Predictors of Disease Progression in Patients with Left Ventricular Non-Dilated Cardiomyopathy

Background: Non-Dilated Left Ventricular Cardiomyopathy (NDLVC) is a highly heterogeneous and unexplored category of cardiomyopathies introduced in the 2023 European Society of Cardiology (ESC) guidelines. This study aims to identify factors associated with adverse remodeling in a large multicenter cohort of patients with NDLVC. Methods: 432 patients with NDLVC (63.4% male, mean age 39.4±14.6 years) with multiparametric characterization were enrolled from January 2010 to May 2023 in two high-volume Italian centers. Diagnosis followed ESC criteria. Endpoints were (I) worsening of left ventricular ejection fraction (LVEF) ≥10% from the baseline value (or group W), (II) evolution to dilated cardiomyopathy (DCM) (or group E), and (III) the concomitant occurrence of both (or group W+E), assessed at the latest available echocardiographic evaluation. Results: During a median follow-up of 77 months (IQR:48-109), 27.3% of patients experienced worsening LVEF, 28.9% progressed to DCM, and 18.3% reached the combined W+E endpoint. A multivariable model including positive genetic testing associated to myocardial inflammation, family history of cardiomyopathies and/or sudden cardiac death, intraventricular conduction delay, baseline echocardiographic LVEF<45%, a ring-like late gadolinium enhancement on cardiac magnetic resonance, and non-sustained ventricular tachycardia at baseline, had the strongest discrimination power for predicting worsening LVEF [AUC of 0.8 (95% CI: 0.75-0.86)], evolution to DCM [AUC 0.78 (95% CI: 0.73-0.84)] and the combined W+E [AUC 0.84 (95% CI: 0.79-0.89)]. Negative genetic testing reduced the risk across all the endpoints [(OR: 0.2, 95% CI: 0.1-0.4, p<0.001), (OR: 0.2, 95% CI: 0.1-0.4, p<0.001) and (OR: 0.1, 95% CI: 0.04-0.3, p<0.001), respectively]. Conclusions: In this large NDLVC cohort, in which 38% of patients showed an adverse remodelling over long-term follow-up, a multiparametric approach integrating deep phenotyping and genetics effectively identified high-risk patients.