Heart rate variability and repolarization characteristics in symptomatic and asymptomatic Brugada syndrome

Multivariate ensemble classification for the prediction of symptoms in patients with Brugada syndrome

Identification of asymptomatic patients at higher risk for suffering cardiac events remains controversial and challenging in Brugada syndrome (BS). In this work, we proposed an ECG-based classifier to predict BS-related symptoms, by merging the most predictive electrophysiological features derived from the ventricular depolarization and repolarization periods, along with autonomic-related markers. The initial feature space included local and dynamic ECG markers, assessed during a physical exercise test performed in 110 BS patients (25 symptomatic). Morphological, temporal and spatial properties quantifying the ECG dynamic response to exercise and recovery were considered. Our model was obtained by proposing a two-stage feature selection process that combined a resampled-based regularization approach with a wrapper model assessment for balancing, simplicity and performance. For the classification step, an ensemble was constructed by several logistic regression base classifiers, whose outputs were fused using a performance-based weighted average. The most relevant predictors corresponded to the repolarization interval, followed by two autonomic markers and two other makers of depolarization dynamics. Our classifier allowed for the identification of novel symptom-related markers from autonomic and dynamic ECG responses during exercise testing, suggesting the need for multifactorial risk stratification approaches in order to predict future cardiac events in asymptomatic BS patients. Graphical abstract Pipeline for feature selection and predictive modeling of symptoms in Brugada syndrome.

Autonomic cardiac innervation: impact on the evolution of arrhythmias in inherited cardiac arrhythmia syndromes

The autonomic nervous system (ANS) is an essential component of arrhythmogenicity, especially in the absence of structural heart disease and channelopathy. In this article, the authors review the role and characteristics of ANS in various channelopathies. Some of these, such as most long QT syndromes and catecholaminergic polymorphic ventricular tachycardia, are highly dependent on sympathetic activation, while parasympathetic tone is an important factor for arrhythmias in other channelopathies such as Brugada syndrome or early repolarisation syndrome. Recent advances highlighting the subtle role of ANS in channelopathies are presented here, demonstrating that all is far from being so simple and straightforward and revealing some paradoxical behaviours of channelopathies in relation to discrete ANS imbalance.

Measures of repolarization variability predict ventricular arrhythmogenesis in heptanol-treated Langendorff-perfused mouse hearts

BACKGROUND

Time-domain and non-linear methods can be used to quantify beat-to-beat repolarization variability but whether measures of repolarization variability can predict ventricular arrhythmogenesis in mice have never been explored.

METHODS

Left ventricular monophasic action potentials (MAPs) were recorded during constant right ventricular 8 ​Hz pacing in Langendorff-perfused mouse hearts, in the presence or absence of the gap junction and sodium channel inhibitor heptanol (0.1, 0.5, 1 or 2 ​mM).

RESULTS

Under control conditions, mean action potential duration (APD) was 39.4 ​± ​8.1 ​ms. Standard deviation (SD) of APDs was 0.3 ​± ​0.2 ​ms, coefficient of variation was 0.9 ​± ​0.8% and the root mean square (RMS) of successive differences in APDs was 0.15 ​± ​0.14 ​ms. Poincaré plots of APDn+1 against APDn revealed ellipsoid morphologies with a SD along the line-of-identity (SD2) to SD perpendicular to the line-of-identity (SD1) ratio of 4.6 ​± ​2.1. Approximate and sample entropy were 0.61 ​± ​0.12 and 0.76 ​± ​0.26, respectively. Detrended fluctuation analysis revealed short- and long-term fluctuation slopes of 1.49 ​± ​0.27 and 0.81 ​± ​0.36, respectively. Heptanol at 2 ​mM induced ventricular tachycardia in five out of six hearts. None of the above parameters were altered by heptanol during which reproducible electrical activity was observed (KW-ANOVA, P ​> ​0.05). Contrastingly, SD2/SD1 decreased to 2.03 ​± ​0.41, approximate and sample entropy increased to 0.82 ​± ​0.12 and 1.45 ​± ​0.34, and short-term fluctuation slope decreased to 0.82 ​± ​0.19 during the 20-s period preceding spontaneous ventricular tachy-arrhythmias (n ​= ​6, KW-ANOVA, P ​< ​0.05).

CONCLUSION

Measures of repolarization variability, such as SD2/SD1, entropy, and fluctuation slope are altered preceding the occurrence of ventricular arrhythmogenesis in mouse hearts. Changes in these variables may allow detection of impending arrhythmias for early intervention.

Symmetric Projection Attractor Reconstruction analysis of murine electrocardiograms: Retrospective prediction of Scn5a+/- genetic mutation attributable to Brugada syndrome

Background

Life-threatening arrhythmias resulting from genetic mutations are often missed in current electrocardiogram (ECG) analysis. We combined a new method for ECG analysis that uses all the waveform data with machine learning to improve detection of such mutations from short ECG signals in a mouse model.

Objective

We sought to detect consequences of Na⁺ channel deficiencies known to compromise action potential conduction in comparisons of Scn5a^+/- mutant and wild-type mice using short ECG signals, examining novel and standard features derived from lead I and II ECG recordings by machine learning algorithms.

Methods

Lead I and II ECG signals from anesthetized wild-type and Scn5a^+/- mutant mice of length 130 seconds were analyzed by extracting various groups of features, which were used by machine learning to classify the mice as wild-type or mutant. The features used were standard ECG intervals and amplitudes, as well as features derived from attractors generated using the novel Symmetric Projection Attractor Reconstruction method, which reformulates the whole signal as a bounded, symmetric 2-dimensional attractor. All the features were also combined as a single feature group.

Results

Classification of genotype using the attractor features gave higher accuracy than using either the ECG intervals or the intervals and amplitudes. However, the highest accuracy (96%) was obtained using all the features. Accuracies for different subgroups of the data were obtained and compared.

Conclusion

Detection of the Scn5a^+/- mutation from short mouse ECG signals with high accuracy is possible using our Symmetric Projection Attractor Reconstruction method.

Differences in Brugada Syndrome Patients Through Ventricular Repolarization Analysis During Sleep

Brugada syndrome (BS) is a genetic pathology that might cause sudden cardiac death (SCD) in patients with a structurally normal heart. Repolarization disorders have been postulated as a potential substrate for triggering cardiac arrhythmia in BS, that usually occur at rest or during sleep. In this paper, we have characterized ventricular repolarization markers during sleep on patients suffering from BS. To this end, standard 12-lead ECG recordings were analyzed in a population of 110 BS patients (25 symptomatic). The QT and the T-wave peak to T-wave end intervals (respectively QT and Tpe) were assessed from lead V5. The linear relationship between these markers and the instantaneous heart rate period (RR interval) are determined during each hour and for the whole sleep period. From the models obtained, corrected QT and Tpe measures were then estimated for each patient at 60 beats/min (QT₆₀ and Tpe₆₀) and at the mean heart rate observed during the involved time interval (QT_HR and Tpe_HR). Results show larger values for symptomatic patients in all markers, with significant differences with respect to the asymptomatic group in the case of Tpe (Tpe₆₀: p = 0.0012; Tpe_HR: p = 0.0014). Moreover, the temporal profiles of these markers reveal major differences among BS subgroups during the last 3 hours of sleep, where symptomatic patients presented increased QT_60/HR (p = 0.01) and Tpe_60/HR (p <; 0.001), as compared to the initial sleep hours. We conclude that BS patients present different repolarization properties according to their symptomatology, especially during the final stage of sleep.

Dynamic changes in ventricular depolarization during exercise in patients with Brugada syndrome

Brugada syndrome (BS) is a genetic pathological condition associated with a high risk for sudden cardiac death (SCD). Ventricular depolarization disorders have been suggested as a potential electrophysiological mechanism associated with high SCD risk on patients with BS. This paper aims to characterize the dynamic changes of ventricular depolarization observed during physical exercise in symptomatic and asymptomatic BS patients. To this end, cardiac ventricular depolarization features were automatically extracted from 12-lead ECG recordings acquired during standardized exercise stress test in 110 BS patients, of whom 25 were symptomatic. Conventional parameters were evaluated, including QRS duration, R and S wave amplitudes (AR, AS), as well as QRS morphological features, such as up-stroke and down-stroke slopes of the R and S waves (UR, DR and US). The effects of physical exercise and recovery on the dynamics of these markers were assessed in both BS populations. Features showing significantly different dynamics between the studied groups were used alone and in combination with the clinical characteristics of the patients in a logistic regression analysis. Results show larger changes in the second half of the QRS complex through AS and US measured in the right precordial leads for asymptomatic patients, especially during recovery, when the vagal tone is more pronounced. Multivariate analysis involving both types of features resulted in a reduced model of three relevant features (ΔAS in lead V2, Sex and heart rate recovery, HRR), which achieved a suitable discrimination performance between groups; sensitivity = 80% and specificity = 75% (AUC = 83%). However, after controlling the model for possible confounding factors, only one feature (ΔAS) remained meaningful. This adjusted model significantly improved the overall discrimination performance by up to: sensitivity = 84% and specificity = 100% (AUC = 94%). The study highlights the importance of physical exercise test to unmask differentiated behaviors between symptomatic and asymptomatic BS patients through depolarization dynamic analysis. This analysis together with the obtained model may help to identify asymptomatic patients at low or high risk of future cardiac events, but it should be confirmed by further prospective studies.

Heart rate differences between symptomatic and asymptomatic Brugada syndrome patients at night

OBJECTIVE

Ventricular arrhythmias in Brugada syndrome (BS) mainly occur at rest, especially during nighttime, suggesting that parasympathetic activity at night may play an important role in the arrhythmogenesis of the disease. This study examined and compared the autonomic function of symptomatic and asymptomatic BS patients overnight.

APPROACH

We analyzed various heart rate variability (HRV) and heart rate complexity (HRC) markers in a clinical series including 87 BS patients, where 23 were symptomatic.

MAIN RESULTS

Statistically significant differences were found in markers MIRR, SDNN, SDANN, [Formula: see text] and SampEn, suggesting that symptomatic patients may be related to lower heart rate variability and complexity values, as well as to greater circadian fluctuations overnight.

SIGNIFICANCE

The results provide further evidence for the role of autonomic imbalance in the pathophysiology of BS, highlighting the relevance of nighttime analysis to the unmasking of significant ANS changes. Based on these outcomes, the role of HRV and HRC assessment at night could be a step forward towards the understanding of BS and the risk for the occurrence of symptoms in these patients, with a potential future impact on therapeutic strategies.

Multivariate classification of Brugada syndrome patients based on autonomic response to exercise testing

Ventricular arrhythmias in Brugada syndrome (BS) typically occur at rest and especially during sleep, suggesting that changes in the autonomic modulation may play an important role in arrhythmogenesis. The autonomic response to exercise and subsequent recovery was evaluated on 105 patients diagnosed with BS (twenty-four were symptomatic), by means of a time-frequency heart rate variability (HRV) analysis, so as to propose a novel predictive model capable of distinguishing symptomatic and asymptomatic BS populations. During incremental exercise, symptomatic patients showed higher HF_nu values, probably related to an increased parasympathetic modulation, with respect to asymptomatic subjects. In addition, those extracted HRV features best distinguishing between populations were selected using a two-step feature selection approach, so as to build a linear discriminant analysis (LDA) classifier. The final features subset included one third of the total amount of extracted autonomic markers, mostly acquired during incremental exercise and active recovery, thus evidencing the relevance of these test segments in BS patients classification. The derived predictive model showed an improved performance with respect to previous works in the field (AUC = 0.92 ± 0.01; Se = 0.91 ± 0.06; Sp = 0.90 ± 0.05). Therefore, based on these findings, some of the analyzed HRV markers and the proposed model could be useful for risk stratification in Brugada syndrome.