A new prediction model for ventricular arrhythmias in arrhythmogenic right ventricular cardiomyopathy

Julia Cadrin-Tourigny, Laurens P. Bosman, Anna Nozza, Weijia Wang, Rafik Tadros, Aditya Bhonsale, Mimount Bourfiss, Annik Fortier, Øyvind H. Lie, Ardan M. Saguner, Anneli Svensson, Antoine Andorin, Crystal Tichnell, Brittney Murray, Katja Zeppenfeld, Maarten P. Van Den Berg, Folkert W. Asselbergs, Arthur A.M. Wilde, Andrew D. Krahn, Mario TalajicLena Rivard, Stephen Chelko, Stefan L. Zimmerman, Ihab R. Kamel, Jane E. Crosson, Daniel P. Judge, Sing Chien Yap, Jeroen F. Van Der Heijden, Harikrishna Tandri, Jan D.H. Jongbloed, Marie Claude Guertin, J. Peter Van Tintelen, Pyotr G. Platonov, Firat Duru, Kristina H. Haugaa, Paul Khairy, Richard N.W. Hauer, Hugh Calkins, Anneline S.J.M. Te Riele, Cynthia A. James

Research output: Contribution to journalArticlepeer-review

64 Scopus citations

Abstract

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 Five hundred and twenty-eight patients with a definite diagnosis and no history of sustained VAs/SCD at baseline, and results 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).

Original languageEnglish (US)
Pages (from-to)1850-1858
Number of pages9
JournalEuropean heart journal
Volume40
Issue number23
DOIs
StatePublished - Jun 14 2019

Keywords

  • Arrhythmogenic right ventricular cardiomyopathy
  • Implantable cardioverter-defibrillators
  • Sudden cardiac death
  • Ventricular arrhythmias

ASJC Scopus subject areas

  • Cardiology and Cardiovascular Medicine

Fingerprint

Dive into the research topics of 'A new prediction model for ventricular arrhythmias in arrhythmogenic right ventricular cardiomyopathy'. Together they form a unique fingerprint.

Cite this