Spectral Turbulence Analysis: A Valuable Method for the Prediction of Cardiac Events in Elderly Patients With Intraventricular Conduction Abnormalities.
BACKGROUND: Intraventricular block and its associated heart disease are common in the elderly. The aim of this study was to evaluate the ability of spectral turbulence analysis of signal-averaged electrocardiograms to predict the cardiac events of sudden death, sustained ventricular tachycardia, ventricular fibrillation, and syncope in elderly patients with wide QRS as seen on a standard 12 lead surface electrocardiogram. METHODS: We studied 51 consecutive elderly patients (age at or above 70 years), for whom at least 12 months of follow up was available following the initial signal-averaged electrocardiogram. The patients included 40 males, and 11 females, of whom 47 had coronary artery heart disease and 25 had a history of prior myocardial infarction, and 4 with dilated cardiomyopathy. The subjects were divided into 3 groups. Group I comprised 22 patients without any events; Group II included 16 patients with events-sudden death(N equals 6), ventricular tachycardia (N equals 5), ventircular fibrillation (N equals 1), and syncope (N equals 4); Group III consisted of 13 patients with nonsustained VT. The bipolar three-lead orthogonal signal-averaged electrocardiogram from each patient was analyzed for spectral turbulence. The optimal criteria for predicting cardiac events were determined by computer algorithm. RESULTS: Spectral turbulence predicted future cardiac events with a sensitivity of 88%, a specificity of 67%, a positive predictive accuracy of 67%, a negative predictive accuracy of 88%, and a total predictive accuracy of 74%. CONCLUSIONS: Spectral turbulence analysis of the signal-averaged electrocardiogram was found to be a highly sensitive predictor of serious cardiac events in elderly patients with a wide QRS complex.
Salazar
Manuel F.
MF
Department of Medicine, Division of Cardiology, St. Vincent's Medical Center of Richmond, Staten Island, NY.
Wei
Wang
W
Kelen
George J.
GJ
Bloomfield
Dennis A.
DA