Young Investigator Awards Competition - Basic Science Finalists-YIA Basic

Video Transcription

Video Summary

The 2020 Young Investigators Basic Science Competition featured three finalists presenting their innovative research. Dr. Rogers presented his work on using machine learning to improve risk stratification for sudden cardiac arrest. By applying machine learning algorithms to ventricular action potentials, he was able to predict clinical outcomes such as ventricular arrhythmias and death. He also identified specific ion channel abnormalities associated with these outcomes. Dr. Wimbo's presentation focused on the effects of thoracic epidural anesthesia on autonomic and electrophysiological function in the setting of chronic myocardial infarction. His study found that thoracic epidural anesthesia had antiarrhythmic effects, prolonging action potential duration and improving vagal function. Finally, Jonathan Huang presented his research on the effects of thoracic epidural anesthesia on the chronically infarcted porcine heart. His study demonstrated that thoracic epidural anesthesia prolonged atrial and ventricular effective refractory periods, preserved sympathetic and parasympathetic function, and enhanced vagal afferent efferent function. It also suppressed ventricular arrhythmias and reduced heterogeneity in activation. Overall, these presentations showcased the innovative research being conducted in the field of cardiac electrophysiology and highlighted potential new approaches to risk stratification and antiarrhythmic therapies.

Keywords

2020 Young Investigators Basic Science Competition

machine learning

risk stratification

sudden cardiac arrest

ventricular action potentials

ventricular arrhythmias

ion channel abnormalities

thoracic epidural anesthesia

autonomic function

electrophysiological function