Heart rate variability (HRV) analysis represents an important tool for the characterization of complex cardiovascular control. HRV indexes are usually calculated from electrocardiographic (ECG) recordings after measuring the time duration between consecutive R peaks, and this is considered the gold standard. An alternative method consists of assessing the Pulse Rate Variability (PRV) from signals acquired through photoplethysmography, a technique also employed for the continuous noninvasive monitoring of blood pressure. In this work, we carry out a thorough analysis and comparison of short term variability indexes computed from HRV time series obtained from the ECG and from PRV time series obtained from continuous blood pressure (CBP) signals, in order to evaluate the reliability of using CBP-based recordings in place of standard ECG tracks. The analysis has been carried out on short time series (300 beats) of HRV and PRV in 76 subjects studied in different conditions: resting in the supine position, postural stress during 45° head-up tilt, and mental stress during computation of arithmetic test. Nine different indexes have been taken into account, computed in the time domain (mean, variance, root mean square of the successive differences), frequency domain (low-to-high frequency power ratio LF/HF, HF spectral power and central frequency) and information domain (entropy, conditional entropy, self entropy). Thorough validation has been performed using comparison of the HRV and PRV distributions, robust linear regression, and Bland-Altman plots. Results demonstrate the feasibility of extracting HRV indexes from CBP-based data, showing an overall relatively good agreement of time, frequency, and information domain measures. The agreement decreased during postural and mental arithmetic stress, especially with regard to band-power ratio, conditional and self entropy. This finding suggests to use caution in adopting PRV as a surrogate of HRV during stress conditions.

The study of short-term cardiovascular interactions is classically performed through the bivariate analysis of the interactions between the beat-to-beat variability of heart period (RR interval from the ECG) and systolic blood pressure (SBP). Recent progress in the development of multivariate time series analysis methods is making it possible to explore how directed interactions between two signals change in the context of networks including other coupled signals. Exploiting these advances, the present study aims at assessing directional cardiovascular interactions among the basic variability signals of RR, SBP and diastolic blood pressure (DBP), using an approach which allows direct comparison between bivariate and multivariate coupling measures. To this end, we compute information-theoretic measures of the strength and delay of causal interactions between RR, SBP and DBP using both bivariate and trivariate (conditioned) formulations in a group of healthy subjects in a resting state and during stress conditions induced by head-up tilt (HUT) and mental arithmetics (MA). We find that bivariate measures better quantify the overall (direct  +  indirect) information transferred between variables, while trivariate measures better reflect the existence and delay of directed interactions. The main physiological results are: (i) the detection during supine rest of strong interactions along the pathway RR  →  DBP  →  SBP, reflecting marked Windkessel and/or Frank-Starling effects; (ii) the finding of relatively weak baroreflex effects SBP  →  RR at rest; (iii) the invariance of cardiovascular interactions during MA, and the emergence of stronger and faster SBP  →  RR interactions, as well as of weaker RR  →  DBP interactions, during HUT. These findings support the importance of investigating cardiovascular interactions from a network perspective, and suggest the usefulness of directed information measures to assess physiological mechanisms and track their changes across different physiological states.

Heart rate variability (HRV; variability of the RR interval of the electrocardiogram) results from the activity of several coexisting control mechanisms, which involve the influence of respiration (RESP) and systolic blood pressure (SBP) oscillations operating across multiple temporal scales and changing in different physiological states. In this study, multiscale information decomposition is used to dissect the physiological mechanisms related to the genesis of HRV in 78 young volunteers monitored at rest and during postural and mental stress evoked by head-up tilt (HUT) and mental arithmetics (MA). After representing RR, RESP and SBP at different time scales through a recently proposed method based on multivariate state space models, the joint information transfer T RESP , SBP → RR is decomposed into unique, redundant and synergistic components, describing the strength of baroreflex modulation independent of respiration ( U SBP → RR ), nonbaroreflex ( U RESP → RR ) and baroreflex-mediated ( R RESP , SBP → RR ) respiratory influences, and simultaneous presence of baroreflex and nonbaroreflex respiratory influences ( S RESP , SBP → RR ), respectively. We find that fast (short time scale) HRV oscillations—respiratory sinus arrhythmia—originate from the coexistence of baroreflex and nonbaroreflex (central) mechanisms at rest, with a stronger baroreflex involvement during HUT. Focusing on slower HRV oscillations, the baroreflex origin is dominant and MA leads to its higher involvement. Respiration influences independent on baroreflex are present at long time scales, and are enhanced during HUT.

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Our results document the importance of employing a network perspective in the evaluation of the short-term complexity of cardiovascular and respiratory dynamics across different physiological states.

Aim: Motivated by the paradoxical and differing results of the early atherosclerosis related indices – Cardio-Ankle Vascular Index (CAVI) reflecting arterial stiffness and Reactive Hyperemia Index (RHI) evaluating endothelium dependent flow-induced vasodilation – in obesity, we aimed to assess CAVI and RHI in obese adolescents and young adults in the context of differences in systemic vascular resistance (SVR).Methods: We examined 29 obese (14f, 15.4 [12.3–18.5] y; BMI: 33.2 ± 4.4 kg.m−2) and 29 non-obese gender and age matched adolescents and young adults (BMI: 21.02 ± 2.3 kg.m−2). CAVI and RHI were measured using VaSera VS-1500 (Fukuda Denshi, Japan) and Endo-PAT 2000 (Itamar Medical, Israel), respectively. Hemodynamic measures were recorded using volume-clamp plethysmography (Finometer Pro, FMS, Netherlands) and impedance cardiography (CardioScreen 2000, Medis GmbH, Germany). SVR and sympathetic activity related indices – Velocity Index (VI) and Heather Index (HI), and LFSAP (spectral power in low frequency band of systolic blood pressure oscillations) were determined.Results: In obese group, CAVI (4.59 ± 0.88 vs. 5.18 ± 0.63, p = 0.002) and its refined version CAVI0 (6.46 ± 1.39 vs. 7.33 ± 0.99, p = 0.002) were significantly lower. No significant difference in RHI was found. SVR and sympathetic activity indices were all significantly lower in the obese group than in the non-obese group. RHI correlated positively with SVR (r = 0.390, p = 0.044) in obese subjects.Conclusion: Our results indicate that both indices used for the detection of early atherosclerotic changes are influenced by vascular tone. Vascular resistance could influence CAVI and RHI results impairing their interpretation.

In previous studies, one of the systolic time intervals – preejection period (PEP) – was used as an index of sympathetic activity reflecting the cardiac contractility. However, PEP could be also influenced by several other cardiovascular variables including preload, afterload and diastolic blood pressure (DBP). The aim of this study was to assess the behavior of the PEP together with other potentially confounding cardiovascular system characteristics in healthy humans during mental and orthostatic stress (head-up tilt test – HUT). Forty-nine healthy volunteers (28 females, 21 males, mean age 18.6 years (SD=1.8 years)) participated in the study. We recorded finger arterial blood pressure by volume-clamp method (Finometer Pro, FMS, Netherlands), PEP, thoracic fluid content (TFC) – a measure of preload, and cardiac output (CO) by impedance cardiography (CardioScreen® 2000, Medis, Germany). Systemic vascular resistance (SVR) – a measure of afterload – was calculated as a ratio of mean arterial pressure and CO. We observed that during HUT, an expected decrease in TFC was accompanied by an increase of PEP, an increase of SVR and no significant change in DBP. During mental stress, we observed a decrease of PEP and an increase of TFC, SVR and DBP. Correlating a change in assessed measures (delta values) between mental stress and previous supine rest, we found that ΔPEP correlated negatively with ΔCO and positively with ΔSVR. In orthostasis, no significant correlation between ΔPEP and ΔDBP, ΔTFC, ΔCO, ΔMBP or ΔSVR was found. We conclude that despite an expected increase of sympathetic activity during both challenges, PEP behaved differently indicating an effect of other confounding factors. To interpret PEP values properly, we recommend simultaneously to measure other variables influencing this cardiovascular measure.

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