Title | Scatter in repolarization timing predicts clinical events in post-myocardial infarction patients. | ||
Author | Segerson, Nathan M; Litwin, Sheldon E; Daccarett, Marcos; Wall, T Scott; Hamdan, Mohamed H; Lux, Robert L | ||
Journal | Heart Rhythm | Publication Year/Month | 2008-Feb |
PMID | 18242541 | PMCID | PMC2330016 |
Affiliation | 1.University of Utah School of Medicine, Department of Internal Medicine, Division of Cardiology, Salt Lake City, Utah, USA. Nathan.Segerson@hsc.utah.edu. |
BACKGROUND: Increased spatial and temporal dispersion of repolarization contributes to ventricular arrhythmogenesis. Beat-to-beat fluctuations in T-wave timing are thought to represent such dispersion and may predict clinical events. OBJECTIVE: The purpose of this study was to assess whether a novel noninvasive measure of beat-to-beat instability in T-wave timing would provide additive prognostic information in post-myocardial infarction patients. METHODS: We studied 678 patients from 12 hospitals with 32-lead 5-minute electrocardiogram recordings 6-8 weeks after myocardial infarction. Custom software identified R wave-to-T wave intervals (RTIs) and diastolic intervals (DIs). Repolarization scatter (RTI:DI(StdErr)) was then calculated as the standard error about the RTI:DI regression line. In addition, left ventricular ejection fraction (LVEF), short-term heart rate variability (HRV) parameters, and QT variability index were measured. Patients were followed for the composite endpoint of death or life-threatening ventricular arrhythmia. RESULTS: After a mean follow-up of 63 months, 134 patients met the composite endpoint. An RTI:DI(StdErr) >5.50 ms was associated with a 210% increase in arrhythmias or deaths (P <.001). After adjusting for LVEF, RTI:DI(StdErr) remained an independent predictor (P <.001). RTI:DI(StdErr) was also independent of short-term HRV parameters and the QT variability index. CONCLUSIONS: Increased repolarization scatter, a measure of high-frequency, cycle-length-dependent repolarization instability, predicts poor outcomes in patients after myocardial infarction.