In silico cardiac risk assessment in patients with long QT syndrome: type 1: clinical predictability of cardiac models

Research output: Contribution to journalJournal articleResearchpeer-review

Ryan Hoefen, Matthias Reumann, Ilan Goldenberg, Arthur J Moss, Jin O-Uchi, Yiping Gu, Scott McNitt, Wojciech Zareba, Christian Jons, Jørgen K. Kanters, Pyotr G Platonov, Wataru Shimizu, Arthur A M Wilde, John Jeremy Rice, Coeli M Lopes

The study was designed to assess the ability of computer-simulated electrocardiography parameters to predict clinical outcomes and to risk-stratify patients with long QT syndrome type 1 (LQT1).
Original languageEnglish
JournalJournal of the American College of Cardiology
Issue number21
Pages (from-to)2182-91
Number of pages10
Publication statusPublished - 20 Nov 2012

    Research areas

  • Adolescent, Adult, Computer Simulation, DNA, Electrophysiologic Techniques, Cardiac, Female, Follow-Up Studies, Genotype, Heart Rate, Humans, KCNQ1 Potassium Channel, Male, Models, Cardiovascular, Mutation, Phenotype, Predictive Value of Tests, Prognosis, Registries, Risk Assessment, Risk Factors, Romano-Ward Syndrome, Young Adult

ID: 48052110