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In Silico Cardiac Risk Assessment in Patients With Long QT Syndrome Type 1: Clinical Predictability of Cardiac Models

Hoefen, Ryan; Reumann, Matthias; Goldenberg, Ilan; Moss, Arthur J.; O-Uchi, Jin; Gu, Yiping; McNitt, Scott; Zareba, Wojciech; Jons, Christian and Kanters, Jorgen K., et al. (2012) In Journal of the American College of Cardiology 60(21). p.2182-2191
Abstract
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... (More)
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. (J Am Coll Cardiol 2012;60:2182-91) (C) 2012 by the American College of Cardiology Foundation (Less)
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published
subject
keywords
IKs, KCNQ1, KCNQ2, LQT, QT
in
Journal of the American College of Cardiology
volume
60
issue
21
pages
2182 - 2191
publisher
Elsevier USA
external identifiers
  • wos:000311077600009
  • scopus:84869051881
ISSN
0735-1097
DOI
10.1016/j.jacc.2012.07.053
language
English
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yes
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361bb984-64c8-49c2-8641-93c501061a86 (old id 3243939)
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2013-01-07 09:33:09
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2017-01-01 03:49:51
@article{361bb984-64c8-49c2-8641-93c501061a86,
  abstract     = {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 &lt; 0.0001]; &gt;= upper quartile hazard ratio: 2.80 [p &lt; 0.0001]) and life-threatening events (aborted cardiac arrest/sudden cardiac death: 27% per 10-ms increment [p = 0.03]; &gt;= 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 (&lt;500 ms), the risk associated with TRP was maintained (36% per 10 ms [p &lt; 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. (J Am Coll Cardiol 2012;60:2182-91) (C) 2012 by the American College of Cardiology Foundation},
  author       = {Hoefen, Ryan and Reumann, Matthias and Goldenberg, Ilan and Moss, Arthur J. and O-Uchi, Jin and Gu, Yiping and McNitt, Scott and Zareba, Wojciech and Jons, Christian and Kanters, Jorgen K. and Platonov, Pyotr and Shimizu, Wataru and Wilde, Arthur A. M. and Rice, John Jeremy and Lopes, Coeli M.},
  issn         = {0735-1097},
  keyword      = {IKs,KCNQ1,KCNQ2,LQT,QT},
  language     = {eng},
  number       = {21},
  pages        = {2182--2191},
  publisher    = {Elsevier USA},
  series       = {Journal of the American College of Cardiology},
  title        = {In Silico Cardiac Risk Assessment in Patients With Long QT Syndrome Type 1: Clinical Predictability of Cardiac Models},
  url          = {http://dx.doi.org/10.1016/j.jacc.2012.07.053},
  volume       = {60},
  year         = {2012},
}