Heart rate complexity analysis in Brugada syndrome during physical stress testing

Calvo, Mireia; Gomis, Pedro; Romero, Daniel; Rolle, Virginie Le; Béhar, Nathalie; Mabo, Philippe; Hernández, Alfredo

doi:10.1088/1361-6579/aa513c

Cited by 8 publications

(7 citation statements)

References 42 publications

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“…Subramanian et al [ 23 ] proved the usefulness of some electrocardiographic markers extracted during exercise testing for risk stratification in BS. Moreover, our group has recently reported significant differences in heart rate complexity between symptomatic and asymptomatic patients, during periods of recovery after exertion [ 24 ]. Nevertheless, Amin et al [ 22 ] published the first work measuring the autonomic function of 50 BS patients and 35 controls during exercise, finding a higher parasympathetic reactivation during early recovery in patients with prior VF events.…”

Section: Discussionmentioning

confidence: 99%

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

et al. 2018

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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 HFnu 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.

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Section: Discussionmentioning

confidence: 99%

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

et al. 2018

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“…Then, based on our previously reported analyses on the autonomic function of BS patients during A) exercise [11,12], B) HUT testing [14] and C) sleep [7], several HRV markers were calculated for each patient, to build a set of candidate features to be used for classification purposes.…”

Section: Hrv Featuresmentioning

confidence: 99%

“…In previous works, we reported significant differences in the autonomic function of symptomatic and asymptomatic BS patients overnight [7] and during exercise [11][12][13] and head-up tilt (HUT) testing [14,15]. In this paper, we further explore the potential of heart rate variability (HRV) markers for BS classification, by combining features extracted from these experimental conditions.…”

Section: Introductionmentioning

confidence: 99%

Multivariate Classification of Brugada Syndrome Patients Based on the Autonomic Response During Sleep, Exercise and Head-up Tilt Testing

Calvo¹,

Rolle²,

Romero³

et al. 2019

2019 Computing in Cardiology Conference (CinC)

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Several autonomic markers were estimated overnight and during exercise and head-up tilt (HUT) testing for 44 BS patients, to design classifiers capable of distinguishing patients at different levels of risk. The classification performance of predictive models built from the optimization of a step-based machine-learning method were compared, so as to identify those autonomic protocols and markers best distinguishing between symptomatic and asymptomatic patients. Although exercise and HUT testing together led to better predictive results than when they were separately assessed, among all analyzed combinations, the night-based classifier presented the best performance (AU C = 95%), using the least amount of features. This optimal features subset was mostly composed of markers extracted between 4 a.m. -5 a.m. Thus, results provide further evidence for the role of nighttime analysis, mainly during the last hours of sleep, for risk stratification in BS.

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“…Conversely, postexercise cardiodeceleration is adjusted by parasympathetic activation and sympathetic withdrawal [14]. Indeed, some studies have already reported the potential of exercise testing in BS [15,16,17,18]. Amin et al [19] found a higher parasympathetic reactivation during early recovery after exertion in BS patients with prior ventricular fibrillation events.…”

Section: Introductionmentioning

confidence: 99%

Recursive model identification for the analysis of the autonomic response to exercise testing in Brugada syndrome

Calvo

Rolle

Romero

et al. 2019

Artificial Intelligence in Medicine

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This paper proposes the integration and analysis of a closed-loop model of the baroreflex and cardiovascular systems, focused on a time-varying estimation of the autonomic modulation of heart rate in Brugada syndrome (BS), during exercise and subsequent recovery. Patient-specific models of 44 BS patients at different levels of risk (symptomatic and asymptomatic) were identified through a recursive evolutionary algorithm. After parameter identification, a close match between experimental and simulated signals (mean error = 0.81%) was observed. The model-based estimation of vagal and sympathetic contributions were consistent with physiological knowledge, enabling to observe the expected autonomic changes induced by exercise testing. In particular, symptomatic patients presented a significantly higher parasympathetic activity during exercise, and an autonomic imbalance was observed in these patients at peak effort and during post-exercise recovery. A higher vagal modulation during exercise, as well as an increased parasympathetic activity at peak effort and a decreased vagal contribution during post-exercise recovery could be related with symptoms and, thus, with a worse prognosis in BS. This work proposes the first evaluation of the sympathetic and parasympathetic responses to exercise testing in patients suffering from BS, through the recursive identification of computational models; highlighting important trends of clinical relevance that provide new insights into the underlying autonomic mechanisms regulating the cardiovascular system in BS.

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Heart rate complexity analysis in Brugada syndrome during physical stress testing

Cited by 8 publications

References 42 publications

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

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

Multivariate Classification of Brugada Syndrome Patients Based on the Autonomic Response During Sleep, Exercise and Head-up Tilt Testing

Recursive model identification for the analysis of the autonomic response to exercise testing in Brugada syndrome

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