Heart Rate Variability Density Analysis (Dyx) and Prediction of Long-Term Mortality after Acute Myocardial Infarction.

Aims: The density HRV parameter Dyx is a new heart rate variability (HRV) measure based on multipole analysis of the Poincaré plot obtained from RR interval time series, deriving information from both the time and frequency domain. Preliminary results have suggested that the parameter may provide new predictive information on mortality in survivors of acute myocardial infarction (MI). This study compares the prognostic significance of Dyx to that of traditional linear and nonlinear measures of HRV.

Determinants and prognostic value of cardiovascular autonomic function in coronary artery disease patients with and without type 2 diabetes.

OBJECTIVE Cardiovascular autonomic dysfunction is a common finding among patients with coronary artery disease (CAD) and type 2 diabetes (T2D). The reasons and prognostic value of autonomic dysfunction in CAD patients with T2D are not well known. RESEARCH DESIGN AND METHODS We examined the association between heart rate recovery (HRR), 24-h heart rate (HR) variability (SD of normal R-R interval [SDNN]), and HR turbulence (HRT), and echocardiographic parameters, metabolic, inflammatory, and coronary risk variables, exercise capacity, and the presence of T2D among 1,060 patients with CAD (mean age 67 ± 8 years; 69% males; 50% patients with T2D).

Role of editing of R-R intervals in the analysis of heart rate variability.

This paper reviews the methods used for editing of the R-R interval time series and how this editing can influence the results of heart rate (HR) variability analyses. Measurement of HR variability from short and long-term electrocardiographic (ECG) recordings is a non-invasive method for evaluating cardiac autonomic regulation. HR variability provides information about the sympathetic-parasympathetic autonomic balance.

Effects of postectopic heart rate turbulence on measures of heart rate variability in patients after an acute myocardial infarction.

Background: Heart rate (HR) turbulence lasting up to 15 beats after ventricular premature beats (VPBs) may have profound effects on HR variability measures. Aim of this study was to examine the effects of HR turbulence on HR variability measures.

Methods: We developed an algorithm, which deletes 15 consecutive RR intervals after VPBs and examined the effects of the HR turbulence removal on the HR variability measures in patients after an acute myocardial infarction (AMI).

Respiratory sinus arrhythmia as a predictor of sudden cardiac death after myocardial infarction.

Background: Measurement of high-frequency (HF) spectral power of heart rate (HR) variability has not been able to identify the patients at risk of sudden cardiac death (SCD) despite the experimental evidence of protective role of vagal activity for fatal arrhythmias.

Aim: We developed a novel respiratory sinus arrhythmia (RSA) analysis method and tested its ability to predict SCD after an acute myocardial infarction.

Method: The RSA analysis method was developed in 13 subjects from simultaneous recordings of respiration and R-R intervals.

Effects and significance of premature beats on fractal correlation properties of R-R interval dynamics.

Background: Premature beats (PBs) have been considered as artifacts producing a bias in the traditional analysis of heart rate (HR) variability. We assessed the effects and significance of PBs on fractal scaling exponents in healthy subjects and patients with a recent myocardial infarction (AMI).

Methods: Artificial PBs were first generated into a time series of pure sinus beats in 20 healthy subjects and 20 post-AMI patients.