Heart rate complexity in sinoaortic-denervated mice

Heart rate variability in congenital central hypoventilation syndrome: relationships with hypertension and sinus pauses

BACKGROUND

Autonomic nervous system (ANS) dysregulation has been described in congenital central hypoventilation syndrome (CCHS). The objectives were to describe heart rate variability (HRV) analyses in children suffering from CCHS both while awake and asleep and their relationships with both ambulatory blood pressure (BP) and ECG monitoring results.

METHODS

This retrospective study enrolled children with CCHS (n = 33, median age 8.4 years, 18 girls) who had BP and ECG monitored during the same 24 h. From the latter, HRV analyses were obtained during daytime and nighttime.

RESULTS

The prevalences of hypertension and sinus pauses were 33% (95% confidence interval [CI]: 18-52) and 18% (95% CI: 7-35), respectively. The decrease in systolic BP at night negatively correlated with an increase in very low frequency (VLF) and LF powers at night, and the longest RR interval positively correlated with daytime VLF and LF powers. Among the three groups of children (polyalanine repeat expansion mutation [PARM], moderate [20/25 and 20/26], severe [20/27 and 20/33], and non-PARMs), the prevalence of elevated BP or hypertension was different: in PARM subjects: 6/18 moderate, 7/9 severe versus 0/6 in non-PARM (p = 0.002).

CONCLUSION

Modifications of cardiac ANS are associated with systemic hypertension and the occurrence of sinus pauses in CCHS.

IMPACT

Children with congenital central hypoventilation syndrome (CCHS) exhibit an increased prevalence of hypertension and sinus pauses that are linked to cardiac autonomic nervous system dysfunction. Sinus pauses are the main manifestation of sinus nodal dysfunction in children with CCHS. The increased prevalence of hypertension, especially at nighttime, is a new finding in CCHS. Sinus nodal dysfunction can be due to the sole impairment of the cardiac autonomic nervous system. Ambulatory blood pressure and ECG monitoring are mandatory in patients with CCHS.

Fractal Correlation Properties of Heart Rate Variability as a Biomarker for Intensity Distribution and Training Prescription in Endurance Exercise: An Update

While established methods for determining physiologic exercise thresholds and intensity distribution such as gas exchange or lactate testing are appropriate for the laboratory setting, they are not easily obtainable for most participants. Data over the past two years has indicated that the short-term scaling exponent alpha1 of Detrended Fluctuation Analysis (DFA a1), a heart rate variability (HRV) index representing the degree of fractal correlation properties of the cardiac beat sequence, shows promise as an alternative for exercise load assessment. Unlike conventional HRV indexes, it possesses a dynamic range throughout all intensity zones and does not require prior calibration with an incremental exercise test. A DFA a1 value of 0.75, reflecting values midway between well correlated fractal patterns and uncorrelated behavior, has been shown to be associated with the aerobic threshold in elite, recreational and cardiac disease populations and termed the heart rate variability threshold (HRVT). Further loss of fractal correlation properties indicative of random beat patterns, signifying an autonomic state of unsustainability (DFA a1 of 0.5), may be associated with that of the anaerobic threshold. There is minimal bias in DFA a1 induced by common artifact correction methods at levels below 3% and negligible change in HRVT even at levels of 6%. DFA a1 has also shown value for exercise load management in situations where standard intensity targets can be skewed such as eccentric cycling. Currently, several web sites and smartphone apps have been developed to track DFA a1 in retrospect or in real-time, making field assessment of physiologic exercise thresholds and internal load assessment practical. Although of value when viewed in isolation, DFA a1 tracking in combination with non-autonomic markers such as power/pace, open intriguing possibilities regarding athlete durability, identification of endurance exercise fatigue and optimization of daily training guidance.

Baroreceptor denervation reduces inflammatory status but worsens cardiovascular collapse during systemic inflammation

Beyond the regulation of cardiovascular function, baroreceptor afferents play polymodal roles in health and disease. Sepsis is a life-threatening condition characterized by systemic inflammation (SI) and hemodynamic dysfunction. We hypothesized that baroreceptor denervation worsens lipopolysaccharide (LPS) induced-hemodynamic collapse and SI in conscious rats. We combined: (a) hemodynamic and thermoregulatory recordings after LPS administration at a septic-like non-lethal dose (b) analysis of the cardiovascular complexity, (c) evaluation of vascular function in mesenteric resistance vessels, and (d) measurements of inflammatory cytokines (plasma and spleen). LPS-induced drop in blood pressure was higher in sino-aortic denervated (SAD) rats. LPS-induced hemodynamic collapse was associated with SAD-dependent autonomic disbalance. LPS-induced vascular dysfunction was not affected by SAD. Surprisingly, SAD blunted LPS-induced surges of plasma and spleen cytokines. These data indicate that baroreceptor afferents are key to alleviate LPS-induced hemodynamic collapse, affecting the autonomic control of cardiovascular function, without affecting resistance blood vessels. Moreover, baroreflex modulation of the LPS-induced SI and hemodynamic collapse are not dependent of each other given that baroreceptor denervation worsened hypotension and reduced SI.

Changes in the Complexity of Heart Rate Variability with Exercise Training Measured by Multiscale Entropy-Based Measurements

Quantifying complexity from heart rate variability (HRV) series is a challenging task, and multiscale entropy (MSE), along with its variants, has been demonstrated to be one of the most robust approaches to achieve this goal. Although physical training is known to be beneficial, there is little information about the long-term complexity changes induced by the physical conditioning. The present study aimed to quantify the changes in physiological complexity elicited by physical training through multiscale entropy-based complexity measurements. Rats were subject to a protocol of medium intensity training ( n = 13 ) or a sedentary protocol ( n = 12 ). One-hour HRV series were obtained from all conscious rats five days after the experimental protocol. We estimated MSE, multiscale dispersion entropy (MDE) and multiscale SDiff q from HRV series. Multiscale SDiff q is a recent approach that accounts for entropy differences between a given time series and its shuffled dynamics. From SDiff q , three attributes (q-attributes) were derived, namely SDiff q m a x , q m a x and q z e r o . MSE, MDE and multiscale q-attributes presented similar profiles, except for SDiff q m a x . q m a x showed significant differences between trained and sedentary groups on Time Scales 6 to 20. Results suggest that physical training increases the system complexity and that multiscale q-attributes provide valuable information about the physiological complexity.

Nonlinearities of heart rate variability in animal models of impaired cardiac control: contribution of different time scales

Heart rate variability (HRV) has been extensively explored by traditional linear approaches (e.g., spectral analysis); however, several studies have pointed to the presence of nonlinear features in HRV, suggesting that linear tools might fail to account for the complexity of the HRV dynamics. Even though the prevalent notion is that HRV is nonlinear, the actual presence of nonlinear features is rarely verified. In this study, the presence of nonlinear dynamics was checked as a function of time scales in three experimental models of rats with different impairment of the cardiac control: namely, rats with heart failure (HF), spontaneously hypertensive rats (SHRs), and sinoaortic denervated (SAD) rats. Multiscale entropy (MSE) and refined MSE (RMSE) were chosen as the discriminating statistic for the surrogate test utilized to detect nonlinearity. Nonlinear dynamics is less present in HF animals at both short and long time scales compared with controls. A similar finding was found in SHR only at short time scales. SAD increased the presence of nonlinear dynamics exclusively at short time scales. Those findings suggest that a working baroreflex contributes to linearize HRV and to reduce the likelihood to observe nonlinear components of the cardiac control at short time scales. In addition, an increased sympathetic modulation seems to be a source of nonlinear dynamics at long time scales. Testing nonlinear dynamics as a function of the time scales can provide a characterization of the cardiac control complementary to more traditional markers in time, frequency, and information domains.NEW & NOTEWORTHY Although heart rate variability (HRV) dynamics is widely assumed to be nonlinear, nonlinearity tests are rarely used to check this hypothesis. By adopting multiscale entropy (MSE) and refined MSE (RMSE) as the discriminating statistic for the nonlinearity test, we show that nonlinear dynamics varies with time scale and the type of cardiac dysfunction. Moreover, as complexity metrics and nonlinearities provide complementary information, we strongly recommend using the test for nonlinearity as an additional index to characterize HRV.

Complexity of cardiovascular rhythms during head-up tilt test by entropy of patterns

OBJECTIVE

The head-up tilt (HUT) test, which provokes transient dynamical alterations in the regulation of cardiovascular system, provides insights into complex organization of this system. Based on signals with heart period intervals (RR-intervals) and/or systolic blood pressure (SBP), differences in the cardiovascular regulation between vasovagal patients (VVS) and the healthy people group (CG) are investigated.

APPROACH

Short-term relations among signal data represented symbolically by three-beat patterns allow to qualify and quantify the complexity of the cardiovascular regulation by Shannon entropy. Four types of patterns: permutation, ordinal, deterministic and dynamical, are used, and different resolutions of signal values in the the symbolization are applied in order to verify how entropy of patterns depends on a way in which values of signals are preprocessed.

MAIN RESULTS

At rest, in the physiologically important signal resolution ranges, independently of the type of patterns used in estimates, the complexity of SBP signals in VVS is different from the complexity found in CG. Entropy of VVS is higher than CG what could be interpreted as substantial presence of noisy ingredients in SBP of VVS. After tilting this relation switches. Entropy of CG occurs significantly higher than VVS for SBP signals. In the case of RR-intervals and large resolutions, the complexity after the tilt becomes reduced when compared to the complexity of RR-intervals at rest for both groups. However, in the case of VVS patients this reduction is significantly stronger than in CG.

SIGNIFICANCE

Our observations about opposite switches in entropy between CG and VVS might support a hypothesis that baroreflex in VVS affects stronger the heart rate because of the inefficient regulation (possibly impaired local vascular tone alternations) of the blood pressure.

The role of sympathetic and vagal cardiac control on complexity of heart rate dynamics

Analysis of heart rate variability (HRV) by nonlinear approaches has been gaining interest due to their ability to extract additional information from heart rate (HR) dynamics that are not detectable by traditional approaches. Nevertheless, the physiological interpretation of nonlinear approaches remains unclear. Therefore, we propose long-term (60 min) protocols involving selective blockade of cardiac autonomic receptors to investigate the contribution of sympathetic and parasympathetic function upon nonlinear dynamics of HRV. Conscious male Wistar rats had their electrocardiogram (ECG) recorded under three distinct conditions: basal, selective (atenolol or atropine), or combined (atenolol plus atropine) pharmacological blockade of autonomic muscarinic or β1-adrenergic receptors. Time series of RR interval were assessed by multiscale entropy (MSE) and detrended fluctuation analysis (DFA). Entropy over short (1 to 5, MSE1–5) and long (6 to 30, MSE6–30) time scales was computed, as well as DFA scaling exponents at short (αshort, 5 ≤ n ≤ 15), mid (αmid, 30 ≤ n ≤ 200), and long (αlong, 200 ≤ n ≤ 1,700) window sizes. The results show that MSE1–5 is reduced under atropine blockade and MSE6–30 is reduced under atropine, atenolol, or combined blockade. In addition, while atropine expressed its maximal effect at scale six, the effect of atenolol on MSE increased with scale. For DFA, αshort decreased during atenolol blockade, while the αmid increased under atropine blockade. Double blockade decreased αshort and increased αlong. Results with surrogate data show that the dynamics during combined blockade is not random. In summary, sympathetic and vagal control differently affect entropy (MSE) and fractal properties (DFA) of HRV. These findings are important to guide future studies.

NEW & NOTEWORTHY Although multiscale entropy (MSE) and detrended fluctuation analysis (DFA) are recognizably useful prognostic/diagnostic methods, their physiological interpretation remains unclear. The present study clarifies the effect of the cardiac autonomic control on MSE and DFA, assessed during long periods (1 h). These findings are important to help the interpretation of future studies.

Molecular Mechanisms Linking Autonomic Dysfunction and Impaired Cardiac Contractility in Critical Illness

OBJECTIVES

Molecular mechanisms linking autonomic dysfunction with poorer clinical outcomes in critical illness remain unclear. We hypothesized that baroreflex dysfunction alone is sufficient to cause cardiac impairment through neurohormonal activation of (nicotinamide adenine dinucleotide phosphate oxidase dependent) oxidative stress resulting in increased expression of G-protein-coupled receptor kinase 2, a key negative regulator of cardiac function.

DESIGN

Laboratory/clinical investigations.

SETTING

University laboratory/medical centers.

SUBJECTS

Adult rats; wild-type/nicotinamide adenine dinucleotide phosphate oxidase subunit-2-deficient mice; elective surgical patients.

INTERVENTIONS

Cardiac performance was assessed by transthoracic echocardiography following experimental baroreflex dysfunction (sino-aortic denervation) in rats and mice. Immunoblots assessed G-protein-coupled receptor recycling proteins expression in rodent cardiomyocytes and patient mononuclear leukocytes. In surgical patients, heart rate recovery after cardiopulmonary exercise testing, time/frequency measures of parasympathetic variables were related to the presence/absence of baroreflex dysfunction (defined by spontaneous baroreflex sensitivity of <6 ms mm Hg). The associations of baroreflex dysfunction with intraoperative cardiac function and outcomes were assessed.

MEASUREMENTS AND MAIN RESULTS

Experimental baroreflex dysfunction in rats and mice resulted in impaired cardiac contractility and upregulation of G-protein-coupled receptor kinase 2 expression. In mice, genetic deficiency of gp91 nicotinamide adenine dinucleotide phosphate oxidase subunit-2 prevented upregulation of G-protein-coupled receptor kinase 2 expression in conditions of baroreflex dysfunction and preserved cardiac function. Baroreflex dysfunction was present in 81 of 249 patients (32.5%) and was characterized by lower parasympathetic tone and increased G-protein-coupled receptor kinase 2 expression in mononuclear leukocytes. Baroreflex dysfunction in patients was also associated with impaired intraoperative cardiac contractility. Critical illness and mortality were more frequent in surgical patients with baroreflex dysfunction (relative risk, 1.66 [95% CI, 1.16-2.39]; p = 0.006).

CONCLUSIONS

Reduced baroreflex sensitivity is associated with nicotinamide adenine dinucleotide phosphate oxidase subunit-2-mediated upregulation of G-protein-coupled receptor kinase 2 expression in cardiomyocytes and impaired cardiac contractility. Autonomic dysfunction predisposes patients to the development of critical illness and increases mortality.

Correlation between RR, inter-systolic and inter-diastolic intervals and their differences for the analysis of spontaneous heart rate variability

Analysis of heart rate variability (HRV) is performed through interbeat interval time series derived from either electrocardiographic or arterial pressure (AP) recordings. However, little attention has been given to the reliability of calculating the time series from different sources, i.e. electrocardiogram (ECG) or pulse intervals (PI). Therefore, the present study aimed to evaluate the correlation between interbeat interval time series obtained from RR, inter-systolic (SS) and inter-diastolic (DD) intervals, as well as their impact on indices of HRV calculated from series of RR or PI. Conscious rats previously instrumented with subcutaneous electrodes and a catheter into the femoral artery were subjected to simultaneous ECG and AP recording for 5 min. Correlation and Bland-Altman plots between RR and PI were evaluated. Moreover, HRV was analyzed in time (mean cardiac interval, SDNN and RMSSD) and frequency domain (power in LF and HF spectral bands) as well as by nonlinear approaches (symbolic dynamics and sample entropy). First, RR showed a stronger correlation with PI calculated by DD than SS. Second, most HRV indices showed similar results when calculated with RR or DD series, but not with SS series. Considering RR interval as the gold standard for the calculation of cardiac cycle, when using PI inter diastolic intervals are the better choice to study HRV. These findings are quite relevant, especially when AP recording is used for HRV analysis.

Multiscale entropy analysis of heart rate variability in heart failure, hypertensive, and sinoaortic-denervated rats: classical and refined approaches

The analysis of heart rate variability (HRV) by nonlinear methods has been gaining increasing interest due to their ability to quantify the complexity of cardiovascular regulation. In this study, multiscale entropy (MSE) and refined MSE (RMSE) were applied to track the complexity of HRV as a function of time scale in three pathological conscious animal models: rats with heart failure (HF), spontaneously hypertensive rats (SHR), and rats with sinoaortic denervation (SAD). Results showed that HF did not change HRV complexity, although there was a tendency to decrease the entropy in HF animals. On the other hand, SHR group was characterized by reduced complexity at long time scales, whereas SAD animals exhibited a smaller short- and long-term irregularity. We propose that short time scales (1 to 4), accounting for fast oscillations, are more related to vagal and respiratory control, whereas long time scales (5 to 20), accounting for slow oscillations, are more related to sympathetic control. The increased sympathetic modulation is probably the main reason for the lower entropy observed at high scales for both SHR and SAD groups, acting as a negative factor for the cardiovascular complexity. This study highlights the contribution of the multiscale complexity analysis of HRV for understanding the physiological mechanisms involved in cardiovascular regulation.