Affiliation:
1. From the Department of Medicine, Cardiovascular Diseases Section, University of Oklahoma Health Sciences Center, Oklahoma City (P.L., R.L.); Universidad Simón Bolívar, Caracas, Venezuela (P.G.); Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor (R.G.); Electrical Engineering Department, Indiana University–Purdue University at Indianapolis (E.J.B.); Institut de Cibernética, Barcelona, Spain (P.C.); and the College of Physicians and Surgeons of Columbia...
Abstract
Background
Using the signal-averaged ECG (SAECG), this study developed a new electrical index for predicting arrhythmic events: abnormal intra-QRS potentials (AIQP).
Methods and Results
We studied 173 patients followed after myocardial infarction for a mean duration of 14±7 months. Sixteen arrhythmic events occurred, defined as sudden cardiac death, documented sustained ventricular tachycardia, or nonfatal cardiac arrest. Noninvasive indices of arrhythmia risk were measured, including AIQP, conventional SAECG, Holter, and left ventricular ejection fraction (LVEF). Abnormal intra-QRS potentials were defined as abnormal signals occurring anywhere within the QRS period. They were estimated with a lead-specific, parametric modeling method that removed the smooth, predictable part of the QRS. AIQPs are characterized by the remaining transient, unpredictable component of the QRS and manifest as low-amplitude notches and slurs. A combined XYZ-lead AIQP index exhibited higher specificity (95%) and predictive value (PV) (+PV, 47%; −PV, 94%) than the conventional SAECG in combination with Holter and LVEF (specificity, 89%; +PV, 25%; −PV, 93%).
Conclusions
AIQP improved specificity and predictive value, compared with conventional tests, for prediction of arrhythmic events. AIQP emerged as the best noninvasive univariate predictor of arrhythmic events after myocardial infarction in this study. A review of several other reports shows that AIQP in the present study outperformed the conventional predictive indices reported in those other data sets.
Publisher
Ovid Technologies (Wolters Kluwer Health)
Subject
Physiology (medical),Cardiology and Cardiovascular Medicine
Cited by
34 articles.
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