Computer model appears to predict LQTS risk

A computer model designed to simulate repolarization successfully predicted clinical outcomes and improved risk stratification in patients with long QT syndrome type 1.

This research marks the first incident of cardiac modeling used as an arrhythmic risk predictor for patients, according to Ryan Hoefen, MD, PhD, of the University of Rochester School of Medicine and Dentistry, and colleagues.

“This is a strong proof-of-principle study showing that computer simulation can be used to predict risk of cardiac arrhythmias,” Coeli M. Lopes, PhD, of the Cardiovascular Research Institute at University of Rochester School of Medicine and Dentistry, said in a press release. “With this model, we can determine the influence of a single mutation on the much bigger overall response of the heart.”

Investigators examined 633 patients with long QT syndrome (LQTS) type 1 who had 34 mutations from several multinational long QT syndrome registries.

The computer model was designed by Matthias Reumann, PhD, and J. Jeremy Rice, PhD. According to the press release, the model includes 192 heart cells designed to function electrically, similar to the ventricle wall, by assigning properties to cells because on their position — inside, middle or outside — in the heart wall. The researchers determined cellular electrophysiology function for the mutations, which were introduced in the 1-D transmural electrocardiography computer model.

The mutation effect on transmural repolarization was determined for each mutation and related to the risk for cardiac events among patients, according to the study abstract.

Multivariate analysis revealed that mutation-specific transmural repolarization was associated with increased risk for cardiac events (35% per 10-ms increment [P<.0001]; ≥upper quartile HR= 2.8 [P<.0001]) and life-threatening events (aborted cardiac arrest/sudden cardiac arrest/sudden cardiac death: 27% per 10-ms increment [P=.03]; ≥upper quartile HR=2.24 [P=.002]). These findings were independent of the patients’ individual QT interval corrected for heart rate.

Subgroup analysis showed that increased risk associated with transmural repolarization held steady (36% per 10 ms; P<.0001) among patients with mild to moderate QTc duration (<500 ms). However, the same association between QTc and increased risk was not observed after adjustment for transmural repolarization, according to the abstract.

“We have shown that simulated transmural repolarization is a particularly strong marker of risk for cardiac events in this population, which may translate into changes in treatment decisions for identifying high-risk LQTS patients independently of traditional ECG markers,” the researchers wrote. “It would be recommended that patients with the identified prolonged transmural repolarization mutations (V254M, G314S, T3121 and L266P) should be considered to be at high risk for cardiac events even in the absence of QTc prolongation or other clinical risk factors.”

For more information:

Hoefen R. J Am Coll Cardiol. 2012;doi:10.1016/j.jacc.2012.07.053.

Disclosure:See the full study for a list of the researchers’ relevant financial disclosures.