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It is with pride and gratitude that we reflect on the remarkable 10-year journey of European Journal of Arrhythmia & Electrophysiology. With the vital contributions of all of our esteemed authors, reviewers and editorial board members, the journal has served as a platform for groundbreaking research, clinical insights and news that have helped shape the […]

179/Is heart rate variability simply a reflection of heart rate? Analysis of the relationship between heart rate variability heart rate and activity in patients with complex cardiac devices

Z Vali (Presenting Author) – University of Leicester, Leicester, UK; V Pooranachandran – University of Leicester, Leicester, UK; A Mistry – University of Leicester, Leicester, UK; B Sidhu – University of Leicester, Leicester, UK; X Li – University of Leicester, Leicester, UK; GA Ng – University of Leicester, Leicester, UK
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Published Online: Oct 3rd 2008 European Journal of Arrhythmia & Electrophysiology. 2019;5(Suppl. 1):abstr179
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Article

Introduction: Heart rate variability (HRV) has been established as an important clinical tool, especially in patients with underlying heart disease. Studies have shown its prognostic value. However, despite tens of thousands of publications, HRV and its underlying mechanisms remain controversial. Some have suggested that HRV is simply a feature of heart rate (HR) rather than a measure of autonomic tone (Boyett et al., 2019, Journal of Physiology and Monfredi et al., 2014, Hypertension). We aimed to assess whether there is an inverse relationship in our cohort of patients with complex cardiac devices, which are able to report both HR and HRV.

Methods: We reviewed the diagnostic data of patients with Medtronic and Boston Scientific complex cardiac pacemaker and defibrillator devices. The HRV, mean HR and daily activity levels were recorded from the most recent device download. These values were then analysed to assess correlation, with statistical analysis performed using R. Further analysis was also done factoring age into HR, to mitigate the effects of age on HR. Patients with atrial arrhythmia or atrial pacing were excluded.

Results: Data from 160 patients (80 with Medtronic and 80 with Boston Scientific devices) was analysed. In patients with Medtronic devices there was a weak inverse correlation between HRV and mean HR (r=-0.32; p=0.002), weak positive correlation between HRV and activity level (r=0.42; p<0.001) and no significant correlation between HRV and age (r=-0.18; p=0.09). After factoring age into HR, there was no correlation between HRV and mean HR (r=0.04; p=0.69).The patients with Boston devices had no significant correlation between HRV and mean HR (r=-0.19; p=0.08), weak positive correlation between HRV and activity level (r=0.32; p=0.003), and weak inverse correlation between HRV and age (r=-0.31; p=0.004). After factoring age into HR, there remained no significant correlation (r=0.12; p=0.25)

Discussion: There was a weak inverse correlation between HRV and HR in the data from Medtronic devices, but not after taking into account the potential effects of age on HR, and not in patients with Boston devices. The difference between different devices may be due to the different algorithms used to validate HRV measurements or due to the different methods of calculating HRV (SDNN in Medtronic versus SDANN in Boston). HRV data is only reported in dual chamber Boston devices ensuring only atrial sensed events are used, hence a true reflection of sinus node activity. Measurement of HRV simply from RR intervals is prone to error, especially in patients at risk of transient arrhythmias.

The weak positive correlation between HRV and activity level may be reflection of the fact that low HRV is associated with more severe disease. In conclusion, our data does not support the argument that HRV is a reflection of heart rate, but rather an independent measure of autonomic tone. The method of analysing HRV is an important factor and may explain some of the conflicting results in previous studies. Our data is limited to time domain measures of HRV. More work with larger datasets and frequency domain measures are needed to confirm our findings.

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