ArticleFrontiers in cardiovascular medicine2022
Genotype-Specific ECG-Based Risk Stratification Approaches in Patients With Long-QT Syndrome.
Article in Frontiers in cardiovascular medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 9 citations in OpenAlex.
- Differential effects of non-selective and cardio-selective beta-blocker therapy on ECG parameters in long QT syndrome type 1.International journal of cardiology. Heart & vasculature · 2026Article
- Research progress on the relationship between long QT syndrome (LQTS) and epilepsy: A review.Medicine · 2026Review
- A MATLAB Algorithm to Automatically Estimate the QT Interval and Other ECG Parameters and Validation Using a Machine Learning Approach in Congenital Long-QT Syndrome.Journal of cardiovascular translational research · 2025Article
- Current and future precision therapy approaches in the long QT syndrome.Medizinische Genetik : Mitteilungsblatt des Berufsverbandes Medizinische Genetik e.V · 2025Article
- Clinical, Electrical, and Mechanical Parameters in Potassium Channel-Mediated Congenital Long QT Syndrome.Journal of clinical medicine · 2025Article
- Article
Corrections and comments
- Erratum issued
Authors and funding
10 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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 (QT 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, 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.
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