Heart rate and autonomic biomarkers distinguish convulsive epileptic vs. functional or dissociative seizures

20-40% of individuals whose seizures are not controlled by anti-seizure medications exhibit manifestations comparable to epileptic seizures (ES), but there are no EEG correlates. These events are called functional or dissociative seizures (FDS). Due to limited access to EEG-monitoring and inconclusive results, we aimed to develop an alternative diagnostic tool that distinguishes ES vs. FDS. We evaluated the temporal evolution of ECG-based measures of autonomic function (heart rate variability, HRV) to determine whether they distinguish ES vs. FDS.

The prospective study includes patients admitted to the University of Rochester Epilepsy Monitoring Unit. Participants are 18-65 years old, without therapies or co-morbidities associated with altered autonomics. A habitual ES or FDS is recorded during admission. HRV analysis is performed to evaluate the temporal changes in autonomic function during the peri‑ictal period (150-minutes each pre-/post-ictal). We determined if autonomic measures distinguish ES vs. FDS.

The study includes 53 ES and 46 FDS. Temporal evolution of HR and autonomics significantly differ surrounding ES vs. FDS. The pre-to-post-ictal change (delta) in HR differs surrounding ES vs. FDS, stratified for convulsive and non-convulsive events. Post-ictal HR, total autonomic (SDNN & Total Power), vagal (RMSSD & HF), and baroreflex (LF) function differ for convulsive ES vs. convulsive FDS. HR distinguishes non-convulsive ES vs. non-convulsive FDS with ROC>0.7, sensitivity>70%, but specificity<50%. HR-delta and post-ictal HR, SDNN, RMSSD, LF, HF, and Total Power each distinguish convulsive ES vs. convulsive FDS (ROC, 0.83-0.98). Models with HR-delta and post-ictal HR provide the highest diagnostic accuracy for convulsive ES vs. convulsive FDS: 92% sensitivity, 94% specificity, ROC 0.99).

HR and HRV measures accurately distinguish convulsive, but not non-convulsive, events (ES vs. FDS). Results establish the framework for future studies to apply this diagnostic tool to more heterogeneous populations, and on out-of-hospital recordings, particularly for populations without access to epilepsy monitoring units.