Document Detail


Comparison of heart rate variability parameters during complex partial seizures and psychogenic nonepileptic seizures.
MedLine Citation:
PMID:  22642646     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
Purpose:  Psychogenic nonepileptic seizures (PNES) superficially resemble epileptic seizures. Little is known about ictal autonomic nervous system (ANS) activity changes in epilepsy and PNES. This study compares ictal heart rate variability (HRV) parameters as a reflection of ANS tone in epileptic seizures and PNES, and explores differences between interictal and ictal ANS tone in both patient groups. Methods:  Ictal HRV parameters were extracted from single-lead electrocardiography (ECG) data collected during video-electroencephalography (EEG) recordings of 26 patients with medically refractory temporal lobe epilepsy and 24 age- and sex-matched patients with PNES. One seizure per patient in a resting, wake, supine state was analyzed. Interictal ECG data were available for comparison from 14 patients in both groups. HRV parameters in time and frequency domains were analyzed (low frequency [LF], high frequency [HF], standard deviation of all consecutive normal R wave intervals [SDNN], square root of the mean of the sum of the squares of differences between adjacent normal R wave intervals [RMSSD]). CVI (cardiovagal index), CSI (cardiosympathetic index), and ApEn (approximate entropy) were calculated from Lorenz plots. Key Findings:  There were significant differences between ictal HRV measures during epileptic and nonepileptic seizures in the time and frequency domains. CSI (p < 0.001) was higher in epileptic seizures. Time interval between two consecutive R waves in the ECG (RR interval) (p = 0.002), LF (p = 0.02), HF (p = 0.003), and RMSSD (p = 0.003) were significantly lower during epileptic seizures. Binary logistic regression yielded a significant model based on the differences in CSI classifying 88% of patients with epilepsy and 73% of patients with PNES correctly. The comparison between resting and ictal states in both seizure disorders revealed significant differences in RR interval (epilepsy p < 0.001, PNES p = 0.01), CSI (epilepsy p < 0.001, PNES p = 0.02), HF (epilepsy p = 0.002, PNES p = 0.03), and RMSSD (epilepsy p = 0.004, PNES p = 0.04). In patients with epilepsy there were also significant differences in ictal versus interictal mean values of ApEn (p = 0.03) and LF (p = 0.04). Although CSI was significantly higher, the other parameters were lower during the seizures. Stepwise binary regression in the 14 patients with epilepsy produced a significant model differentiating resting state from seizures in 100% of cases. The same statistical approach did not yield a significant model in the PNES group. Significance:  Our results show greater ANS activation in epileptic seizures than in PNES. The biggest ictal HRV changes associated with epileptic seizures (CSI, HF, and RMSSD) reflect high sympathetic system activation and reduced vagal tone. The reduced ApEn also reflects a high sympathetic tone. The observed ictal alterations of HRV patterns may be a more specific marker of epileptic seizures than heart rate changes alone. These altered HRV patterns could be used to detect seizures and also to differentiate epileptic seizures from PNES. Larger studies are justified with intergroup and intragroup comparisons between ictal and resting states.
Authors:
Athi Ponnusamy; Jefferson L B Marques; Markus Reuber
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2012-5-29
Journal Detail:
Title:  Epilepsia     Volume:  -     ISSN:  1528-1167     ISO Abbreviation:  -     Publication Date:  2012 May 
Date Detail:
Created Date:  2012-5-30     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  2983306R     Medline TA:  Epilepsia     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Copyright Information:
Wiley Periodicals, Inc. © 2012 International League Against Epilepsy.
Affiliation:
Department of Clinical Neurophysiology, Royal Hallamshire Hospital, Sheffield, United Kingdom Institute of Biomedical Engineering, Department of Electrical Engineering, Federal University of Santa Catarina, Florianópolis, Brazil Academic Neurology Unit, Royal Hallamshire Hospital, University of Sheffield, Sheffield, United Kingdom.
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