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Combining noninvasive risk stratification parameters improves the prediction of mortality and appropriate ICD shocks
Bert Vandenberk1,2, M Juhani Junttila3, Tomas Robyns1,2
1Department of Cardiovascular Sciences, University of Leuven, Leuven, Belgium.
Insights
Combining noninvasive tests for autonomic function, myocardial substrate, and vulnerability improves sudden cardiac death (SCD) risk prediction. This approach enhances the identification of patients at higher risk for SCD and mortality.
Area of Science:
- Cardiology
- Biomedical Engineering
- Medical Diagnostics
Background:
- Sudden cardiac death (SCD) arises from complex interactions involving autonomic function, myocardial substrate, and vulnerability.
- Current risk stratification methods may not fully capture these multifactorial elements.
Purpose of the Study:
- To evaluate if combining noninvasive risk stratification tests can improve the prediction of SCD and mortality.
- To assess the additive value of tests reflecting autonomic function, myocardial substrate, and vulnerability.
Main Methods:
- Retrospective analysis of 220 patients implanted with an ICD, with pre-implant 24-hr Holter recordings.
- Utilized QRS fragmentation (fQRS) for myocardial substrate, ventricular premature beats (VPB >10/hr) for vulnerability, and detrended fluctuation analysis (DFA), turbulence slope, and deceleration capacity for autonomic function.
- Employed Cox regression analysis to predict appropriate shocks and mortality, comparing C-statistics.
Main Results:
- A combined model of VPB count, inferior fQRS, and abnormal DFA best predicted appropriate shocks within 1 year (p=0.055).
- Each abnormal test significantly increased the risk of appropriate shock (HR 1.793).
- A model including fQRS and abnormal DFA best predicted mortality within 3 years (p=0.023), with each abnormal test significantly increasing mortality risk (HR 5.069).
Conclusions:
- Combining noninvasive risk stratification tests based on physiological mechanisms improves SCD and mortality risk prediction.
- This integrated approach offers enhanced accuracy for identifying patients at high risk.
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.
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