901–37 Computer Implementation of Wavelet Decomposition of Signal Averaged Electrocardiograms

Simple spectral analysis of signal averaged electrocardiograms (SAECG) has been the subject of numerous studies. However, the approaches reported so far appear inferior to the gold-standard time-domain analysis of SAECG. At the same time, the limitations of the time-domain analysis are well known and suggest that a more complex spectral analysis of SAECG will be of clinical importance. One of the possibilities for a more complex spectral analysis of SAECG is the so called Wavelet Analysis (WA) which is a time-scale technique suitable for the detection of small transient signals even if they are hidden in large waves. It is obtained by expanding the signal on a set of functions resulting from translation (time) and dilatation (scale) of a socalled “analysing wavelet”. WA provides a bidimensional representation of the signal in function of time and scale.In order to apply WA to SAECG, a special software package written in Borland Pascal has been developed. The WA of the signal s(t) is computed according to the formula Sg(a,b)=∫-∞+∞(1/√a)g(t)s(t)dt, where parameter a corresponds to the dilatation and parameter b to the time shift. The package uses the Morlet wavelet g(t)=exp(iωt) exp(-t2/2) for ω>=5.3. Empirically, 54 scales were chosen, defined by the scale parameter a=40×2-m, with m ranging from 0.95 to 3.6 with an increment of 0.05. The middle frequencies of the corresponding wavelets range from 250 to 40Hz. The package processes SAECG files in the standard ART format. To synthesise the information contained within all three wavelet transforms, a wavelet vector magnitude is obtained from the wavelets of three averaged X, Y, Z leads and computed as WM=(WX2+WY2+WZ2)1/2.The package has been employed in several studies which showed that (a) WA of SAECG is highly reproducible and (b) selected parameters of WA are superior to the time-domain analysis of SAECG when used for identification of survivors of acute myocardial infarction who are at high risk of sudden death and/or ventricular tachycardia. This comparison of WA and time domain analysis of SAECG used receiver operator and positive predictive characteristics which showed highly significant differences

Sudden Cardiac Death in Dialysis: Arrhythmic Mechanisms and the Value of Non-invasive Electrophysiology

Sudden Cardiac Death (SCD) is the leading cause of cardiovascular death in dialysis patients. This review discusses potential underlying arrhythmic mechanisms of SCD in the dialysis population. It examines recent evidence from studies using implantable loop recorders and from electrophysiological studies in experimental animal models of chronic kidney disease. The review summarizes advances in the field of non-invasive electrophysiology for risk prediction in dialysis patients focusing on the predictive value of the QRS-T angle and of the assessments of autonomic imbalance by means of heart rate variability analysis. Future research directions in non-invasive electrophysiology are identified to advance the understanding of the arrhythmic mechanisms. A suggestion is made of incorporation of non-invasive electrophysiology procedures into clinical practice.Key Concepts:– Large prospective studies in dialysis patients with continuous ECG monitoring are required to clarify the underlying arrhythmic mechanisms of SCD in dialysis patients.– Obstructive sleep apnoea may be associated with brady-arrhythmias in dialysis patients. Studies are needed to elucidate the burden and impact of sleeping disorders on arrhythmic complications in dialysis patients.– The QRS-T angle has the potential to be used as a descriptor of uremic cardiomyopathy.– The QRS-T angle can be calculated from routine collected surface ECGs. Multicenter collaboration is required to establish best methodological approach and normal values.– Heart Rate Variability provides indirect assessment of cardiac modulation that may be relevant for cardiac risk prediction in dialysis patients. Short-term recordings with autonomic provocations are likely to overcome the limitations of out of hospital 24-h recordings and should be prospectively assessed

QRS complex and T wave planarity for the efficacy prediction of automatic implantable defibrillators.

OBJECTIVE To test the hypothesis that in recipients of primary prophylactic implantable cardioverter-defibrillators (ICDs), the non-planarity of ECG vector loops predicts (a) deaths despite ICD protection and (b) appropriate ICD shocks. METHODS Digital pre-implant ECGs were collected in 1948 ICD recipients: 21.4% females, median age 65 years, 61.5% ischaemic heart disease (IHD). QRS and T wave three-dimensional loops were constructed using singular value decomposition that allowed to measure the vector loop planarity. The non-planarity, that is, the twist of the three-dimensional loops out of a single plane, was related to all-cause mortality (n=294; 15.3% females; 68.7% IHD) and appropriate ICD shocks (n=162; 10.5% females; 87.7% IHD) during 5-year follow-up after device implantation. Using multivariable Cox regression, the predictive power of QRS and T wave non-planarity was compared with that of age, heart rate, left ventricular ejection fraction, QRS duration, spatial QRS-T angle, QTc interval and T-peak to T-end interval. RESULTS QRS non-planarity was significantly (p<0.001) associated with follow-up deaths despite ICD protection with HR of 1.339 (95% CI 1.165 to 1.540) but was only univariably associated with appropriate ICD shocks. Non-planarity of the T wave loop was the only ECG-derived index significantly (p<0.001) associated with appropriate ICD shocks with multivariable Cox regression HR of 1.364 (1.180 to 1.576) but was not associated with follow-up mortality. CONCLUSIONS The analysed data suggest that QRS and T wave non-planarity might offer distinction between patients who are at greater risk of death despite ICD protection and those who are likely to use the defibrillator protection

QRS micro-fragmentation as a mortality predictor.

AIMS Fragmented QRS complex with visible notching on standard 12-lead electrocardiogram (ECG) is understood to represent depolarization abnormalities and to signify risk of cardiac events. Depolarization abnormalities with similar prognostic implications likely exist beyond visual recognition but no technology is presently suitable for quantification of such invisible ECG abnormalities. We present such a technology. METHODS AND RESULTS A signal processing method projects all ECG leads of the QRS complex into optimized three perpendicular dimensions, reconstructs the ECG back from this three-dimensional projection, and quantifies the difference (QRS 'micro'-fragmentation, QRS-μf) between the original and reconstructed signals. QRS 'micro'-fragmentation was assessed in three different populations: cardiac patients with automatic implantable cardioverter-defibrillators, cardiac patients with severe abnormalities, and general public. The predictive value of QRS-μf for mortality was investigated both univariably and in multivariable comparisons with other risk factors including visible QRS 'macro'-fragmentation, QRS-Mf. The analysis was made in a total of 7779 subjects of whom 504 have not survived the first 5 years of follow-up. In all three populations, QRS-μf was strongly predictive of survival (P < 0.001 univariably, and P < 0.001 to P = 0.024 in multivariable regression analyses). A similar strong association with outcome was found when dichotomizing QRS-μf prospectively at 3.5%. When QRS-μf was used in multivariable analyses, QRS-Mf and QRS duration lost their predictive value. CONCLUSION In three populations with different clinical characteristics, QRS-μf was a powerful mortality risk factor independent of several previously established risk indices. Electrophysiologic abnormalities that contribute to increased QRS-μf values are likely responsible for the predictive power of visible QRS-Mf. KEY QUESTION KEY FINDING TAKE-HOME MESSAGE QRS-μf is a strong predictor of worsened survival. It can be assessed in standard short-term 12-lead electrocardiograms