Cardiac Baroreflex, HRV, and Statistics: An Interdisciplinary Approach in Hypertension

Interests about the fine underpinnings of cardiovascular beat-by-beat variability have historical roots. Over the last decades, various aspects of the relationships between arterial pressure and heart period were taken as a proxy of the baroreflex in physiology and medicine, stimulating the interest of investigators in several interconnected scientific fields, in particular, bioengineering, neurophysiology, and clinical medicine. Studies of the overall system facilitated the emergence of a simplified negative (vagal) feedback model of the baroreflex and overshadowed the simultaneous interaction with excitatory, sympathetic positive-feedback mechanisms that would, however, better suit the model of a “paired antagonistic (parasympathetic/sympathetic) innervation of the internal organs.” From the bioengineering side, the simplicity of obtaining the series of subsequent RR intervals stimulated the analysis of beat-by-beat variations, providing a multitude of heart rate variability (HRV) indices considered as proxies of the underlying sympatho-vagal balance, and participating to the management of several important clinical conditions, such as hypertension. In this context, advanced statistical methods, used in an integrated manner and controlling for age and gender biases, might help shed new light on the relationship between cardiac baroreflex, assessed by the frequency domain index α, and the HRV indices with the varying of systolic arterial pressure (SAP) levels. The focus is also on a novel unitary Autonomic Nervous System Index (ANSI) built as a synthesis of HRV considering its three most informative proxies [RR, RR variance, and the rest-stand difference in the normalized power of low-frequency (LF) variability component]. Data from a relatively large set of healthy subjects (n = 1154) with a broad range of SAP [from normal (nNt = 778) to elevated (nHt = 232)] show that, e.g., α and ANSI significantly correlate overall (r = 0.523, p < 0.001), and that this correlation is lower in hypertensives (r = 0.444, p < 0.001) and higher in pre-hypertensives (r = 0.618, p < 0.001) than in normotensives (r = 0.5, p < 0.001). That suggests the existence of curvilinear “umbrella” patterns that might better describe the effects of the SAP states on the relationships between baroreflex and HRV. By a mix of robust, non-parametric and resampling statistical techniques, we give empirical support to this study hypothesis and show that the pre-hypertensive group results at the apex/bottom in most of the studied trends

Robustness of Parameter Estimation Procedures in Multilevel Models When Random Effects are MEP Distributed

Hierarchical data, ML and REML estimation, Multivariate exponential power distribution,

Autonomic Differentiation Map: A Novel Statistical Tool for Interpretation of Heart Rate Variability

In spite of the large body of evidence suggesting Heart Rate Variability (HRV) alone or combined with blood pressure variability (providing an estimate of baroreflex gain) as a useful technique to assess the autonomic regulation of the cardiovascular system, there is still an ongoing debate about methodology, interpretation, and clinical applications. In the present investigation, we hypothesize that non-parametric and multivariate exploratory statistical manipulation of HRV data could provide a novel informational tool useful to differentiate normal controls from clinical groups, such as athletes, or subjects affected by obesity, hypertension, or stress. With a data-driven protocol in 1,352 ambulant subjects, we compute HRV and baroreflex indices from short-term data series as proxies of autonomic (ANS) regulation. We apply a three-step statistical procedure, by first removing age and gender effects. Subsequently, by factor analysis, we extract four ANS latent domains that detain the large majority of information (86.94%), subdivided in oscillatory (40.84%), amplitude (18.04%), pressure (16.48%), and pulse domains (11.58%). Finally, we test the overall capacity to differentiate clinical groups vs. control. To give more practical value and improve readability, statistical results concerning individual discriminant ANS proxies and ANS differentiation profiles are displayed through peculiar graphical tools, i.e., significance diagram and ANS differentiation map, respectively. This approach, which simultaneously uses all available information about the system, shows what domains make up the difference in ANS discrimination. e.g., athletes differ from controls in all domains, but with a graded strength: maximal in the (normalized) oscillatory and in the pulse domains, slightly less in the pressure domain and minimal in the amplitude domain. The application of multiple (non-parametric and exploratory) statistical and graphical tools to ANS proxies defines differentiation profiles that could provide a better understanding of autonomic differences between clinical groups and controls. ANS differentiation map permits to rapidly and simply synthesize the possible difference between clinical groups and controls, evidencing the ANS latent domains that have at least a medium strength of discrimination, while the significance diagram permits to identify the single ANS proxies inside each ANS latent domain that resulted in significant comparisons according to statistical tests

Robustness of parameter estimation procedures in multilevel models when random effects are MEP distributed

In this paper we examine maximum likelihood estimation procedures in multilevel models for two level nesting structures. Usually, for fixed effects and variance components estimation, level-one error terms and random effects are assumed to be normally distributed. Nevertheless, in some circumstances this assumption might not be realistic, especially as concerns random effects. Thus we assume for random effects the family of multivariate exponential power distributions (MEP); subsequently, by means of Monte Carlo simulation procedures, we study robustness of maximum likelihood estimators under normal assumption when, actually, random effects are MEP distributed.Hierarchical data, ML and REML estimation, Multilevel model, Multivariate exponential power distribution,

Table1_Autonomic Differentiation Map: A Novel Statistical Tool for Interpretation of Heart Rate Variability.DOCX

<p>In spite of the large body of evidence suggesting Heart Rate Variability (HRV) alone or combined with blood pressure variability (providing an estimate of baroreflex gain) as a useful technique to assess the autonomic regulation of the cardiovascular system, there is still an ongoing debate about methodology, interpretation, and clinical applications. In the present investigation, we hypothesize that non-parametric and multivariate exploratory statistical manipulation of HRV data could provide a novel informational tool useful to differentiate normal controls from clinical groups, such as athletes, or subjects affected by obesity, hypertension, or stress. With a data-driven protocol in 1,352 ambulant subjects, we compute HRV and baroreflex indices from short-term data series as proxies of autonomic (ANS) regulation. We apply a three-step statistical procedure, by first removing age and gender effects. Subsequently, by factor analysis, we extract four ANS latent domains that detain the large majority of information (86.94%), subdivided in oscillatory (40.84%), amplitude (18.04%), pressure (16.48%), and pulse domains (11.58%). Finally, we test the overall capacity to differentiate clinical groups vs. control. To give more practical value and improve readability, statistical results concerning individual discriminant ANS proxies and ANS differentiation profiles are displayed through peculiar graphical tools, i.e., significance diagram and ANS differentiation map, respectively. This approach, which simultaneously uses all available information about the system, shows what domains make up the difference in ANS discrimination. e.g., athletes differ from controls in all domains, but with a graded strength: maximal in the (normalized) oscillatory and in the pulse domains, slightly less in the pressure domain and minimal in the amplitude domain. The application of multiple (non-parametric and exploratory) statistical and graphical tools to ANS proxies defines differentiation profiles that could provide a better understanding of autonomic differences between clinical groups and controls. ANS differentiation map permits to rapidly and simply synthesize the possible difference between clinical groups and controls, evidencing the ANS latent domains that have at least a medium strength of discrimination, while the significance diagram permits to identify the single ANS proxies inside each ANS latent domain that resulted in significant comparisons according to statistical tests.</p

Relationship between Body Composition and Cardiac Autonomic Regulation in a Large Population of Italian Olympic Athletes

Athletic performance is determined by many factors, such as cardiorespiratory fitness, muscular strength and psychological features, which all interact simultaneously. The large Italian National Olympic Committee database of Olympic athletes offers a unique healthy population to verify the strength of the interplay among a number of major elements of training, including autonomic nervous system (ANS) modulation, biochemical indicators and body composition, in a system medicine approach. This observational, retrospective study involved 583 individuals. As part of the yearly precompetitive examination, cardiac autonomic (heart rate variability), psychological, physical (cycloergometer stress test), biochemical and body composition (BOD POD) evaluations were performed. In subsequent analysis, we first considered the relationship between body composition and single individual variables in a simple correlation matrix, including a multitude of variables; then, Exploratory Factor Analysis (EFA) restricted the information to six latent domains, each combining congruent information in relation to body composition. Finally, we employed a multiple quantile regression model to evaluate possible relationships between ANSIs (index capable of synthetizing ANS regulation) and the latent domains indicated by EFA reflecting body composition. We observed a clear relationship between ANS and body mass composition parameters, as indicated by both bivariate correlations and the quantile regression result of ANSIs versus the latent domain aggregating mainly body composition data expressed in % (p = 0.002). In conclusion, these results suggest that specific training may elicit parallel adaptation of ANS control and body composition. The analysis of Olympic athletes&rsquo; data allowed us to obtain a better understanding of the complex, multidimensional factors involved in determining sport performance. The latter appears to be determined by the simultaneous interaction not only of cardiorespiratory fitness, muscular strength and psychological features, but also of ANS cardiovascular modulation and body composition

Psychological Intervention Based on Mental Relaxation to Manage Stress in Female Junior Elite Soccer Team: Improvement in Cardiac Autonomic Control, Perception of Stress and Overall Health

Chronic stress may represent one of the most important factors that negatively affects the health and performance of athletes. Finding a way to introduce psychological strategies to manage stress in everyday training routines is challenging, particularly in junior teams. We also must consider that a stress management intervention should be regarded as “efficacious” only if its application results in improvement of the complex underlying pathogenetic substratum, which considers mechanistically interrelated factors, such as immunological, endocrine and autonomic controls further to psychological functioning and behavior. In this study, we investigated the feasibility of implementing, in a standard training routine of the junior team of the Italian major soccer league, a stress management program based on mental relaxation training (MRT). We evaluated its effects on stress perception and cardiac autonomic regulation as assessed by means of ANSI, a single composite percentile-ranked proxy of autonomic balance, which is free of gender and age bias, economical, and simple to apply in a clinical setting. We observed that the simple employed MRT intervention was feasible in a female junior soccer team and was associated with a reduced perception of stress, an improved perception of overall health, and a betterment of cardiac autonomic control. This data may corroborate the scientific literature that indicates psychological intervention based on MRT as an efficacious strategy to improve performance, managing negative stress effects on cardiac autonomic control

Endothelial progenitor cell secretome delivered by novel polymeric nanoparticles in ischemic hindlimb

Endothelial progenitor cells (EPCs) contribute to ischemic tissue repair by paracrine secretion up-regulated by hypoxia. In this study we use novel nanoparticles (NPs) as carriers for a controlled release of EPC secretome (CM) to improve their angiogenic properties. The in vivo effect in ischemic hindlimb rat model was evaluated, comparing hypoxic EPC-CM-NPs with hypoxic EPC-CM alone. A proteomic characterization of hypoxic CM and the in vitro effect on endothelial cells (HUVECs) were also performed. Up to 647 protein, 17 of which with angiogenic properties, were upregulated by hypoxia. Moreover, hypoxic EPC-CM significantly promoted capillary-like structures on Matrigel. A significant increase of blood perfusion in ischemic limbs at 2 weeks with EPC-CM-loaded NPs as compared to both EPC-CM and control and a significant increase of capillary formation were observed. The use of EPC-CM-NPs significantly improved neoangiogenesis in vivo, underlining the advantages of controlled release in regenerative medicine