1,721,029 research outputs found
Letter by Moderato et al Regarding Article, "Persistent Long-Term Structural, Functional, and Metabolic Changes After Stress-Induced (Takotsubo) Cardiomyopathy"
No full textSodium intake and hypertension
Full text linkThe close relationship between hypertension and dietary sodium intake is widely recognized and supported by several studies. A reduction in dietary sodium not only decreases the blood pressure and the incidence of hypertension, but is also associated with a reduction in morbidity and mortality from cardiovascular diseases. Prolonged modest reduction in salt intake induces a relevant fall in blood pressure in both hypertensive and normotensive individuals, irrespective of sex and ethnic group, with larger falls in systolic blood pressure for larger reductions in dietary salt. The high sodium intake and the increase in blood pressure levels are related to water retention, increase in systemic peripheral resistance, alterations in the endothelial function, changes in the structure and function of large elastic arteries, modification in sympathetic activity, and in the autonomic neuronal modulation of the cardiovascular system. In this review, we have focused on the effects of sodium intake on vascular hemodynamics and their implication in the pathogenesis of hypertensio
Assessing sodium sensitivity in clinical practice: new insights from ambulatory blood pressure monitoring data.
No full textMultifractal-Multiscale Analysis of Cardiovascular Signals: A DFA-Based Characterization of Blood Pressure and Heart-Rate Complexity by Gender
No full textDetrended Fluctuation Analysis (DFA) is a popular method for assessing the fractal characteristics of biosignals, recently adapted for evaluating the heart-rate multifractal and/or multiscale characteristics. However, the existing methods do not consider the beat-by-beat sampling of heart rate and have relatively low scale resolutions and were not applied to cardiovascular signals other than heart rate. Therefore, aim of this work is to present a DFA-based method for joint multifractal/multiscale analysis designed to address the above critical points and to provide the first description of the multifractal/multiscale structure of interbeat intervals (IBI), systolic blood pressure (SBP), and diastolic blood pressure (DBP) in male and female volunteers separately. The method optimizes data splitting in blocks to reduce the DFA estimation variance and to evaluate scale coefficients with Taylor's expansion formulas and maps the scales from beat domains to temporal domains. Applied to cardiovascular signals recorded in 42 female and 42 male volunteers, it showed that scale coefficients and degree of multifractality depend on the temporal scale, with marked differences between IBI, SBP, and DBP and with significant sex differences. Results may be interpreted considering the distinct physiological mechanisms regulating heart-rate and blood-pressure dynamics and the different autonomic profile of males and females
Multiscale Sample Entropy of Cardiovascular Signals: Does the Choice between Fixed- or Varying-Tolerance among Scales Influence Its Evaluation and Interpretation?
No full textMultiscale entropy (MSE) quantifies the cardiovascular complexity evaluating Sample Entropy (SampEn) on coarse-grained series at increasing scales tau. Two approaches exist, one using a fixed tolerance r at all scales (MSEFT), the other a varying tolerance r(tau) adjusted following the standard-deviation changes after coarse graining (MSEVT). The aim of this study is to clarify how the choice between MSEFT and MSEVT influences quantification and interpretation of cardiovascular MSE, and whether it affects some signals more than others. To achieve this aim, we considered 2-h long beat-by-beat recordings of inter-beat intervals and of systolic and diastolic blood pressures in male (N = 42) and female (N = 42) healthy volunteers. We compared MSE estimated with fixed and varying tolerances, and evaluated whether the choice between MSEFT and MSEVT estimators influence quantification and interpretation of sex-related differences. We found substantial discrepancies between MSEFT and MSEVT results, related to the degree of correlation among samples and more important for heart rate than for blood pressure; moreover the choice between MSEFT and MSEVT may influence the interpretation of gender differences for MSE of heart rate. We conclude that studies on cardiovascular complexity should carefully choose between fixed-or varying-tolerance estimators, particularly when evaluating MSE of heart rate
Multiscale sample entropy of heart rate and blood pressure: methodological aspects
No full textThe entropy of heart rate variability is one of the main features characterizing the complexity of the cardiovascular system. In order to take into account the multiscale nature of cardiovascular regulation, it was proposed to evaluate entropy with a multiscale approach, based on the estimation of Sample Entropy on progressively coarse-grained series (Multiscale Sample Entropy, MSE). Aim of this work is to investigate two methodological aspects related to MSE of cardiovascular signals. The first aspect regards the tolerance below which a couple of points are considered similar in a given embedding dimension, in particular how the way the tolerance is set at each level of coarse graining influences the MSE estimates. The second aspect regards whether heart rate and blood pressure (BP) signals are characterized by different MSE structures.To investigate these aspects, we analyzed 65 continuous BP recordings of more than 90-minute duration in healthy volunteers sitting at rest, and applied MSE estimators to beat-by-beat series of systolic BP, diastolic BP and pulse interval (inverse of heart rate). Results indicate that the way the tolerance is set during coarse graining influences substantially the MSE profile of cardiovascular signals, modifying the relative level of their unpredictability
Multifractal multiscale dfa of cardiovascular time series: Differences in complex dynamics of systolic blood pressure, diastolic blood pressure and heart rate
No full textThe heart-rate fractal dynamics can be assessed by Detrended Fluctuation Analysis (DFA), originally proposed for estimating a short-term coefficient, α1 (for scales n≤12 beats), and a long-term coefficient α2 (for longer scales). Successively, DFA was extended to provide a multiscale α, i.e. a continuous function of n, α(n); or a multifractal α, i.e. a function of the order q of the fluctuations moment, α(q). Very recently, a multifractal-multiscale DFA was proposed for evaluating multifractality at different scales separately. Aim of this work is to describe the multifractal multiscale dynamics of three cardiovascular signals often recorded beat by beat in physiological and clinical settings: systolic blood pressure (SBP), diastolic blood pressure (DBP) and pulse interval (PI, inverse of the heart rate). We recorded SBP, DBP and PI for at least 90' in 65 healthy volunteers at rest, and adapted the previously proposed multifractal multiscale DFA to estimate α as function of the temporal scale, τ, between 15 and 450 s, and of the order q, between -5 and 5. We report, for the first time: 1) substantial differences among α(q,τ) surfaces of PI, SBP and DBP; 2) a strong dependency of the degree of multifractality on the temporal scale
Sex Differences in Heart Rate Nonlinearity by Multifractal Multiscale Detrended Fluctuation Analysis
No full textRecent developments of detrended fluctuation analysis (DFA) provide multifractal/multiscale (MFMS) descriptions of the heart rate self-similarity, a promising approach to cardiovascular complexity. However, it is unclear whether the MFMS DFA may also describe the nonlinear components of heart rate variability. Our aim is to define MFMS DFA indices for quantifying the short-term and long-term degree of the heart-rate nonlinearity and to apply these indices to detect possible sex-related differences.We recorded the inter-beat-interval (IBI) series in 42 male and in 42 female healthy participants sitting at rest for about 2 hours. For each series j, we generated 100 phase-randomized surrogate series. We applied the MFMS DFA to estimate the self-similarity coefficients α over scales τ between 8 and 512 s and moment orders q between -5 and +5, obtaining coefficients for the original series, αO,j (q, τ), and for each surrogate, αi,j (q, τ) with 1≤i≤100. We first evaluated πj(q, τ), percentile of αi,j (q, τ) distribution in which was αO,j (q, τ). Then we calculated the percentages of scales where πj(q, τ) was <5% for 8≤τ≤16 s (short-term nonlinearity index NL1(q)) and for 16≤τ≤512 s (long-term nonlinearity index NL2(q)). We found that NL1(q) was generally greater than 50% at all q≥0 but q=2 (i.e., moment order of the monofractal DFA), while at q<0 it was high in males only, with significant sex differences at q=-1 and q=-2. Results indicate that the multifractal DFA may highlight nonlinear heart-rate components at the short scales that are not revealed by the traditional monofractal DFA and that appear related to gender differences.Clinical Relevance - This supports the use of MFMS DFA to integrate the linear information from traditional spectral methods of heart rate variability in clinical studies aimed at improving the stratification of the cardiovascular risk
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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