RESUMEN
Background: Congenital long-QT syndrome (LQTS) is a major cause of sudden cardiac death (SCD) in young individuals, calling for sophisticated risk assessment. Risk stratification, however, is challenging as the individual arrhythmic risk varies pronouncedly, even in individuals carrying the same variant. Materials and Methods: In this study, we aimed to assess the association of different electrical parameters with the genotype and the symptoms in patients with LQTS. In addition to the heart-rate corrected QT interval (QTc), markers for regional electrical heterogeneity, such as QT dispersion (QTmax-QTmin in all ECG leads) and delta Tpeak/end (Tpeak/end V5 - Tpeak/end V2), were assessed in the 12-lead ECG at rest and during exercise testing. Results: QTc at rest was significantly longer in symptomatic than asymptomatic patients with LQT2 (493.4 ms ± 46.5 ms vs. 419.5 ms ± 28.6 ms, p = 0.004), but surprisingly not associated with symptoms in LQT1. In contrast, post-exercise QTc (minute 4 of recovery) was significantly longer in symptomatic than asymptomatic patients with LQT1 (486.5 ms ± 7.0 ms vs. 463.3 ms ± 16.3 ms, p = 0.04), while no such difference was observed in patients with LQT2. Enhanced delta Tpeak/end and QT dispersion were only associated with symptoms in LQT1 (delta Tpeak/end 19.0 ms ± 18.1 ms vs. -4.0 ms ± 4.4 ms, p = 0.02; QT-dispersion: 54.3 ms ± 10.2 ms vs. 31.4 ms ± 10.4 ms, p = 0.01), but not in LQT2. Delta Tpeak/end was particularly discriminative after exercise, where all symptomatic patients with LQT1 had positive and all asymptomatic LQT1 patients had negative values (11.8 ± 7.9 ms vs. -7.5 ± 1.7 ms, p = 0.003). Conclusion: Different electrical parameters can distinguish between symptomatic and asymptomatic patients in different genetic forms of LQTS. While the classical "QTc at rest" was only associated with symptoms in LQT2, post-exercise QTc helped distinguish between symptomatic and asymptomatic patients with LQT1. Enhanced regional electrical heterogeneity was only associated with symptoms in LQT1, but not in LQT2. Our findings indicate that genotype-specific risk stratification approaches based on electrical parameters could help to optimize risk assessment in LQTS.
