Abstract
BACKGROUND: Experimental studies have demonstrated that unstable repolarization dynamics is a risk factor of arrhythmia. We have recently developed an algorithm to detect QT interval (QTI) instability from the clinical electrocardiogram (ECG). OBJECTIVE: To develop a clinical arrhythmia risk stratification index based on the detection of QTI instability. METHODS: Intracardiac ECGs were recorded at rest in 114 patients with implanted implantable cardioverter-defibrillators (ICDs). Patients were followed up until appropriate implantable cardioverter-defibrillator therapy or death occurred, whichever came first. Each ECG recording was divided into 1-minute episodes (minECGs); the instability in QTI dynamics, if any, of each minECG was detected with our algorithm. An arrhythmia risk index termed QTI instability index (QTII) was defined as the number of minECGs with unstable QTI dynamics normalized by the number of minECGs with premature activations. The performance of QTII in arrhythmia risk stratification was examined with survival analysis and was compared with other risk indices, such as the mean RR interval (RRI), the standard deviation of the RRI and the QTI, and the frequency of premature activation. We hypothesized that the index QTII, which accounts for multiple risk factors and their interdependence, performs better than indices quantifying individual arrhythmia risk factors in the stratification of arrhythmia risk. RESULTS: The results of survival analysis show that QTII outperformed all other studied indices in arrhythmia risk stratification and was the only independent indicator of arrhythmia propensity in a multivariate survival model. CONCLUSION: QTII is a promising arrhythmia risk stratification index.