjusted Fourier Transform (PWIAAFT) surrogates preserve nonstationary behavior in time series, a common characteristic of HRV. We aimed to test synthetic data and HRV time series for the existence of nonlinearity. Recurrence Quantitative Analysis (RQA) indices were used as discriminative statistics in IAAFT and PWIAAFT surrogates of linear stationary and nonstationary processes. HRV time series of healthy subjects and 29 ESRD patients before and after HD were tested in this setting during an active standing test. Contrary to PWIAAFT, linear nonstationary time series may be erroneously regarded as nonlinear according to the IAAFT surrogates. Here, a lower proportion of HRV time series was classified as nonlinear with PWIAAFT, compared to IAAFT, confirming that the nonstationarity condition influences the testing of nonlinear behavior in HRV. A contribution of nonlinearity was found in the HRV data of healthy individuals. A lower proportion of nonlinear time series was also found in ESRD patients, but statistical significance was not found. Although this proportion tends to be lower in ESRD patients, as much as 60% of time series proved to be nonlinear in healthy subjects. Given the important contribution of nonlinearity in HRV data, a nonlinear point of view is required to achieve a broader understanding of cardiovascular physiology.

Which subject-related variables contribute to movement variability during a simulated repetitive and standardised occupational task? Recurrence quantification analysis of surface electromyographic signals

Movement variability is a component of human movement. This study applied recurrence quantification analysis (RQA) on electromyographic signals to determine the effects of two types of variables on movement variability during a short, simulated repetitive and standardised occupational clip-fitting task. The electrical activity of six muscles in the dominant upper limb was recorded in 21 participants. Variables related to the task performance (insertion force and movements performed when fitting clips) affected RQA measures: recurrence rate (RR), percentage of determinism (DET) and diagonal line length entropy (ENT). Variables related to participant's characteristics (sex, age, and BMI) affected only DET and ENT. A constrasting variability was observed such as a high-DET value combined with a high-ENT value and inversely. Variables affected mainly the recurrences organisation of the more distal muscles. Even if movement variability is complex, it should be considered by ergonomists and work place designers to better understanding of operators' movements. Practitioner summary: It is essential to consider the complexity of operators' movement variability to understand their activities. Based on intrinsic movement variability knowledge, ergonomists and work place designers will be able to modulate the movement variability by acting on workstation designs and occupational organisation with the aim of preserving operators' health. Abbreviations: RR: recurrence rate; DET: percentage of determinism; ENT: diagonal line length entropy; BMI: body mass index; FDS: flexor digitorum superficialis; EXT: extensor digitorum communis; BIC: biceps brachii; TRI: triceps brachii; DEL: deltoideus anterior; TRA: trapezius pars descendens; F: female; M: male; S: supinated; P: pronated; CM: continuous movement; DM: discontinuous movement.

Quantification and classification of potassium and calcium disorders with the electrocardiogram: What do clinical studies, modeling, and reconstruction tell us?

Diseases caused by alterations of ionic concentrations are frequently observed challenges and play an important role in clinical practice. The clinically established method for the diagnosis of electrolyte concentration imbalance is blood tests. A rapid and non-invasive point-of-care method is yet needed. The electrocardiogram (ECG) could meet this need and becomes an established diagnostic tool allowing home monitoring of the electrolyte concentration also by wearable devices. In this review, we present the current state of potassium and calcium concentration monitoring using the ECG and summarize results from previous work. Selected clinical studies are presented, supporting or questioning the use of the ECG for the monitoring of electrolyte concentration imbalances. Differences in the findings from automatic monitoring studies are discussed, and current studies utilizing machine learning are presented demonstrating the potential of the deep learning approach. Furthermore, we demonstrate the potential of computational modeling approaches to gain insight into the mechanisms of relevant clinical findings and as a tool to obtain synthetic data for methodical improvements in monitoring approaches.

Anticipation of ventricular tachyarrhythmias by a novel mathematical method: Further insights towards an early warning system in implantable cardioverter defibrillators

Implantable cardioverter defibrillators (ICD) are the most effective therapy to terminate malignant ventricular arrhythmias (VA) and therefore to prevent sudden cardiac death. Until today, there is no way to predict the onset of such VA. Our aim was to develop a mathematical model that could predict VA in a timely fashion. We analyzed the time series of R-R intervals from 3 groups. Two groups from the Spontaneous Ventricular Tachyarrhythmia Database (v 1.0) were analyzed from a set of 81 pairs of R-R interval time series records from patients, each pair containing one record before the VT episode (Dataset 1A) and one control record which was obtained during the follow up visit (Dataset 1B). A third data set was composed of the R-R interval time series of 54 subjects without a significant arrhythmia heart disease (Dataset 2). We developed a new method to transform a time series into a network for its analysis, the ε-regular graphs. This novel approach transforms a time series into a network which is sensitive to the quantitative properties of the time series, it has a single parameter (ε) to be adjusted, and it can trace long-range correlations. This procedure allows to use graph theory to extract the dynamics of any time series. The average of the difference between the VT and the control record graph degree of each patient, at each time window, reached a global minimum value of -2.12 followed by a drastic increase of the average graph until reaching a local maximum of 5.59. The global minimum and the following local maxima occur at the windows 276 and 393, respectively. This change in the connectivity of the graphs distinguishes two distinct dynamics occurring during the VA, while the states in between the 276 and 393, determine a transitional state. We propose this change in the dynamic of the R-R intervals as a measurable and detectable "early warning" of the VT event, occurring an average of 514.625 seconds (8:30 minutes) before the onset of the VT episode. It is feasible to detect retrospectively early warnings of the VA episode using their corresponding ε-regular graphs, with an average of 8:30 minutes before the ICD terminates the VA event.

Association between Mean Heart Rate and Recurrence Quantification Analysis of Heart Rate Variability in End-Stage Renal Disease

Linear heart rate variability (HRV) indices are dependent on the mean heart rate, which has been demonstrated in different models (from sinoatrial cells to humans). The association between nonlinear HRV indices, including those provided by recurrence plot quantitative analysis (RQA), and the mean heart rate (or the mean cardiac period, also called meanNN) has been scarcely studied. For this purpose, we analyzed RQA indices of five minute-long HRV time series obtained in the supine position and during active standing from 30 healthy subjects and 29 end-stage renal disease (ESRD) patients (before and after hemodialysis). In the supine position, ESRD patients showed shorter meanNN (i.e., faster heart rate) and decreased variability compared to healthy subjects. The healthy subjects responded to active standing by shortening the meanNN and decreasing HRV indices to reach similar values of ESRD patients. Bivariate correlations between all RQA indices and meanNN were significant in healthy subjects and ESRD after hemodialysis and for most RQA indices in ESRD patients before hemodialysis. Multiple linear regression analyses showed that RQA indices were also dependent on the position and the ESRD condition. Then, future studies should consider the association among RQA indices, meanNN, and these other factors for a correct interpretation of HRV.

Dynamical interaction between heart rate and blood pressure of end-stage renal disease patients evaluated by cross recurrence plot diagonal analysis

The assessment of spontaneous variability of blood pressure and heart rate is based on specific physiological hypotheses about dynamic features, for example, the baroreflex modulation of heart rate over time in daily life. Usually, arterial baroreflex control of heart rate is explored without delays between blood pressure and heart rate data points, within a narrow range of values, excluding the analysis of saturation regions or low-threshold changes. In this work, we examine the dynamic interactions between systolic blood pressure (SBP) and interbeat interval (IBI), in 15-min length time series and for the first time using the analysis of diagonals derived from a cross-recurrence plots in healthy persons and end-stage renal disease (ESRD) patients. We found that ESRD patients have stronger intermittent dynamical interactions between IBI and SBP, but they lose most of the dynamical interactions. Although healthy subjects exhibit a continuously changing order of precedence between IBI and SBP at different lags, ESRD patients preserve this changing order of precedence only for lags >0 beats.NEW & NOTEWORTHY This study is the first to compare the time-variant pattern of systolic blood pressure (SBP) and interbeat interval (IBI) coupling between ESRD patients and healthy volunteers through the analysis of diagonal in cross-recurrence plots, and in the face of an orthostatic challenge. Our results demonstrated alternant interactions on the order of precedence (IBI → SBP or SBP→ IBI) at different time delays. This pattern is different in resting position and during active standing for the two groups studied, and interestingly, some association patterns are lost in ESRD patients. These patterns of alternant interactions on the order of precedence could be related to autonomic neural activities and cardiovascular synchronization at different scales both in time and space. This could reflect physiological adaptive flexibility of cardiovascular regulation. Losing some association patterns in ESRD may be the result of chronic adjustments of many physiological mechanisms (including chronic sympathetic hyperactivity), which could increase cardiovascular vulnerability to hemodynamic challenges.

Analysis of diagonals in cross recurrence plots between heart rate and systolic blood pressure during supine position and active standing in healthy adults

The inter beat interval (IBI) duration and systolic blood pressure (SBP) are cardiovascular variables related through several feedback mechanisms. We propose the analysis of diagonal lines in cross recurrence plots (CRPs) from IBI and SBP embedded within the same phase space to identify events where trajectories of both variables concur. The aim of the study was to describe the relationship between IBI and SBP of healthy subjects using CRP and diagonal analysis during baseline condition-supine position (SP)-and how the relationship changes during the physiological stress of active standing (AS). IBI and SBP time series were obtained from continuous blood pressure recordings during SP and AS (15 min each) in 19 young healthy subjects. IBI and SBP time series were embedded within a five-dimensional phase space using an embedding delay estimated from cross correlation between IBI and SBP. During SP, mean CRP showed high determinism (≥85%) and also brief but repeated events where both variables stay within a reduced space. Most quantitative recurrences analysis indexes of CRP increased significantly (p < 0.05) during AS. CRP analysis showed short diagonals indicating a very strong deterministic relationship between IBI and SBP with intermittent unlocking periods. The strength of IBI and SBP relationship increased during the physiological stress of AS. The CRP method allowed a rigorous quantitative description of the deterministic association between these two variables. Diagonal lines were intermittent and not always parallel, showing that there is not a defined and unique rhythm. This suggests the activation of different influences at different times and with different precedence between the heart rate and blood pressure in response to AS.

Sign and magnitude scaling properties of heart rate variability in patients with end-stage renal failure: Are these properties useful to identify pathophysiological adaptations?

The scaling properties of heart rate variability data are reliable dynamical features to predict mortality and for the assessment of cardiovascular risk. The aim of this manuscript was to determine if the scaling properties, as provided by the sign and magnitude analysis, can be used to differentiate between pathological changes and those adaptations basically introduced by modifications of the mean heart rate in distinct manoeuvres (active standing or hemodialysis treatment, HD), as well as clinical conditions (end stage renal disease, ESRD). We found that in response to active standing, the short-term scaling index (α₁) increased in healthy subjects and in ESRD patients only after HD. The sign short-term scaling exponent (α_1sign) increased in healthy subjects and ESRD patients, showing a less anticorrelated behavior in active standing. Both α₁ and α_1sign did show covariance with the mean heart rate in healthy subjects, while in ESRD patients, this covariance was observed only after HD. A reliable estimation of the magnitude short-term scaling exponent (α_1magn) required the analysis of time series with a large number of samples (>3000 data points). This exponent was similar for both groups and conditions and did not show covariance with the mean heart rate. A surrogate analysis confirmed the presence of multifractal properties (α_1magn > 0.5) in the time series of healthy subjects and ESDR patients. In conclusion, α₁ and α_1sign provided insights into the physiological adaptations during active standing, which revealed a transitory impairment before HD in ESRD patients. The presence of multifractal properties indicated that a reduced short-term variability does not necessarily imply a declined regulatory complexity in these patients.

Effects of Orthostatism and Hemodialysis on Mean Heart Period and Fractal Heart Rate Properties of Chronic Renal Failure Patients

The aim of this work was to evaluate the short-term fractal index (α₁ ) of heart rate variability (HRV) in chronic renal failure (CRF) patients by identifying the effects of orthostatism and hemodialysis (HD), and by evaluating the correlation between α₁ and the mean RR interval from sinus beats (meanNN). HRV time series were derived from ECG data of 19 CRF patients and 20 age-matched healthy subjects obtained at supine and orthostatic positions (lasting 5 min each). Data from CRF patients were collected before and after HD. α₁ was calculated from each time series and compared by analysis of variance. Pearson's correlations between meanNN and α₁ were calculated using the data from both positions by considering three groups: healthy subjects, CRF before HD and CRF after HD. At supine position, α₁ of CRF patients after HD (1.17 ± 0.30) was larger (P < 0.05) than in healthy subjects (0.89 ± 0.28) but not before HD (1.10 ± 0.34). α₁ increased (P < 0.05) in response to orthostatism in healthy subjects (1.29 ± 0.26) and CRF patients after HD (1.34 ± 0.31), but not before HD (1.25 ± 0.37). Whereas α₁ was correlated (P < 0.05) with the meanNN of healthy subjects (r = -0.562) and CRF patients after HD (r = -0.388), no significance in CRF patients before HD was identified (r = 0.003). Multiple regression analysis confirmed that α₁ was mainly predicted by the orthostatic position (in all groups) and meanNN (healthy subjects and patients after HD), showing no association with the renal disease condition in itself. In conclusion, as in healthy subjects, α₁ of CRF patients correlates with meanNN after HD (indicating a more irregular-like HRV behavior at slower heart rates). This suggests that CRF patients with stable blood pressure preserve a regulatory adaptability despite a shifted setting point of the heart period (i.e., higher heart rate) in comparison with healthy subjects.

Heart rate variability is an indicator for intradialytic hypotension among chronic hemodialysis patients

BACKGROUND

Intradialytic hypotension (IDH) carries adverse impact. Heart rate variability (HRV) represents autonomic cardiac regulation which influences intradialytic blood pressure. We aimed to evaluate the association between IDH and HRV.

METHODS

This prospective study was carried out in a teaching hospital in Taiwan from June to August 2010. Adult patients on chronic hemodialysis without active medical conditions were enrolled and received HRV measurements for 4 times (before and during an index hemodialysis session). Patients were categorized by the changes of systolic blood pressure during the index hemodialysis into Group 1 (elevation >20 mmHg), Group 2 (decrease >20 mmHg), and Group 3 (others). Then we compared HRV indices among the three groups, and determined the indicators for IDH.

RESULTS

One hundred and seventy-one patients (96 women, mean age 64.9 years) were enrolled and categorized into Group 1 (n = 47, 27.5 %), Group 2 (n = 45, 26.3 %) and Group 3 (n = 79, 46.2 %). Comparing with Group 1 and/or Group 3, Group 2 had significantly higher blood pressure at hemodialysis initiation (most p < 0.001) and statistically lower levels of HRV indices including variance, total power, very low-frequency, low-frequency and high-frequency since the middle phase of the hemodialysis. By logistic regression method, higher systemic blood pressure [odds ratio (OR) 1.048; p < 0.001], heart rate (OR 1.093; p = 0.021), low-frequency/high-frequency ratio (OR 1.715; p = 0.022), as well as lower variance (OR 0.639; p = 0.048) at hemodialysis initiation were independently associated with intradialytic blood pressure changes.

CONCLUSIONS

HRV is a useful indicator for IDH among hemodialysis patients.

Paradoxical response to an emotional task: trait characteristics and heart-rate dynamics

The present study evaluated the heart-rate dynamics of subjects reporting decreased (responders) or paradoxically increased relaxation (nonresponders) at the end of a threatening movie. Heart-rate dynamics were characterized by indices extracted through recurrence quantification analysis (RQA) and detrended fluctuation analysis (DFA). These indices were studied as a function of a few individual characteristics: hypnotizability, gender, absorption, anxiety, and the activity of the behavioral inhibition and activation systems (BIS/BAS). Results showed that (a) the subjective experience of responsiveness is associated with the activity of the behavioral inhibition system and (b) a few RQA and DFA indices are able to capture the influence of cognitive-emotional traits, including hypnotizability, on the responsiveness to the threatening task.

VO2 and VCO2 variabilities through indirect calorimetry instrumentation

The aim of this paper is to understand how to measure the VO2 and VCO2 variabilities in indirect calorimetry (IC) since we believe they can explain the high variation in the resting energy expenditure (REE) estimation. We propose that variabilities should be separately measured from the VO2 and VCO2 averages to understand technological differences among metabolic monitors when they estimate the REE. To prove this hypothesis the mixing chamber (MC) and the breath-by-breath (BbB) techniques measured the VO2 and VCO2 averages and their variabilities. Variances and power spectrum energies in the 0-0.5 Hertz band were measured to establish technique differences in steady and non-steady state. A hybrid calorimeter with both IC techniques studied a population of 15 volunteers that underwent the clino-orthostatic maneuver in order to produce the two physiological stages. The results showed that inter-individual VO2 and VCO2 variabilities measured as variances were negligible using the MC while variabilities measured as spectral energies using the BbB underwent 71 and 56% (p < 0.05), increase respectively. Additionally, the energy analysis showed an unexpected cyclic rhythm at 0.025 Hertz only during the orthostatic stage, which is new physiological information, not reported previusly. The VO2 and VCO2 inter-individual averages increased to 63 and 39% by the MC (p < 0.05) and 32 and 40% using the BbB (p < 0.1), respectively, without noticeable statistical differences among techniques. The conclusions are: (a) metabolic monitors should simultaneously include the MC and the BbB techniques to correctly interpret the steady or non-steady state variabilities effect in the REE estimation, (b) the MC is the appropriate technique to compute averages since it behaves as a low-pass filter that minimizes variances, (c) the BbB is the ideal technique to measure the variabilities since it can work as a high-pass filter to generate discrete time series able to accomplish spectral analysis, and (d) the new physiological information in the VO2 and VCO2 variabilities can help to understand why metabolic monitors with dissimilar IC techniques give different results in the REE estimation.