ABS 102: Exploring circadian variations in autonomic input preceding ventricular tachycardia and ventricular fibrillation: a pathway to predictive models for sudden cardiac death

Sathvik Bodepudi, Steven Pogwizd MD

Van Wickle (2025) Volume 1, ABS 102

Introduction: This study investigates circadian variations in heart rate variability (HRV) and nonlinear
dynamics (NLD) leading up to VT/VF cardiac arrests among in-hospital patients, with a focus on comparing these patterns with a standard control group, ultimately aiming to
develop predictive models for sudden cardiac death (SCD). Sudden cardiac death (SCD) remains a significant public health concern, affecting between 300,000 and 400,000 Americans every year. Ventricular tachycardia (VT) and ventricular fibrillation (VF) are leading causes of SCD, often occurring unpredictably. There is a time-of-day variation in SCD with an early morning predominance that corresponds to early morning increase in sympathetic nervous activity. Analyzing HRV and NLD can reveal autonomic changes that precede these life-threatening arrhythmias.

Methods: We examined telemetry ECG data from patients who experienced VT/VF cardiac arrests at UAB Hospital, excluding those in ICUs or with conditions such as metastatic cancer. Using Kubios HRV Scientific analysis software, we assessed HRV indices (e.g., LF/HF ratio, RMSSD, TINN, AC) and NLD parameters (e.g., DFA𝛼1, DFA𝛼2, sample entropy).

Discussion: Our study underscores the importance of considering temporal patterns in arrhythmogenesis and supports the potential for HRV analysis in predicting sudden cardiac death. By comparing these patterns with a control, insights into the specific mechanisms underlying ventricular arrhythmias can be elucidated. This will also allow us to develop predictive analytics to help identify patients who are at risk for sudden death using HRV analysis of their ECG along with clinical factors (e.g. presence of CAD and/or CHF).