Harmonizing Heartbeats: A translational approach towards preventing life-threatening ventricular arrhythmias

Abstract

Cardiovascular diseases remain a leading cause of mortality worldwide, with sudden cardiac death, characterized by ventricular arrhythmias such as ventricular tachycardia (VT) or ventricular fibrillation (VF), being a significant contributor due to its abrupt onset and frequency. The Implantable Cardioverter-Defibrillator (ICD) stands as a crucial intervention to detect and terminate these life-threatening arrhythmias. While studies have demonstrated the survival benefits of ICD therapy, it does not address the underlying causes of arrhythmias and is associated with psychological challenges and reduced quality of life for recipients. Ideally, the ICD would not only terminate existing arrhythmias but also predict and prevent future occurrences, allowing for preemptive therapies like accelerated pacing. Short-Term Variability of Repolarization (STV) emerged as a potential predictive parameter for ventricular arrhythmias, reflecting the repolarization reserve of the heart. Understanding the protective effect of accelerated pacing on arrhythmia onset is crucial before implementing STV-guided pacing to prevent arrhythmias. This thesis focuses on improving the treatment of life-threatening ventricular arrhythmias by translating preclinical findings into clinical applications. Preclinical investigations utilized two animal models: the chronic atrioventricular block (CAVB) dog model and the ischemic pig model. These models elucidated the antiarrhythmic mechanisms of accelerated pacing and tested the feasibility of STV-guided pacing through ICDs to prevent arrhythmias. Additionally, methods for automatically measuring STV in ICDs were explored in both animal models. Clinical studies aimed to translate preclinical findings to human patients, examining changes in STV preceding spontaneous ventricular arrhythmias in ICD patients. The potential of pacing to reduce STV and the performance of an automatic STV algorithm on human signals measured with an ICD lead were evaluated. The preclinical section focused on the CAVB dog model and demonstrated that Torsade de Pointes (TdP) arrhythmias could be induced reproducibly, offering insights into new antiarrhythmic strategies. The increase in STV before TdP onset and its reduction during accelerated pacing suggested its potential as a predictive marker for pacing guidance. Moreover, research in the ischemic pig model underscored the importance of STV as a predictor of ventricular arrhythmias, highlighting the potential for automatic monitoring of arrhythmia risk through ICDs and other cardiac devices. In the clinical section, Holter registrations in ICD patients revealed an increase in STV preceding ventricular arrhythmias, validating its role as a predictive marker. Development of methods to automatically measure STV in intracardiac electrogram signals showed promise for clinical use, demonstrating reliability and the potential to guide pacing interventions effectively. In conclusion, STV emerges as a promising marker for monitoring impending ventricular arrhythmias through ICDs, offering avenues for preventive interventions like accelerated pacing. This represents a significant advancement in ICD therapies, providing personalized approaches to prevent life-threatening arrhythmias. This thesis contributes to a deeper understanding of the complex mechanisms behind ventricular arrhythmias and proposes innovative, personalized clinical approaches to prevent them.