
The long QT syndrome (LQTS) has often been considered as a model to study the abnormalities of cardiac repolarization in humans because it represents a pure electrical disease with no evidence of cardiac structural abnormalities. The arrhythmogenic potential of prolonged ventricular repolarization has been extensively studied both in experimental models and at the clinical level in LQTS patients, and many studies pointed to the pathogenetic role of the dispersion of ventricular recovery times (i.e., dispersion of ventricular repolarization). In the last few years, a new critical knowledge has been achieved thanks to the molecular biology techniques that are unveiling the genetic bases of LQTS. Indeed, the understanding of the genes and mutations that may cause the LQTS opened the way to understanding the molecular determinants of the altered ventricular repolarization that can be found in LQTS patients. From the clinical standpoint, the traditional tools applied for the detection and quantification of the dispersion of ventricular repolarization (monophasic action potential, QT dispersion) showed their effectiveness but also their limitations. More recently, the availability of new algorithms and the development of powerful computerized supports allowed the evaluation of innovative techniques, which now represent possible attractive alternatives intended to quantify the degree of repolarization abnormalities in LQTS patients and possibly to noninvasively quantify the risk of cardiac events.
Electrocardiography, Long QT Syndrome, QT Dispersion, 616, Electrocardiography, Ambulatory, 610, Animals, Humans, Heart, Arrhythmias
Electrocardiography, Long QT Syndrome, QT Dispersion, 616, Electrocardiography, Ambulatory, 610, Animals, Humans, Heart, Arrhythmias
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 20 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
