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Objective. The percentages of cardiac and sympathetic baroreflex patterns detected via baroreflex sequence (SEQ) technique from spontaneous variability of heart period (HP) and systolic arterial pressure (SAP) and of muscle nerve sympathetic activity (MSNA) burst rate and diastolic arterial pressure (DAP) are utilized to assess the level of the baroreflex engagement. The cardiac baroreflex patterns can be distinguished in those featuring both HP and SAP increases (cSEQ++) and decreases (cSEQ--), while the sympathetic baroreflex patterns in those featuring a MSNA burst rate decrease and a DAP increase (sSEQ+-) and vice versa (sSEQ-+). The present study aims to assess the modifications of the involvement of the cardiac and sympathetic arms of the baroreflex with age and postural stimulus intensity. Approach. We monitored the percentages of cSEQ++ (%cSEQ++) and cSEQ-- (%cSEQ--) in 100 healthy subjects (age: 21-70 years, 54 males, 46 females), divided into five sex-balanced groups consisting of 20 subjects in each decade at rest in supine position and during active standing (STAND). We evaluated %cSEQ++, %cSEQ--, and the percentages of sSEQ+- (%sSEQ+-) and sSEQ-+ (%sSEQ-+) in 12 young healthy subjects (age 23 ± 2 years, 3 females, 9 males) undergoing incremental head-up tilt. Main results. We found that: (i) %cSEQ++ and %cSEQ-- decreased with age and increased with STAND and postural stimulus intensity; (ii) %sSEQ+- and %sSEQ-+ augmented with postural challenge magnitude; (iii) the level of cardiac and sympathetic baroreflex engagement did not depend on either the absolute value of arterial pressure or the direction of its changes. Significance. This study stresses the limited ability of the cardiac and sympathetic arms of the baroreflex in controlling absolute arterial pressure values and the equivalent ability of both positive and negative arterial pressure changes in soliciting them., (Creative Commons Attribution license.)

Objective. Closed loop cardiovascular (CV) and cerebrovascular (CBV) variability interactions are assessed via transfer entropy (TE) from systolic arterial pressure (SAP) to heart period (HP) and vice versa and from mean arterial pressure (MAP) to mean cerebral blood velocity (MCBv) and vice versa. This analysis is exploited to assess the efficiency of baroreflex and cerebral autoregulation. This study aims at characterizing CV and CBV controls in postural orthostatic tachycardiac syndrome (POTS) subjects experiencing exaggerated sympathetic response during orthostatic challenge via unconditional TE and TE conditioned on respiratory activity ( R ). Approach. In 18 healthy controls (age: 28 ± 13 yrs; 5 males, 13 females) and 15 POTS individuals (age: 29 ± 11 yrs; 3 males, 12 females) we acquired beat-to-beat variability of HP, SAP, MAP and MCBv and two R signals, namely respiratory chest movement (RCM) and capnogram (CAP). Recordings were made at sitting rest and during active standing (STAND). TE was computed via vector autoregressive approach. Main results. We found that: (i) when assessing CV interactions, the increase of the TE from SAP to HP during STAND, indicating baroreflex activation, is detected solely when conditioning on RCM; (ii) when assessing CBV interactions, the impact of R on the TE computation is negligible; (iii) POTS shows baroreflex impairment during STAND; (iv) POTS exhibits a normal CBV response to STAND. Significance. TE is useful for detecting the impairment of specific regulatory mechanisms in POTS. Moreover, using different R signals highlights the sensitivity of CV and CBV controls to specific R aspects., (Creative Commons Attribution license.)

Objective . Beat-to-beat fluctuations in the QT interval-QT variability (QTV)-have been shown to vary amongst the different ECG leads. This study aims to compare the utility of single and multi-lead ECG to disentangle the mechanisms contributing to QTV. Approach . Twelve-lead ECG was analysed in 57 coronary artery disease patients before and after an elective percutaneous transluminal coronary angiography (PTCA) procedure. QT, RR and respiration time series were extracted. QTV was decomposed into contributions by heart rate, respiration and QTV independent of heart rate and respiration using parametric autoregressive modelling. Signal-to-noise ratio, model goodness-of-fit, mean QT, corrected QT, QT variability and RR variability were also computed. Results from two single leads (Lead II and V5) and three one-dimensional representations of 12-lead ECG (principal component analysis (PCA), vector magnitude (VM), and root mean square of the 8 independent leads of the standard 12 leads (RMS8)) were compared during resting conditions, before and after PTCA, and between patients with myocardial infarction and those without. Main results . At baseline, mean QT and corrected QT were significantly lower in VM and RMS8 compared to single leads. While overall QT variability was not different between the leads, QT independent of heart rate and respiration was significantly lower in VM and RMS8. Following PTCA, changes in these variables were similar in all leads. Differences between patients with MI and those without MI were consistent in all leads. Significance . Despite the differences in some QTV components amongst various leads, single-lead ECG could be sufficient for analyzing QTV in populations with pathological cardiovascular conditions compared to those without, or for quantification of intervention effects., (© 2022 Institute of Physics and Engineering in Medicine.)

Objective: A network physiology approach to evaluate the strength of the directed interactions among cardiac controls at sinoatrial and ventricular levels and respiration (R) is proposed., Approach: The network is composed of three nodes (i.e. sinoatrial and ventricular cardiac controls and R) and their activity is exemplified by the variability of heart period (HP), the variability of the duration of the electrical activity of the heart approximated as the temporal distance between Q-wave onset and T-wave end or apex (i.e. QTe or QTa) and thoracic movements respectively. Model-based transfer entropy provided the estimate of the strength of the causal link from the source to the destination conditioned on the remaining node activity. The interactions were monitored in 15 healthy subjects aged from 24 to 54 years (9 males). Increasing levels of sympathetic activity were induced by graded head-up tilt with table inclination of 0, 15, 30, 45, 60, 75°., Main Results: We found that: (i) the strength of the causal link from HP to QTe gradually decreases with tilt table angle, while that in the reverse direction is weak, even though significant, and constant; (ii) the action of R on HP is stronger than that from R to QTe; (iii) the strength of the relation from R to HP is weakly related to tilt table inclination, while that from R to QTe does not depend on it; (iv) while QTe cannot affect R, a weak causal dependence of R on HP is detected; (v) the network computed over QTa is qualitatively similar to that over QTe, even though the strength of the causal relations might be different., Significance: The proposed network physiology approach provides a comprehensive picture of the directed links among relevant cardiac regulatory mechanisms and their evolution with sympathetic tone usable to identify pathological conditions.

Beat-to-beat variability of the QT interval (QTV) measured on surface ECG has emerged as a potential marker for ventricular repolarization instability and has been used along with heart rate variability (HRV) to predict arrhythmic risk. Since measurement modalities of QTV have not been standardized, the objective of this study was to investigate the effect of ECG recording duration on QTV as well as HRV. Using a database of 30 min ECG recorded from 500 patients with acute myocardial infraction during rest, we extracted RR and QT interval time series and estimated different HRV and QTV metrics over windows of varying length. Analysis of variance (ANOVA) and intra-class correlation analyses were computed to investigate the effect of recording length on consistency and short-term reproducibility of HRV and QTV variables. Good consistency (non-significant ANOVA results) and short-term reproducibility (intra-class correlation coefficients  >0.8) were demonstrated for all but standard deviation based metrics when at least 200 beats were included in the estimation. In conclusion, QTV can be quantified from resting ECG with good short-term consistency and reproducibility that is comparable to that of HRV.

Long QT syndrome (LQTS) is an inherited disorder associated with prolongation of the QT/QTc interval on the surface electrocardiogram (ECG) and a markedly increased risk of sudden cardiac death due to cardiac arrhythmias. Up to 25% of genotype-positive LQTS patients have QT/QTc intervals in the normal range. These patients are, however, still at increased risk of life-threatening events compared to their genotype-negative siblings. Previous studies have shown that analysis of T-wave morphology may enhance discrimination between control and LQTS patients. In this study we tested the hypothesis that automated analysis of T-wave morphology from Holter ECG recordings could distinguish between control and LQTS patients with QTc values in the range 400-450 ms. Holter ECGs were obtained from the Telemetric and Holter ECG Warehouse (THEW) database. Frequency binned averaged ECG waveforms were obtained and extracted T-waves were fitted with a combination of 3 sigmoid functions (upslope, downslope and switch) or two 9th order polynomial functions (upslope and downslope). Neural network classifiers, based on parameters obtained from the sigmoid or polynomial fits to the 1 Hz and 1.3 Hz ECG waveforms, were able to achieve up to 92% discrimination between control and LQTS patients and 88% discrimination between LQTS1 and LQTS2 patients. When we analysed a subgroup of subjects with normal QT intervals (400-450 ms, 67 controls and 61 LQTS), T-wave morphology based parameters enabled 90% discrimination between control and LQTS patients, compared to only 71% when the groups were classified based on QTc alone. In summary, our Holter ECG analysis algorithms demonstrate the feasibility of using automated analysis of T-wave morphology to distinguish LQTS patients, even those with normal QTc, from healthy controls.

Recently it could be demonstrated that systolic and diastolic blood pressure variability (BPV) as well as segmented Poincare plot analysis (SPPA) contribute to risk stratification in patients suffering from dilated cardiomyopathy (DCM). The aim of this study was to improve the risk stratification applying a multivariate technique including QT variability (QTV). We enrolled and significantly separated 56 low risk and 13 high risk DCM patients by nearly all applied BPV and QTV methods, but not with traditional heart rate variability analysis. The optimum set of two indices calculating the multivariate discriminate analysis (DA) included one BPV index calculated by symbolic dynamics method (DBP(Shannon)) and one index calculated from QTV (QTV(log)) achieving an area under the receiver operating characteristics curve (AUC) of 92%, sensitivity of 92.3% and specificity of 89.3%. Performing only electrocardiogram analysis, the optimum multivariate approach including indices from segmented Poincaré plot analysis and QTV still achieved a remarkable AUC of 88.3%. Increasing the number of indices for multivariate DA up to three, we achieved an AUC of 95.7%, sensitivity of 100% and specificity of 85.7% including one clinical, one BPV and one QTV index. Summarizing, we identified DCM patients with an increased risk of sudden cardiac death applying QTV analysis in a multivariate approach.

Ageing has been associated with changes in cardiac electrophysiology that result in QT interval prolongation. The effect of age on rate-adaptation dynamics of the QT interval is less well understood. The aim of this study was to assess age-related changes in the temporal relationship between QT and RR interval variability. Resting ECG of 20 young and 20 elderly healthy subjects were analyzed. Beat-to-beat RR and QT interval time series were automatically extracted. Coupling between QT and RR was assessed by means of the QT variability index, coherence in the frequency domain, rate-corrected QT interval, cross-multiscale entropy, information based similarity index and joint symbolic dynamics. In addition to QT interval prolongation (433 ± 31 versus 405 ± 33 ms, p = 0.008), elderly subjects were characterized by a significantly increased QT variability index (-1.26 ± 0.28 versus -1.52 ± 0.22 ms, p < 0.0001), reduced coherence in high (0.11 ± 0.09 versus 0.29 ± 0.14 ms, p = 0.003), and low frequency bands (0.20 ± 0.16 versus 0.49 ± 0.15 ms, p < 0.0001), reduced information domain synchronization index (0.13 ± 0.07 versus 0.19 ± 0.05 ms, p = 0.001) as well as increased entropy and disparity in joint symbolic dynamics of QT and RR interval time series. In conclusion, ageing is associated with decoupling of QT variability from heart rate variability. Complexity analysis in addition to standard metrics may provide additional insight.

The purpose of this study was to investigate the effects of T-wave amplitude and ECG lead on beat-to-beat QT interval variability (QTV) in patients with myocardial infarction (MI) compared to healthy subjects. Standard resting 12-lead ECGs of 79 MI patients and 69 healthy subjects were investigated. Beat-to-beat QT intervals were measured separately for each lead using a template matching algorithm. In addition, we extracted the beat-to-beat T-wave amplitude in each lead. We computed the standard deviation of beat-to-beat QT intervals as a marker of QTV for both healthy subjects and MI patients. Significant QTV differences were observed between the 12 ECG leads as well as between the groups of healthy subjects and MI patients. Beat-to-beat QTV was significantly higher in MI patients than in healthy subjects for half of the leads. Furthermore, significant T-wave amplitude differences across leads and between groups were observed. A significant inverse relation between beat-to-beat QTV and T-wave amplitude was demonstrated. The group differences in QTV remained significant after co-varying for the T-wave amplitude. In conclusion, the increase in beat-to-beat QTV that has been repeatedly reported in patients with MI is partly due to the lower T-wave amplitudes. However, QTV remains significantly increased in MI patients after covarying for this effect.

Time irreversibility is a characteristic feature of non-equilibrium, complex systems such as the cardiovascular control mediated by the autonomic nervous system (ANS). Time irreversibility analysis of heart rate variability (HRV) and blood pressure variability (BPV) represents a new approach to assess cardiovascular regulatory mechanisms. The aim of this paper was to assess the changes in HRV and BPV irreversibility during the active orthostatic test (a balance of ANS shifted towards sympathetic predominance) in 28 healthy young subjects. We used three different time irreversibility indices-Porta's, Guzik's and Ehler's indices (P%, G% and E, respectively) derived from data segments containing 1000 beat-to-beat intervals on four timescales. We observed an increase in the HRV and a decrease in the BPV irreversibility during standing compared to the supine position. The postural change in irreversibility was confirmed by surrogate data analysis. The differences were more evident in G% and E than P% and for higher scale factors. Statistical analysis showed a close relationship between G% and E. Contrary to this, the association between P% and G% and P% and E was not proven. We conclude that time irreversibility of beat-to-beat HRV and BPV is significantly altered during orthostasis, implicating involvement of the autonomous nervous system in its generation.

Hypertensive pregnancy disorders affect 6% to 8% of all pregnancies and can result in severe complications for the mother and the foetus of which pre-eclampsia (PE) has the worst perinatal outcome. Several studies suggested that the autonomic nervous system plays an important role in the process of developing hypertensive pregnancy disorders, especially PE. The aim of this retrospective study was to investigate whether women with PE could be differentiated from women with various other hypertensive pregnancy disorders, by employing an enhanced Poincaré plot analysis (PPA), the segmented Poincaré plot analysis (SPPA), to their beat-to-beat interval and blood pressure signals. Sixty-nine pregnant women with hypertensive disorders (29 PE, 40 with chronic or gestational hypertension) were included. The SPPA as well as the traditional PPA found significant differences between PE and other hypertensive disorders of diastolic blood pressure (p < 0.001 versus p < 0.001) but only the SPPA method revealed significant differences (p < 0.001) also of the systolic blood pressure. Further on, linear discrimination analysis demonstrated that indices derived from SPPA are more suitable for differentiation between chronic and gestational hypertension and PE than those from traditional PPA (area under the ROC curve 0.85 versus 0.69). Therefore this procedure could contribute to the differential diagnosis of hypertensive pregnancy disorders.

Cardiovascular control acts over multiple time scales, which introduces a significant amount of complexity to heart rate and blood pressure time series. Multiscale entropy (MSE) analysis has been developed to quantify the complexity of a time series over multiple time scales. In previous studies, MSE analyses identified impaired cardiovascular control and increased cardiovascular risk in various pathological conditions. Despite the increasing acceptance of the MSE technique in clinical research, information underpinning the involvement of the autonomic nervous system in the MSE of heart rate and blood pressure is lacking. The objective of this study is to investigate the effect of orthostatic challenge on the MSE of heart rate and blood pressure variability (HRV, BPV) and the correlation between MSE (complexity measures) and traditional linear (time and frequency domain) measures. MSE analysis of HRV and BPV was performed in 28 healthy young subjects on 1000 consecutive heart beats in the supine and standing positions. Sample entropy values were assessed on scales of 1-10. We found that MSE of heart rate and blood pressure signals is sensitive to changes in autonomic balance caused by postural change from the supine to the standing position. The effect of orthostatic challenge on heart rate and blood pressure complexity depended on the time scale under investigation. Entropy values did not correlate with the mean values of heart rate and blood pressure and showed only weak correlations with linear HRV and BPV measures. In conclusion, the MSE analysis of heart rate and blood pressure provides a sensitive tool to detect changes in autonomic balance as induced by postural change.

The purpose of this paper is to investigate the effect of orthostatic challenge on recurrence plot based complexity measures of heart rate and blood pressure variability (HRV and BPV). HRV and BPV complexities were assessed in 28 healthy subjects over 15 min in the supine and standing positions. The complexity of HRV and BPV was assessed based on recurrence quantification analysis. HRV complexity was reduced along with the HRV magnitude after changing from the supine to the standing position. In contrast, the BPV magnitude increased and BPV complexity decreased upon standing. Recurrence quantification analysis (RQA) of HRV and BPV is sensitive to orthostatic challenge and might therefore be suited to assess changes in autonomic neural outflow to the cardiovascular system.

Multiscale entropy (MSE) analysis provides information about complexity on various time scales. The aim of this study was to test whether MSE is able to detect autonomic dysregulation in young patients with diabetes mellitus (DM). We analyzed heart rate (HR) oscillations, systolic (SBP) and diastolic blood pressure (DBP) signals in 14 patients with DM type 1 and 14 age- and sex-matched healthy controls. SampEn values (scales 1-10) and linear measures were computed. HR: among the linear measures of heart rate variability significant differences between groups were only found for RMSSD (p = 0.043). MSE was significantly reduced on scales 2 and 3 in DM (p = 0.023 and 0.010, respectively). SBP and DBP: no significant differences were detected with linear measures. In contrast, MSE analysis revealed significantly lower SampEn values in DM on scale 3 (p = 0.039 for SBP; p = 0.015 for DBP). No significant correlations were found between MSE and linear measures. In conclusion, MSE analysis of HR, SBP and DBP oscillations is able to detect subtle abnormalities in cardiovascular control in young patients with DM and is independent of standard linear measures.

Scaling analysis of heart rate time series has emerged as a useful tool for the assessment of autonomic cardiac control. We investigate the heart rate time series of ten athletes (five males and five females), by applying detrended fluctuation analysis (DFA). High resolution ECGs are recorded under standardized resting conditions over 30 min and subsequently heart rate time series are extracted and artifacts filtered. We find three distinct regions of scale invariance, which correspond to the well-known VLF, LF and HF bands in the power spectra of heart rate variability. The scaling exponents alpha are alpha(HF): 1.15 [0.96-1.22], alpha(LF): 0.68 [0.57-0.84], alpha(VLF): 0.83[0.82-0.99], p < 10(-5)). In conclusion, DFA scaling exponents of heart rate time series should be fitted to the VLF, LF and HF ranges, respectively.