Prediction of atrial fibrillation recurrence after cardioversion—Interaction analysis of cardiac autonomic regulation

Multi-scale Entropy Evaluates the Proarrhythmic Condition of Persistent Atrial Fibrillation Patients Predicting Early Failure of Electrical Cardioversion

Atrial fibrillation (AF) is nowadays the most common cardiac arrhythmia, being associated with an increase in cardiovascular mortality and morbidity. When AF lasts for more than seven days, it is classified as persistent AF and external interventions are required for its termination. A well-established alternative for that purpose is electrical cardioversion (ECV). While ECV is able to initially restore sinus rhythm (SR) in more than 90% of patients, rates of AF recurrence as high as 20-30% have been found after only a few weeks of follow-up. Hence, new methods for evaluating the proarrhythmic condition of a patient before the intervention can serve as efficient predictors about the high risk of early failure of ECV, thus facilitating optimal management of AF patients. Among the wide variety of predictors that have been proposed to date, those based on estimating organization of the fibrillatory (f-) waves from the surface electrocardiogram (ECG) have reported very promising results. However, the existing methods are based on traditional entropy measures, which only assess a single time scale and often are unable to fully characterize the dynamics generated by highly complex systems, such as the heart during AF. The present work then explores whether a multi-scale entropy (MSE) analysis of the f-waves may provide early prediction of AF recurrence after ECV. In addition to the common MSE, two improved versions have also been analyzed, composite MSE (CMSE) and refined MSE (RMSE). When analyzing 70 patients under ECV, of which 31 maintained SR and 39 relapsed to AF after a four week follow-up, the three methods provided similar performance. However, RMSE reported a slightly better discriminant ability of 86%, thus improving the other multi-scale-based outcomes by 3-9% and other previously proposed predictors of ECV by 15-30%. This outcome suggests that investigation of dynamics at large time scales yields novel insights about the underlying complex processes generating f-waves, which could provide individual proarrhythmic condition estimation, thus improving preoperative predictions of ECV early failure.

Study of impaired cardiovascular and respiratory coupling during orthostatic stress based on joint symbolic dynamics

The present study investigates the instantaneous coupling among the cardiac, vascular, and respiratory systems, using the heart rate, respiration, and systolic and diastolic blood pressure variability in 12 healthy and 16 vasovagal syncope female subjects during a head-up tilt (HUT) testing protocol at 70° This study contributes to the coupling analysis by using a nonlinear joint symbolic dynamics (JSD) in a high-temporal resolution scheme, based on 5 min segments of the time series that are shifted every minute. For each segment, a bivariate JSD matrix was constructed to obtain global and local coupling indices in accordance to Shannon's entropy and the probability of occurrence of various bivariate words, respectively. The novel approach revealed important findings in the coupling dynamics of the systems, thus allowing the detection of group differences during the early orthostatic phase, and during the HUT test, before the occurrence of any pre-syncopal symptoms. In patients, the global indices indicated a significant decrease of cardiovascular coupling, starting at 10 min after the tilt-up, manifested by reduced baroreflex sensitivity and cardiorespiratory coupling that was initiated 8 min after the onset of the orthostatic phase (OP). A decreased autonomic control on cardiovascular-respiratory couplings was further evidenced by increased alterations of the JSD indices during the OP compared to the supine position in patients compared to controls. Furthermore, findings based on local indices demonstrated that female patients showed reductions and disengagements in cardiovascular (p < 0.001) and cardiorespiratory (p < 0.01) couplings, as early as the first 5 min and during the complete OP.

Delta space plot analysis of cardiovascular coupling in vasovagal syncope during orthostatic challenge

In this work, a graphical method to study cardiovascular coupling, called delta space plot analysis (DSPA), was introduced. The graphical representation is susceptible to be parameterized in shape and orientation. The usefulness of this technique was studied on cardiovascular data from patients with vasovagal syncope (VVS) and from controls. The study included 15 female patients diagnosed with VVS and 11 age-matched healthy female subjects. All subjects were enrolled in a head-up tilt (HUT) test, breathing normally, including 5 minutes of supine position (baseline) and 18 minutes of 70° orthostatic phase. The DSPA parameters were obtained at different times during the HUT test, i.e., at baseline, early (first 5 min) and late (10-15 min) orthostatic phases. In baseline there were no considerable differences between female controls and female patients. During the late orthostatic phase, parameters from DSPA showed highly significantly (p=0.000003) reduced cardiovascular coupling in patients. Findings indicated a loss of control on cardiovascular coupling in female patients susceptible to vasovagal syncope during orthostatic challenge. In addition, this study provided promising results for a new graphical method to investigate cardiovascular coupling.

Three-dimensional dominant frequency mapping using autoregressive spectral analysis of atrial electrograms of patients in persistent atrial fibrillation

BACKGROUND

Areas with high frequency activity within the atrium are thought to be 'drivers' of the rhythm in patients with atrial fibrillation (AF) and ablation of these areas seems to be an effective therapy in eliminating DF gradient and restoring sinus rhythm. Clinical groups have applied the traditional FFT-based approach to generate the three-dimensional dominant frequency (3D DF) maps during electrophysiology (EP) procedures but literature is restricted on using alternative spectral estimation techniques that can have a better frequency resolution that FFT-based spectral estimation.

METHODS

Autoregressive (AR) model-based spectral estimation techniques, with emphasis on selection of appropriate sampling rate and AR model order, were implemented to generate high-density 3D DF maps of atrial electrograms (AEGs) in persistent atrial fibrillation (persAF). For each patient, 2048 simultaneous AEGs were recorded for 20.478 s-long segments in the left atrium (LA) and exported for analysis, together with their anatomical locations. After the DFs were identified using AR-based spectral estimation, they were colour coded to produce sequential 3D DF maps. These maps were systematically compared with maps found using the Fourier-based approach.

RESULTS

3D DF maps can be obtained using AR-based spectral estimation after AEGs downsampling (DS) and the resulting maps are very similar to those obtained using FFT-based spectral estimation (mean 90.23 %). There were no significant differences between AR techniques (p = 0.62). The processing time for AR-based approach was considerably shorter (from 5.44 to 5.05 s) when lower sampling frequencies and model order values were used. Higher levels of DS presented higher rates of DF agreement (sampling frequency of 37.5 Hz).

CONCLUSION

We have demonstrated the feasibility of using AR spectral estimation methods for producing 3D DF maps and characterised their differences to the maps produced using the FFT technique, offering an alternative approach for 3D DF computation in human persAF studies.

Altered autonomic regulation as a cardiovascular risk marker for patients with sudden sensorineural hearing loss

OBJECTIVES

To measure autonomic nervous system function after idiopathic sudden sensorineural hearing loss (ISSHL).

STUDY DESIGN

Diagnostic prospective cohort single-center study.

SETTING

Tertiary referral university hospital.

PATIENTS

Twenty-three adult patients with ISSHL and 10 normal-hearing control patients without ISSHL (CON) matched with respect to age, sex, hypertension, and medication.

MAIN OUTCOME MEASURES

Bivariate analysis of autonomic regulation (ISSHL versus CON) using 30-minute heart rate (HR) and systolic and diastolic blood pressure (BP) time series at baseline, based on cardiovascular coupling, HR and BP regulatory patterns, high-resolution coupling analysis based on joint symbolic dynamics (High-Resolution Joint Symbolic Dynamics).

INTERVENTION

No intervention.

RESULTS

Multivariate discrimination between ISSHL and CON achieved values of area under the receiver operator characteristic curve = 95.5, sensitivity = 90.9%, and specificity = 88.9%. Independent from medication and hypertension increased the complexity of nonlinear HR regulation and reduced cardiovascular coupling of ISSHL patients and independent from hypertension altered nonlinear systolic and diastolic BP regulation. Coupling patterns are characterized by a less pronounced strong and fast decrease of systolic BP when HR increases and rapidly changes in ISSHL patients. Disturbed BP modulation and complexity by impaired baroreflex activities resulting in short-term BP fluctuations, altered peripheral resistance, and reduced cochlear blood flow. Increased values for the pulse wave velocity in the aorta and carotid-femoral were early indicators that the elasticity of the arteries might be restricted in ISSHL patients.

CONCLUSION

ISSHL patients show an altered autonomic regulation. At least a subgroup of ISSHL patients seems to exist where a vascular impairment might play an important role in the pathogenesis of this disease.

QT variability improves risk stratification in patients with dilated cardiomyopathy

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.

Joint symbolic dynamics for the assessment of cardiovascular and cardiorespiratory interactions

Beat-to-beat variations in heart period provide information on cardiovascular control and are closely linked to variations in arterial pressure and respiration. Joint symbolic analysis of heart period, systolic arterial pressure and respiration allows for a simple description of their shared short-term dynamics that are governed by cardiac baroreflex control and cardiorespiratory coupling. In this review, we discuss methodology and research applications. Studies suggest that analysis of joint symbolic dynamics provides a powerful tool for identifying physiological and pathophysiological changes in cardiovascular and cardiorespiratory control.