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

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

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

29 Scopus citations


Objectives: 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). Background: Although attempts have been made to correlate mutation-specific ion channel dysfunction with patient phenotype in long QT syndrome, these have been largely unsuccessful. Systems-level computational models can be used to predict consequences of complex changes in channel function to the overall heart rhythm. Methods: A total of 633 LQT1-genotyped subjects with 34 mutations from multinational long QT syndrome registries were studied. Cellular electrophysiology function was determined for the mutations and introduced in a 1-dimensional transmural electrocardiography computer model. The mutation effect on transmural repolarization was determined for each mutation and related to the risk for cardiac events (syncope, aborted cardiac arrest, and sudden cardiac death) among patients. Results: Multivariate analysis showed that mutation-specific transmural repolarization prolongation (TRP) was associated with an increased risk for cardiac events (35% per 10-ms increment [p < 0.0001]; <upper quartile hazard ratio: 2.80 [p < 0.0001]) and life-threatening events (aborted cardiac arrest/sudden cardiac death: 27% per 10-ms increment [p = 0.03]; <upper quartile hazard ratio: 2.24 [p = 0.002]) independently of patients' individual QT interval corrected for heart rate (QTc). Subgroup analysis showed that among patients with mild to moderate QTc duration (<500 ms), the risk associated with TRP was maintained (36% per 10 ms [p < 0.0001]), whereas the patient's individual QTc was not associated with a significant risk increase after adjustment for TRP. Conclusions: These findings suggest that simulated repolarization can be used to predict clinical outcomes and to improve risk stratification in patients with LQT1, with a more pronounced effect among patients with a lower-range QTc, in whom a patient's individual QTc may provide less incremental prognostic information.

Original languageEnglish
Pages (from-to)2182-2191
Number of pages10
JournalJournal of the American College of Cardiology
Issue number21
StatePublished - 2012
Externally publishedYes


  • IKs
  • KCNQ1
  • KCNQ2
  • LQT
  • QT


Dive into the research topics of 'In silico cardiac risk assessment in patients with long QT syndrome: Type 1: Clinical predictability of cardiac models'. Together they form a unique fingerprint.

Cite this