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Long QT syndrome type 2 (LQT2) is an inherited disease leading to arrhythmias and sudden death often in response to an abrupt sympathetic stimulus. Heart period (HP) and QT interval variability analyses were carried out over asymptomatic (ASYMP, n=10, age 39.0±11.0 yrs, 9 males) and symptomatic (SYMP, n=7, age 41.7±12.8 yrs, 4 males) LQT2 patients. Beat-to-beat series were derived from 24h Holter ECG recordings during daytime and nighttime. In addition to HP and QT mean and variance, we calculated HP power in high frequency (HF, from 0.15 to 0.5 Hz) band as a marker of vagal modulation directed to sinus node and QT power in low frequency (LF, from 0.04 to 0.15 Hz) band as a marker of sympathetic modulation directed to ventricles. HP and QT means exhibited significant day-night changes in both groups. ASYMP showed a shorter corrected QT and a more reactive vagal modulation leading to significant day-night variations of respiratory sinus arrhythmia. By contrast, SYMP had no significant day-night variations of the vagal control. Conversely, SYMP showed a higher sympathetic control during day compared to ASYMP, having a larger QT variance. These findings suggest that frequency domain HP and QT variability markers can account for the different arrhythmic risk of LQT2 ASYMP and SYMP patients.

This work proposes an empirical mode decomposition (EMD) method to assess the strength of the interactions between heart period (HP) and systolic arterial pressure (SAP) variability. EMD was exploited to decompose the original series (OR) into its first, and fastest, intrinsic mode function (IMF1) and the residual (RES) computed by subtracting the IMF1 from OR. EMD procedure was applied to both HP and SAP variability series. Then, the cross correlation function (CCF) was computed over OR, IMF1 and RES series derived from HP and SAP variability in 13 healthy subjects (age 27±8 yrs, 5 males) at rest in supine position (REST) and during head-up tilt (TILT). The first CCF maximum at negative time lags and the first CCF minimum at positive time lags were taken respectively as indexes of the coupling along the feedback baroreflex and feedforward mechanical arms of HP-SAP closed-loop control. Results showed that the coupling strength is increased during TILT on both arms and this result holds on REST. At REST the coupling along both arms was stronger when computed over IMF1 because interactions were mainly governed by respiration. This result was not observed during TILT possibly due to the reduced importance of respiration compared to other mechanisms acting at slower time scales. The proposed method allowed the investigation of the strength of HP-SAP variability interactions according to the time scales of the physiological mechanisms.The proposed EMD-based method allows the quantification of the strength of the HP-SAP closed-loop variability interactions according to the different time scales of respiration and slower baroreflex-mediated reflexes.

The coupling and latency between heart period (HP) and systolic arterial pressure (SAP) variability can be investigated along the two arms of the HP-SAP closed loop, namely along the baroreflex feedback from SAP to HP, and along the feedforward pathway from HP to SAP. This study investigates the HP-SAP closed loop variability interactions through cross-correlation function (CCF). Coupling strength and delay between HP and SAP variability series were monitored in 13 subjects prone to develop orthostatic syncope (SYNC, 28±9 yrs, 5 males) and in 13 subjects with no history of postural syncope (noSYNC, age: 27±8 yrs, 5 males). Analysis was carried out at rest in supine position (REST) and during head-up tilt (TILT) at 60 degrees. The null hypothesis of HP-SAP uncoupling was tested through a surrogate analysis associating the HP series of a subject with a SAP sequence of a different one. Results showed that during TILT the coupling strength increased along the baroreflex and latency augmented along the mechanical feedforward pathway exclusively in noSYNC subjects. Finally, closed loop HP-SAP interactions were detected in about one third of subjects and the situation of full uncoupling was rarely found. CCF analysis was found to be a straightforward and easily applicable method to investigate HP-SAP control deserving a direct comparison with more sophisticated signal processing tools assessing causality.

Cardiovascular regulation and autonomic function change across sleep stages and compared to wake. Little information is present in literature about cardiac control during sleep especially in relation to new information-theoretic quantities such as synergy and redundancy. In the present work we compute synergy and redundancy of baroreflex and non-baroreflex components of the cardiac control according to two information-theoretic approaches, namely predictive information decomposition (PID) and minimal mutual information (MMI) methods. We applied a bivariate approach to heart period (HP) and systolic arterial pressure (SAP) beat-to-beat variability series during sleep in a healthy subject. PID approach computes the net balance between synergy and redundancy, while MMI calculates the two quantities as separate entities. Results suggested that: i) redundancy was dominant over synergy during NREM phases; ii) redundancy increased during NREM phase; iii) synergy did not change across the sleep stages. We interpret this result as a consequence of the vagal enhancement, slowing and deepening of respiration during NREM phases. These preliminary findings support the potential of assessing redundancy/synergy of baroreflex-related and unrelated regulations during sleep to improve our knowledge about physiological mechanisms.

A linear model-based multiscale complexity (MSC) approach was here applied to short heart period (HP) and QT interval variability series derived from 24 hours Holter ECG recordings in a group of long QT syndrome type 1 (LQT1) patients. The MSC approach allows to assess complexity in the typical frequency bands of HP and QT variability, i.e. low frequency (LF, from 0.04 to 0.15 Hz) and high frequency (HF, from 0.15 to 0.5 Hz). MSC was computed along with a single scale complexity over 7 LQT1 asymptomatic mutation carriers (AMC), 22 symptomatic mutation carriers (SMC) and 13 healthy non-mutation carriers (NMC) belonging to the same family line during daytime and nighttime. Time domain markers and HP variability complexity analyses were unable to separate groups. While single scale QT variability complexity analysis could distinguish NMC from mutation carriers, solely MSC of QT variability distinguished AMCs from SMCs, showing that AMCs have a reduced complexity in LF band during daytime. We conclude that a reduced complexity of the sympathetic drive directed to the ventricles might be protective against life threatening arrhythmias especially during day being the most risky period for LQT1 patients. MSC of QT variability could be fruitfully exploited to improve risk stratification in LQT1 population.