Reviews in Cardiovascular Medicine (Jun 2022)

A Territory-Wide Study of Arrhythmogenic Right Ventricular Cardiomyopathy Patients from Hong Kong

  • Ishan Lakhani,
  • Jiandong Zhou,
  • Sharen Lee,
  • Ka Hou Christien Li,
  • Keith Sai Kit Leung,
  • Jeremy Man Ho Hui,
  • Yan Hiu Athena Lee,
  • Guoliang Li,
  • Tong Liu,
  • Wing Tak Wong,
  • Ian Chi Kei Wong,
  • Ngai Shing Mok,
  • Chloe Miu Mak,
  • Qingpeng Zhang,
  • Gary Tse

DOI
https://doi.org/10.31083/j.rcm2307231
Journal volume & issue
Vol. 23, no. 7
p. 231

Abstract

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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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