Heart Rate Variability and P Wave Characteristics after Atrial Fibrillation

Correspondence to: Dr. Victor Dan Moga, e-mail: [email protected]. SUMMARY: Despite the development of pharmacological therapy and/or device therapy, atrial fibrillation remains a leading cause for morbidity and mortality. Heart rate variability (HRV) is studied only in the presence of sinus rhythm. Currently, three different categories of methods in HRV analysis are being used; the time domain, frequency domain, and non-linear dynamic analysis. Both time domain and frequency domain analyses of HRV have been investigated extensively regarding their use as a prognostic marker for cardiovascular mortality. The non-linear dynamic analysis is the latest tool that has shown to have an even higher predictive value than any of the traditional parameters. The relationship heart rate variability and atrial fibrillation is less studied and poorly understood. It is well known that depressed heart rate variability (HRV) in heart failure is associated with increased mortality. The aim of our study was to highlight the complex heart rate modulation after atrial fibrillation and to analyze the behavior of RR intervals dynamics after restoration of the sinus rhythm. Some challenges during our study have been: which is the role of the autonomic tone modulation in the onset of atrial fibrillation and is the autonomic tone involved in the restoration of the sinus rhythm? In this study we recorded ECG at bedside using an ECG Cardiax device and we analyzed the relationship between the heart rate variability parameters and the characteristics of the P wave, like P wave axis, P wave duration and the PQ duration (ms). Also we implement the coefficient of variance (CV) as the ratio of SD of RR intervals and the mean RR. Heart rate variability parameters are measured in both time domain RR intervals (ms), standard deviation of all RR intervals SDRR (ms) and spectral domain – as very low frequency (VLF, 0.01-0.04 Hz), low frequency (LF, 0.05 -0.15 Hz) and high frequency (HF, 0.15-0.50 Hz), LF/HF ratio, respectively nonlinear dynamics parameters like sample entropy, detrended fluctuation analysis, and Poincare plots. Dynamic analysis techniques may quantify abnormalities in heart rate variability (HRV) based on nonlinear and fractal analysis (chaos theory). Approximate entropy (ApEn) was applied to quantify the regularity and complexity of time series, as well as unpredictability of fluctuations in time series. This study suggests that nonlinear analysis technique may complement conventional atrial fibrillation analysis. We consider that it is necessary to consider also P wave axis and P wave duration together with the linear and nonlinear parameters of heart rate variability as complex P wave remodeling elements with complex contribution in restoring the sinus rhythm after atrial fibrillation.