Abstract
BACKGROUND: Sudden cardiac death (SCD) results from a complex interplay of abnormalities in autonomic function, myocardial substrate and vulnerability. We studied whether a combination of noninvasive risk stratification tests reflecting these key players could improve risk stratification. METHODS: Patients implanted with an ICD in whom 24-hr holter recordings were available prior to implant were included. QRS fragmentation (fQRS) was selected as measure of myocardial substrate and a high ventricular premature beat count (VPB >10/hr) for arrhythmic vulnerability. From receiver operating characteristics analysis, detrended fluctuation analysis (DFA), turbulence slope, and deceleration capacity were selected for autonomic function. Adjusted Cox regression analysis with comparison of C-statistics was performed to predict first appropriate shock (AS) and total mortality. RESULTS: A total of 220 patients were included in the analysis with an overall follow-up of 4.3 ± 3.1 years. A model including VPB >10/hr, inferior fQRS, and abnormal nonedited DFA was the best for prediction of AS after 1 year of follow-up with a trends toward improvement of the C-statistics compared to baseline (p = 0.055). The risk increased significantly with every abnormal test (HR 1.793, 95%CI 1.255-2.564). A model including fQRS in any region and abnormal edited DFA was the best for prediction of mortality after 3 years of follow-up with significant improvement of the C-statistics (p = 0.023). Each abnormal test was associated with a significant increase in mortality (HR 5.069, 95%CI 1.978-12.994). CONCLUSION: Combining noninvasive risk stratification tests according to their physiological background can improve the risk prediction of SCD and mortality.