Why the study?
Recent developments such as artificial intelligence for ECG interpretation, genotype-phenotype-specific therapies, and emerging gene therapies prompted a summary of current understanding in congenital LQTs risk stratification and management.
This review provides a comprehensive update on the diagnosis, risk stratification, and management of congenital long QT syndrome, emphasizing the role of beta-blockers and emerging personalized therapies.
Risk stratification in congenital LQTs integrates clinical, ECG, and genetic data; leaves open prospective validation of thresholds for intervention.
Congenital long QT syndrome (LQTs) is an inherited cardiac condition resulting from cardiac repolarization abnormalities. Since the initial description of congenital LQTs by Jervell and Lange-Nielsen in 1957, our understanding of this condition has increased dramatically. A diagnosis of congenital LQTs is based on the medical history of the patient, alongside electrogram features, and a genetic variant that is identified in approximately 75% of cases. The appropriate risk stratification involves a multitude of factors, with β-blockers being the cornerstone of therapy. Recent developments, such as the incorporation of artificial intelligence (AI) for electrocardiogram (ECG) interpretation, genotype-phenotype-specific therapies, and emerging gene therapies, may potentially make personalized medicine in LQTs a reality in the near future. This review summarizes our current understanding of congenital LQTs, with a focus on risk stratification, current therapeutic interventions, and emerging developments in the management of congenital LQTs.
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Ranganathan et al. (2025) studied this question.
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