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A new prediction model for ventricular arrhythmias in arrhythmogenic right ventricular cardiomyopathy
Johns Hopkins Univ Hosp, MD 21287 USA; Univ Montreal, Canada.
Netherlands Heart Inst, Netherlands; Univ Utrecht, Netherlands.
Univ Montreal, Canada.
Johns Hopkins Univ Hosp, MD 21287 USA.
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2019 (English)In: European Heart Journal, ISSN 0195-668X, E-ISSN 1522-9645, Vol. 40, no 23, p. 1850-1858Article in journal (Refereed) Published
Abstract [en]

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 amp;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).

Place, publisher, year, edition, pages
OXFORD UNIV PRESS , 2019. Vol. 40, no 23, p. 1850-1858
Keywords [en]
Arrhythmogenic right ventricular cardiomyopathy; Implantable cardioverter-defibrillators; Sudden cardiac death; Ventricular arrhythmias
National Category
Cardiac and Cardiovascular Systems
Identifiers
URN: urn:nbn:se:liu:diva-161418DOI: 10.1093/eurheartj/ehz103ISI: 000490135400009PubMedID: 30915475OAI: oai:DiVA.org:liu-161418DiVA, id: diva2:1367033
Note

Funding Agencies|Canadian Heart Rhythm Society George Mines Traveling Fellowship; Montreal Heart Institute Foundation Bal du Coeur bursary; Fondation LeducqLeducq Foundation [16 CVD 02]; Dutch Heart FoundationNetherlands Heart Foundation [2015T058]; Netherlands Organisation for Scientific ResearchNetherlands Organization for Scientific Research (NWO) [040.11.586]; Netherlands Heart Institute [06901]; Swiss National Science FoundationSwiss National Science Foundation (SNSF) [320030_160327]; UMC Utrecht 2017 Alexandre Suerman Stipend; UMC Utrecht Fellowship Clinical Research Talent; European Unions Horizon 2020 research and innovation program under the ERA-NET Co-fund action [680969]; Dr Francis P. Chiaramonte Private Foundation; Leyla Erkan Family Fund for ARVD Research; Dr Satish, Rupal, and Robin Shah ARVD Fund at Johns Hopkins; Bogle Foundation; Healing Hearts Foundation; Peter French Memorial Foundation; Wilmerding Endowments; Georg und Bertha Schwyzer-Winiker Foundation; Baugarten Foundation; Swiss Heart Foundation; Leonie-Wild Foundation; Marvin and Philippa Carsley Chair of Medicine; UCL Hospitals NIHR Biomedical Research Centre

Available from: 2019-10-31 Created: 2019-10-31 Last updated: 2019-12-12

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