Lb-456090-4 near-term prediction of life-threatening ventricular arrhythmias using artificial intelligence-enabled single lead ambulatory ecg

Identifying patients at high-risk of sudden cardiac death (SCD) in the mid to long-term remains particularly challenging. Accurate prediction of lethal ventricular arrhythmias in the near-term would enable preemptive actions to eventually prevent SCD. We hypothesized that artificial intelligence could be leveraged to identify a dynamic electrical profile on Holter ECG data heralding the near-term occurrence of sustained ventricular tachycardia (VT).