AIMS Outcome predictors in myocarditis are not well defined; we aimed at identifying predictors of death, heart transplantation (HTx) and relapse before the introduction of immunosuppression. METHODS AND RESULTS From… Click to show full abstract
AIMS Outcome predictors in myocarditis are not well defined; we aimed at identifying predictors of death, heart transplantation (HTx) and relapse before the introduction of immunosuppression. METHODS AND RESULTS From 1992 to 2012 we consecutively included 466 patients (68% male, 37±17 years, single centre recruitment, median follow-up 50 months), 216 with clinically suspected and 250 with biopsy (Bx)-proven myocarditis. Serum anti heart (AHA) and antiintercalated disk (AIDA) auto-antibodies were measured by indirect immunofluorescence. We performed univariable and multivariable analysis of clinical and diagnostic features at diagnosis. Survival free from death or HTx at 10 years was 83% in the whole group and was lower in Bx- proven vs. clinically suspected myocarditis (76% vs 94% respectively, p<0.001). Female gender (hazard ratio (HR) 2.7, 95% Confidence Intervals (CI) 1.1-6.5), fulminant presentation (HR 13.77, CI 9.7-261.73), high-titre organ-specific AHA (HR 4.2, CI 1.2-14.7) and anti-nuclear antibodies (ANA) (HR 5.2, CI 2.1-12.8) were independent predictors of death or HTx; higher echocardiographic left ventricular ejection fraction (LVEF) at diagnosis was protective, with a 0.93 times risk reduction for each 1% LVEF increase (CI 0.89-0.96). History of myocarditis at diagnosis (HR 8.5, CI 3.5-20.7) was independent predictor of myocarditis relapse at follow-up; older age was protective (HR 0.95, CI 0.91-0.99). Predictors of death, HTx and relapse did not differ in Bx-proven vs. clinically suspected myocarditis. CONCLUSIONS Young age and a previous myocarditis were independent relapse predictors; female gender, fulminant onset, lower LVEF at presentation and high-titre organ-specific AHA and ANA were independent predictors of death and HTx, suggesting that autoimmune features predict worse prognosis.
               
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