Does Deep Bradycardia Increase the Risk of Arrhythmias and Syncope in Endurance Athletes?

The aim of this study was to evaluate whether endurance athletes who exhibit deep bradycardia are more prone to arrhythmias and reflex syncope than their non-bradycardic peers. 46 healthy men (ages 19-35) were divided into 3 groups based on whether they were sedentary (SED,<2 h/week) or endurance trained (ET,>6 h/week), and non-bradycardic (NB, resting heart rate (HR)≥60 bpm) or bradycardic (B, resting HR<50 bpm). Resting HR was lower in ETB vs. ETNB and SED (43.8±3.1, 61.3±3.3, 66.1±5.9 bpm, respectively; p<0.001). Thus, 16 SED, 13 ETNB and 17 ETB underwent resting echocardiography, maximal exercise test, tilt test (TT) and 24 h-Holter ECG. Subjects were followed-up during 4.7±1.1 years for training, syncope and cardiac events. Our results showed that incidence of arrhythmias and hypotensive susceptibility did not differ between groups. During follow-up, no episode of syncope or near-syncope was reported. However, cardio-inhibitory syncope occurrence tended to be higher in ETB. Left ventricular end-diastolic diameter index was increased in ETB vs. ETNB and was correlated with resting HR (r=- 0.64; p<0.001). As a result, athletes with deep bradycardia do not present more arrhythmias and more hypotensive susceptibility than their non-bradycardic peers. Cardiac enlargement and autonomic alteration both seem to be involved in an athlete's bradycardia.

Kernel based support vector machine for the early detection of syncope during head-up tilt test.

This study aims to analyze the autonomic nervous system response during head-up tilt test (HUTT), by exploring the changes in dynamic properties of heart rate variability in subjects with and without syncopes, to predict the outcome of HUTT. Baroreflex response, as well as linear and non-linear parameters of RR-interval time series, have been extracted from the ECG of 66 subjects: 35 with and 31 without syncope during HUTT. The results show that, when considering the first 15 min of tilting position, the total power spectrum, the standard deviation, the long-term fractal scale of RR-interval and ΔRR-interval of time series increase, while the sample entropy decreases in the positive group compared to the negative one. These indices may be good predictors of positive response in patients with reflex syncope. Additionally, an analysis of the first 15 min of tilting position using kernel support vector machines leads to a correct classification of 85% of patients, within negative and positive response groups (specificity = 80.6% and sensitivity = 88.5%). In medical applications, it is important to avoid false negative diagnosis of syncopes during HUTT. Taking this into account, an overall accuracy of 72.1% can be obtained in the same window allowing the reduction of the examination time in the clinical domain.