Aims Arrhythmogenic right ventricular dysplasia/cardiomyopathy (ARVC) is characterized by ventricular arrhythmias (VAs) and sudden cardiac death (SCD). We aimed to develop a model for individualized prediction of incident VA/SCD in ARVC patients. Methods and results Five hundred and twenty-eight patients with a definite diagnosis and no history of sustained VAs/SCD at baseline, aged 38.2 ± 15.5 years, 44.7% male, were enrolled from five registries in North America and Europe. Over 4.83 (interquartile range 2.44–9.33) years of follow-up, 146 (27.7%) experienced sustained VA, defined as SCD, aborted SCD, sustained ventricular tachycardia, or appropriate implantable cardioverter-defibrillator (ICD) therapy. A prediction model estimating annual VA risk was developed using Cox regression with internal validation. Eight potential predictors were pre-specified: age, sex, cardiac syncope in the prior 6 months, non-sustained ventricular tachycardia, number of premature ventricular complexes in 24 h, number of leads with T-wave inversion, and right and left ventricular ejection fractions (LVEFs). All except LVEF were retained in the final model. The model accurately distinguished patients with and without events, with an optimism-corrected C-index of 0.77 [95% confidence interval (CI) 0.73–0.81] and minimal over-optimism [calibration slope of 0.93 (95% CI 0.92–0.95)]. By decision curve analysis, the clinical benefit of the model was superior to a current consensus-based ICD placement algorithm with a 20.6% reduction of ICD placements with the same proportion of protected patients ( P < 0.001). Conclusion Using the largest cohort of patients with ARVC and no prior VA, a prediction model using readily available clinical parameters was devised to estimate VA risk and guide decisions regarding primary prevention ICDs ( www.arvcrisk.com ).

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Heart failure (HF) is associated with metabolic perturbations, particularly of fatty acids (FAs), which remain to be better understood in humans. This study aimed at testing the hypothesis that HF patients with reduced ejection fraction display systemic perturbations in levels of energy-related metabolites, especially those reflecting dysregulation of FA metabolism, namely, acylcarnitines (ACs). Circulating metabolites were assessed using mass spectrometry (MS)-based methods in two cohorts. The main cohort consisted of 72 control subjects and 68 HF patients exhibiting depressed left ventricular ejection fraction (25.9 ± 6.9%) and mostly of ischemic etiology with ≥2 comorbidities. HF patients displayed marginal changes in plasma levels of tricarboxylic acid cycle-related metabolites or indexes of mitochondrial or cytosolic redox status. They had, however, 22-79% higher circulating ACs, irrespective of chain length ( < 0.0001, adjusted for sex, age, renal function, and insulin resistance, determined by shotgun MS/MS), which reflects defective mitochondrial β-oxidation, and were significantly associated with levels of NH-terminal pro-B-type natriuretic peptide levels, a disease severity marker. Subsequent extended liquid chromatography-tandem MS analysis of 53 plasma ACs in a subset group from the primary cohort confirmed and further substantiated with a comprehensive lipidomic analysis in a validation cohort revealed in HF patients a more complex circulating AC profile. The latter included dicarboxylic-ACs and dihydroxy-ACs as well as very long chain (VLC) ACs or sphingolipids with VLCFAs (>20 carbons), which are proxies of dysregulated FA metabolism in peroxisomes. Our study identified alterations in circulating ACs in HF patients that are independent of biological traits and associated with disease severity markers. These alterations reflect dysfunctional FA metabolism in mitochondria but also beyond, namely, in peroxisomes, suggesting a novel mechanism contributing to global lipid perturbations in human HF. Mass spectrometry-based profiling of circulating energy metabolites, including acylcarnitines, in two cohorts of heart failure versus control subjects revealed multiple alterations in fatty acid metabolism in peroxisomes in addition to mitochondria, thereby highlighting a novel mechanism contributing to global lipid perturbations in heart failure.Listen to this article's corresponding podcast at http://ajpheart.podbean.com/e/acylcarnitines-in-human-heart-failure/.

Aims Arrhythmogenic right ventricular dysplasia/cardiomyopathy (ARVC) is characterized by ventricular arrhythmias (VAs) and sudden cardiac death (SCD). We aimed to develop a model for individualized prediction of incident VA/SCD in ARVC patients. Methods and results Five hundred and twenty-eight patients with a definite diagnosis and no history of sustained VAs/SCD at baseline, aged 38.2 ± 15.5 years, 44.7% male, were enrolled from five registries in North America and Europe. Over 4.83 (interquartile range 2.44–9.33) years of follow-up, 146 (27.7%) experienced sustained VA, defined as SCD, aborted SCD, sustained ventricular tachycardia, or appropriate implantable cardioverter-defibrillator (ICD) therapy. A prediction model estimating annual VA risk was developed using Cox regression with internal validation. Eight potential predictors were pre-specified: age, sex, cardiac syncope in the prior 6 months, non-sustained ventricular tachycardia, number of premature ventricular complexes in 24 h, number of leads with T-wave inversion, and right and left ventricular ejection fractions (LVEFs). All except LVEF were retained in the final model. The model accurately distinguished patients with and without events, with an optimism-corrected C-index of 0.77 [95% confidence interval (CI) 0.73–0.81] and minimal over-optimism [calibration slope of 0.93 (95% CI 0.92–0.95)]. By decision curve analysis, the clinical benefit of the model was superior to a current consensus-based ICD placement algorithm with a 20.3% reduction of ICD placements with the same proportion of protected patients (P &lt; 0.001). Conclusion Using the largest cohort of patients with ARVC and no prior VA, a prediction model using readily available clinical parameters was devised to estimate VA risk and guide decisions regarding primary prevention ICDs (www.arvcrisk.com).