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Predictors of unfavorable course of acute myocarditis with reduced left ventricular ejection fraction

Early prediction of myocarditis clinical course still remains one of the actual tasks of cardiological science, which has a significant practical value. The purpose of the study was to determine the predictors of unfavorable course of myocarditis with reduced ejection fraction (EF) of the left ventricle (LV) on the basis of follow-up during 24 months. The study included 90 patients with acute myocarditis and reduced LV EF, who were examined in the first month after the disease onset, after 6, 12 and 24 months of follow-up. All patients underwent for echocardiography, Holter monitoring of the electrocardiogram and cardiac magnetic resonance imaging. Statistical processing of the results was performed using the Excel XP software (Місrosoft Office, USA) and Statistica for Windows v. 6.0 (Statsoft, USA). It was found that restoration of cardiac contractility in patients with myocarditis and reduced LV EF began with an increase in the index of LV longitudinal global systolic strain, which occurred 6 months after the debut of the disease and was associated with a decrease in the number of LV segments affected by the inflammatory process, and a significant increase of LV EF and a decrease of LV end-diastolic volume were observed only 1 year after the disease onset. The predictors of cardiovascular events in patients with acute myocarditis during the next 24 months from the onset of the disease, were detected in the 1st month from the debut of the disease and included following pathological changes: value of the LV EF ≤ 30%; reduction of LV longitudinal global systolic strain ≤ 7.0%; evidence of non-sustained ventricular tachycardia, presence of inflammatory changes in ≥6 LV segments, presence of delayed enhancement in ≥ 5 LV segments. Prospects for further research are the creation of registries of patients with myocarditis on the basis of multicenter clinical trial results on a large number of patients surveyed in order to improve diagnosis, prediction of clinical course and identification of early diagnostic markers of cardiovascular events and quantitative risk assessment of their development.