Predicting and preventing sudden cardiac death in myocardial infarction patients

Abstract

Aim. To investigate sudden cardiac death (SCD) predictors in patients after myocardial infarction (MI), to develop the strategy of risk stratification and SCD prevention.Material and methods. In total, 420 patients were examined at Day 10-14 after MI; follow-up period lasted for 1-4 years. General clinical examination, echocardiography, 24-hour electrocardiography (ECG) monitoring, late ventricular potentials (LVP) detection, active orthostatic test (AOT), heart rate variability (HRV) assessment at baseline and during functional tests, as well as psychological testing, were performed. Some participants underwent coronarography and endocardial electrophysiological examination. SCD risk was assessed by Cox multi-factor analysis and Kaplan-Meier survival curve method.Results. According to Cox multivariate regression analysis, the most important predictors included the following six parameters: LVP, HRV reduction, left ventricular ejection fraction <40 %, ventricular arrhythmias, previous MI, and hypotension in AOT Prognostic accuracy and positive predictive value of this model were high enough to assess SCD risk. Based on modeling results, in particular, on the presence of structural and trigger mechanisms of life-threatening arrhythmias, SCD risk stratification was performed. Differential preventive strategy was based on risk levels.Conclusion. In patients after MI, SCD risk stratification (very high, high, intermediate, and low risk), together with differential preventive measures, facilitated a two-fold reduction in sudden and cardiac death incidence, comparing to the control group.

Keywords

• sudden death
• myocardial infarction
• prognosis
• risk stratification
• structural and trigger factors