Key result
Four clinical predictors identify death or heart transplantation risk with ~89% accuracy.
Why the study?
Identifying early risk predictors in myocarditis is clinically relevant because patient outcomes are diverse.
Cohort (n=938)
No
A machine learning approach demonstrates that advanced NYHA class, reduced LVEF, heart failure at diagnosis, and giant cell myocarditis on biopsy are accurate predictors of mortality and need for heart transplantation in adults with myocarditis.
May aid risk stratification in myocarditis; leaves open prospective validation before guiding care.
Background and aims Identifying early risk predictors in myocarditis is clinically relevant, as patients’ outcomes may be very diverse. We aimed to explore predictors of death and heart transplant (HTx) in a large single-center cohort of adult patients with myocarditis using a machine learning (ML) technique. Materials and methods We retrospectively enrolled consecutive adult patients with biopsy-proven or clinically suspected myocarditis, collecting clinical, laboratory, and imaging data, both at diagnosis and during follow-up. A predictive model of death/HTx was developed using Random Forest (RF), ranking covariates according to their predictive accuracy. Results We included 938 patients (median age 36 years, 69% male) with clinically suspected (n=549) or biopsy-proven (n=389) myocarditis. During follow-up, 35 patients died, and 26 underwent HTx. The most important variables in predicting survival were NYHA class (variable importance, VIMP, 10%) LVEF (3.6%) and clinical presentation (2.5%) at diagnosis, histological type of myocarditis on endomyocardial biopsy (EMB)(2.9%), anti-endothelial cell antibodies (0.6%) and anti-nuclear antibodies (0.4%) positivity. Overall, the predictive accuracy of our RF model was good (89.2%, 95% C.I. 86.1-92.3). Conclusions Based on a ML approach, we found, with good predictive accuracy, that advanced NYHA class, reduced LVEF and heart failure at diagnosis, and giant cell myocarditis on EMB are predictors of worse prognosis in adult patients with myocarditis.
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Baritussio et al. (2026) conducted a cohort in Myocarditis (n=938). Clinical and histological risk predictors (advanced NYHA class, reduced LVEF, heart failure presentation, giant cell myocarditis) vs. Absence of these risk predictors was evaluated on Death and heart transplantation (OOB AUC 89.2%, 95% CI 86.1-92.3). Advanced NYHA class, reduced LVEF, heart failure presentation, and giant cell myocarditis predicted death and heart transplantation with an overall model accuracy of 89.2%.
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