Heart rate variability measures as biomarkers in patients with psychogenic nonepileptic seizures: Potential and limitations

Heart rate variability (HRV) metrics provide reliable information about the functioning of the autonomic nervous system (ANS) and have been discussed as biomarkers in anxiety and personality disorders. We wanted to explore the potential of various HRV metrics (VLF, LF, HF, SDNN, RMSSD, cardiovagal index, cardiosympathetic index, approximate entropy) as biomarkers in patients with psychogenic nonepileptic seizures (PNES). HRV parameters were extracted from 3-minute resting single-lead ECGs of 129 subjects (52 with PNES, 42 with refractory epilepsy and 35 age-matched healthy controls). Compared with healthy controls, both patient groups had reduced HRV (all measures P < 0.03). Binary logistic regression analyses yielded significant models differentiating between healthy controls and patients with PNES or patients with epilepsy (correctly classifying 86.2 and 93.5% of cases, respectively), but not between patients with PNES and those with epilepsy. Interictal resting parasympathetic activity and sympathetic activity differ between healthy controls and patients with PNES or those with epilepsy. However, resting HRV measures do not differentiate between patients with PNES and those with epilepsy.

► Compared with controls, both patient groups (those with psychogenic nonepileptic seizures and those with epilepsy) had reduced heart rate variability (P < 0.03). ► In particular, parasympathetic tone was lower and sympathetic tone was higher than in controls. ► Binary logistic regression analyses differentiated patients with psychogenic nonepileptic seizures and patients with epilepsy from controls (86% vs 93%). ► Future studies are needed to establish how the observed heart rate variability alterations can be best explained. ► They may prove a useful indicator of psychopathological subtype or outcome, particularly in PNES.