Matthias Goernig

Comparison of nonlinear methods symbolic dynamics, detrended fluctuation, and Poincaré plot analysis in risk stratification in patients with dilated cardiomyopathy

Dilated cardiomyopathy (DCM) has an incidence of about 20100 000 new cases per annum and accounts for nearly 10 000 deaths per year in the United States. Approximately 36% of patients with dilated cardiomyopathy (DCM) suffer from cardiac death within five years after diagnosis. Currently applied methods for an early risk prediction in DCM patients are rather insufficient. The objective of this study was to investigate the suitability of short-term nonlinear methods symbolic dynamics (STSD), detrended fluctuation (DFA), and Poincare plot analysis (PPA) for risk stratification in these patients. From 91 DCM patients and 30 healthy subjects (REF), heart rate and blood pressure variability (HRV, BPV), STSD, DFA, and PPA were analyzed. Measures from BPV analysis, DFA, and PPA revealed highly significant differences (p<0.0011) discriminating REF and DCM. For risk stratification in DCM patients, four parameters from BPV analysis, STSD, and PPA revealed significant differences between low and high risk (maximum sensitivity: 90%, specificity: 90%). These results suggest that STSD and PPA are useful nonlinear methods for enhanced risk stratification in DCM patients.

Peripheral Arterial Disease Alters Heart Rate Variability in Cardiovascular Patients

Background: Autonomic regulation analysis is useful in risk stratification of ventricular tachycardia and sudden cardiac death in chronic heart failure (CHF). Heart rate variability (HRV) reflects the condition of autonomic regulation. For analyzing the autonomic control the whole cardiovascular system has to be considered. Therefore, the aim of our study was to assess the influence of peripheral arterial disease (PAD) on the autonomic regulation.

Vortex shaped current sources in a physical torso phantom.

Recent studies reported differential information in human magnetocardiogram and in electrocardiogram. Vortex currents have been discussed as a possible source of this divergence. With the help of physical phantom experiments, we quantified the influence of active vortex currents on the strength of electric and magnetic signals, and we tested the ability of standard source localization algorithms to reconstruct vortex currents. The active vortex currents were modeled by a set of twelve single current dipoles arranged in a circle and mounted inside a phantom that resembles a human torso. Magnetic and electric data were recorded simultaneously while the dipoles were switched on stepwise one after the other. The magnetic signal strength increased continuously for an increasing number of dipoles switched on. The electric signal strength increased up to a semicircle and decreased thereafter. Source reconstruction with unconstrained focal source models performed well for a single dipole only (less than 3-mm localization error). Minimum norm source reconstruction yielded reasonable results only for a few of the dipole configurations. In conclusion active vortex currents might explain, at least in part, the difference between magnetically and electrically acquired data, but improved source models are required for their reconstruction.

Blood Pressure Variability as Sign of Autonomic Imbalance in Patients with Idiopathic Dilated Cardiomyopathy

Background:  The problem of identifying idiopathic dilated cardiomyopathy (IDC) patients who are at risk of sudden death is still unsolved. The presence of autonomic imbalance in patients with IDC might predict sudden death and tachyarrhythmic events. The aim of this study was to analyze the suitability of blood pressure variability (BPV) compared to heart rate variability (HRV) for noninvasive risk stratification in IDC patients.

Altered Autonomic Cardiac Control Predicts Restenosis After Percutaneous Coronary Intervention

Background: Early and late restenosis in up to 30% remains a major problem for long‐term success after percutaneous coronary intervention (PCI). Compared to bare metal stents, the use of drug‐eluting stents reduces restenosis below 10%, but implant coasts have to be considered. In restenosis noninvasive testing lacks diagnostic power. We applied a new approach to identify patients with a high risk for restenosis after PCI by combining heart rate (HR) and blood pressure variability (BPV) analyses.

Multivariate and multidimensional analysis of cardiovascular oscillations in patients with heart failure.

Abstract Within 5 years of first diagnosis, nearly 60% of patients with heart failure (HF) suffer from cardiac death. Early diagnosis of HF and reliable risk prediction are still required. Therefore, the objective of this study was to develop a parameter set for enhanced risk stratification in HF patients. In 43 patients suffering from HF (NYHA class ≥II, ejection fraction <45%) and 10 healthy subjects (REF), heart rate and blood pressure variability (HRV and BPV), interactions between heart rate and blood pressure (joint symbolic dynamics, JSD) and blood pressure morphology (BPM) were analysed. BPV, BPM and JSD measures revealed high significance (p<0.0001) in discriminating REF and HF. A set of three parameters from BPV, JSD and BPM was developed for risk stratification (sensitivity 76.5%, specificity 84.2%, area under the receiver operating characteristic curve 81.4%) in patients with HF.

Low HRV entropy is strongly associated with myocardial infarction

Abstract Heart rate variability (HRV) is a marker of autonomous activity in the heart. An important application of HRV measures is the stratification of mortality risk after myocardial infarction. Our hypothesis is that the information entropy of HRV, a non-linear approach, is a suitable measure for this assessment. As a first step, to evaluate the effect of myocardial infarction on the entropy, we compared the entropy to standard HRV parameters. The entropy was estimated by compressing the tachogram with Bzip2. For univariate comparison, statistical tests were used. Multivariate analysis was carried out using automatically generated decision trees. The classification rate and the simplicity of the decision trees were the two evaluation criteria. The findings support our hypothesis. The meanNN-normalized entropy is reduced in patients with myocardial infarction with very high significance. One entropy parameter alone exceeds the discrimination strength of multivariate standards-based trees.

QT variability improves risk stratification in patients with dilated cardiomyopathy

Recently it could be demonstrated that systolic and diastolic blood pressure variability (BPV) as well as segmented Poincare plot analysis (SPPA) contribute to risk stratification in patients suffering from dilated cardiomyopathy (DCM). The aim of this study was to improve the risk stratification applying a multivariate technique including QT variability (QTV). We enrolled and significantly separated 56 low risk and 13 high risk DCM patients by nearly all applied BPV and QTV methods, but not with traditional heart rate variability analysis. The optimum set of two indices calculating the multivariate discriminate analysis (DA) included one BPV index calculated by symbolic dynamics method (DBP(Shannon)) and one index calculated from QTV (QTV(log)) achieving an area under the receiver operating characteristics curve (AUC) of 92%, sensitivity of 92.3% and specificity of 89.3%. Performing only electrocardiogram analysis, the optimum multivariate approach including indices from segmented Poincaré plot analysis and QTV still achieved a remarkable AUC of 88.3%. Increasing the number of indices for multivariate DA up to three, we achieved an AUC of 95.7%, sensitivity of 100% and specificity of 85.7% including one clinical, one BPV and one QTV index. Summarizing, we identified DCM patients with an increased risk of sudden cardiac death applying QTV analysis in a multivariate approach.

Detection of U wave activity in healthy volunteers by high-resolution magnetocardiography

INTRODUCTION The purpose of our study was to prove the existence of the U wave using magnetocardiograms (MCGs). METHODS The 31-channel MCGs of 25 healthy volunteers were recorded. The onset of the U wave was defined by newly developed spatial correlation analysis; and the end, by different approaches. RESULTS A U wave could be proved in all volunteers. In 10 volunteers (heart rate, 57 +/- 19 beats/min) in whom the U wave was found to be separated from the following P wave, the U waves end could be determined as a threshold value (U wave duration, 310 +/- 24 milliseconds). In 15 volunteers (heart rate, 70 +/- 38 beats/min), the end of the U waves was concealed by a continuous transition of the U waves into the following P waves. CONCLUSIONS The U wave seems to be a regular phenomenon and has a distinct spatiotemporal assembly.

Cardiac signal extraction in patients with Implantable Cardioverter Defibrillators

According to the guidelines the indication for Implantable Cardioverter Defibrillator (ICD) implantation is based on the ejection fraction. However, only a fraction of patients with implanted ICD shows live threatening arrhythmic events followed by adequate shocks. For this reason, further research is needed to find a more sensitive risk stratificator for patients prone to ventricular tachycardia or fibrillation. Unfortunately, standard prospective studies are time consuming. An alternative approach is to perform retrospective studies on patients with already implanted ICDs. So far, an implanted ICD is an exclusion criterion for Magnetic Field Imaging (MFI) studies. To overcome this problem several Blind Source Separation (BSS) algorithms have been tested to find out whether it is possible to separate the disturbances from the cardiac signals, in spite of the extreme difference in amplitude. Not all the methods are able to separate cardiac signal and disturbances. Temporal Decorrelation source Separation (TDSEP) is found to be superior both from a separation and performing point of view. For the first time it is possible to extract cardiac signals from measurements disturbed by an ICD, offering the possibility for a QRS-fragmentation analysis in patients with already implanted ICDs.