An interactive in vivo and molecular investigation of the arrhythmogenic mechanisms of sudden cardiac death

Sudden cardiac arrest (SCA) claims over 300,000 lives per year in the U.S. alone. Prior to cardiac arrest alternating changes on the surface heart tracing (ECG) occur which are thought to arise from fluctuations in the electrical activity on the outside of the heart. These fluctuations are initially in synch with one another (concordant alternans) and then become out of synch (discordant alternans) before degenerating into ventricular fibrillation (VF). Although animal studies have demonstrated this, it has not been possible to study these events in man. We have developed a unique strategy to investigate these changes in patients undergoing open heart surgery. Using data from these measurements we will be able to better understand how and why dangerous rhythms develop. This will lead to improvements in identifying people at the greatest risk of sudden death and allow us to create computer models of electrical activity in the heart. This will aid the development of new treatments in these patients.

Sudden cardiac arrest (SCA) due to ventricular arrhythmias claims over 300,000 lives per year in the U.S and 50,000 lives per year in the UK). Prior to cardiac arrest alternating changes on the surface ECG frequently occur which are thought to arise from fluctuations in the electrical currents on the surface of the heart. These fluctuations are initially in phase with one another (concordant alternans) and then become out of phase (discordant alternans) before degenerating into ventricular fibrillation (VF). Although animal studies have demonstrated this, it has not been possible to study these events in man. We have developed a unique strategy to investigate these phenomena in patients undergoing cardiac surgery. This involves multielectrode mapping of the whole heart in combination with cellular electrophysiology & gene expression studies of tissue biopsied from sites susceptible to and resistant to alternans identified by our new on line analysis algorithms of alternans. We will use these data to (1) improve risk stratification of patients for implantable defibrillators based on ECG microvolt T wave alternans (2) improve our understanding of mechanisms underlying discordant alternans in patients with cardiac disease, (3) attempt to identify targets for pharmacological therapy, (4) identify novel pacing strategies to be implemented on implantable devices to prevent ventricular fibrillation, (5) provide unique human whole-heart and molecular data as a first stage in informing a computer model for future on-site, on-line interaction with combined whole-heart / cellular electrophysiology patient studies. This ?virtual heart? model could be employed to predict beat by beat events in the evolution of ventricular arrhythmia and test pacing strategies to abort the transition of alternans to VF. It could also be used to develop & evaluate the effects of new anti-dysrhythmic drugs and minimise the use of testing in animals.