PubMed · 6167943
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D P Zipes. 1981. Pacing 1980.. https://doi.org/10.1111/j.1540-8159.1981.tb06541.x
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OBJECTIVES: The aim of the present study was to determine whether the combination of two markers that reflect depolarization and repolarization abnormalities can predict future arrhythmic events after acute myocardial infarction (MI). BACKGROUND: Although various noninvasive markers have been used to predict arrhythmic events after MI, the positive predictive value of the markers remains low. METHODS: We prospectively assessed T-wave alternans (TWA) and late potentials (LP) by signal-averaged electrocardiogram (ECG) and ejection fraction (EF) in 102 patients with successful determination results after acute MI. The TWA was analyzed using the power-spectral method during supine bicycle exercise testing. No antiarrhythmic drugs were used during the follow-up period. The study end point was the documentation of ventricular arrhythmias. RESULTS: The TWA was present in 50 patients (49%), LP present in 21 patients (21%), and an EF <40% in 28 patients (27%). During a follow-up period of 13 +/- 6 months, symptomatic, sustained ventricular tachycardia or ventricular fibrillation occurred in 15 patients (15%). The event rates were significantly higher in patients with TWA, LP, or an abnormal EF. The sensitivity and the negative predictive value of TWA in predicting arrhythmic events were very high (93% and 98%, respectively), whereas its positive predictive value (28%) was lower than those for LP and EF. The highest positive predictive value (50%) was obtained when TWA and LP were combined. CONCLUSIONS: The combined assessment of TWA and LP was associated with a high positive predictive value for an arrhythmic event after acute MI. Therefore, it could be a useful index to identify patients at high risk of arrhythmic events.
Over the past years, techniques of nonlinear dynamics have gained increasing attention in cardiology. This kind of partly interdisciplinary research is supposed to provide a better understanding of cardiac disease, especially in the field of tachyarrhythmia. This article intends to introduce the principles of diagnostic procedures in terms of nonlinear dynamics, chaos theory and stochastic processes related to cardiology. An introduction to a new technique of wavelet analysis is given, and possible applications in the quantitative classification of high-risk patients for sudden cardiac death are discussed.
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