Why the study?
To investigate the risk of detrimental cardiovascular events in an Asian population with ARVC/D, including incident malignant ventricular arrhythmias, new-onset HFrEF, and long-term mortality.
Cohort (n=109)
Yes
Clinical and electrocardiographic parameters, particularly QRS duration and epsilon waves, can be combined with machine learning algorithms to effectively predict malignant arrhythmias, heart failure, and mortality in patients with ARVC/D.
Background: Arrhythmogenic right ventricular cardiomyopathy/dysplasia (ARVC/D) is a hereditary disease characterized by fibrofatty infiltration of the right ventricular myocardium that predisposes affected patients to malignant ventricular arrhythmias, dual-chamber cardiac failure and sudden cardiac death (SCD). The present study aims to investigate the risk of detrimental cardiovascular events in an Asian population of ARVC/D patients, including the incidence of malignant ventricular arrhythmias, new-onset heart failure with reduced ejection fraction (HFrEF), as well as long-term mortality. Methods and Results: This was a territory-wide retrospective cohort study of patients diagnosed with ARVC/D between 1997 and 2019 in Hong Kong. This study consisted of 109 ARVC/D patients (median age: 61 [46–71] years; 58% male). Of these, 51 and 24 patients developed incident VT/VF and new-onset HFrEF, respectively. Five patients underwent cardiac transplantation, and 14 died during follow-up. Multivariate Cox regression identified prolonged QRS duration as a predictor of VT/VF (p < 0.05). Female gender, prolonged QTc duration, the presence of epsilon waves and T-wave inversion (TWI) in any lead except aVR/V1 predicted new-onset HFrEF (p < 0.05). The presence of epsilon waves, in addition to the parameters of prolonged QRS duration and worsening ejection fraction predicted all-cause mortality (p < 0.05). Clinical scores were developed to predict incident VT/VF, new-onset HFrEF and all-cause mortality, and all were significantly improved by machine learning techniques. Conclusions: Clinical and electrocardiographic parameters are important for assessing prognosis in ARVC/D patients and should in turn be used in tandem to aid risk stratification in the hospital setting.
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Lakhani et al. (2022) conducted a cohort in Arrhythmogenic right ventricular cardiomyopathy/dysplasia (ARVC/D) (n=109). Clinical and electrocardiographic risk score (QRS >98.5 ms, syncope, epsilon waves) vs. Lower risk score was evaluated on Incident ventricular tachycardia/ventricular fibrillation (VT/VF) (HR 1.74, 95% CI 1.30-2.33, p=<0.001).
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