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.