Abstracts

RATIONALE: The differentiation of patients with psychogenic non-epileptic seizures (PNES) and epileptic seizures (ES) is very important. The aim of this study was to identify variables that best predict patients ultimately diagnosed with PNES or ES via long-term video-EEG monitoring. The variables found to best predict clinical group status could then be emphasized in the clinical evaluation of patients presenting with seizures.
METHODS: The two groups (PNES: n = 28; ES: n = 33) received their respective diagnoses following a multidisciplinary inpatient video-EEG monitoring evaluation and for the PNES group, exclusion of a physiological etiology. Demographic (age, gender, education), historical (age of seizure onset, past psychiatric history, past history of sexual and/or physical abuse, past history of neurologic illness/trauma other than seizures), and objective psychological (general intellectual/memory and personality measure of conversion symptoms) variables were obtained and compared between the two groups using nonparametric, univariate, and multivariate statistical procedures.
RESULTS: The two groups were comparable in terms of age, gender, education, Full Scale IQ, and presence of neurological history other than seizures. When compared to the ES group, the PNES patients demonstrated a significantly older age of seizure onset (p [lt] .001), higher proportion of cases with a past history of psychiatric illness (p [lt] .001) and sexual/physical abuse (p [lt] .001), and higher obtained scores on the Conversion subscale of the Personality Assessment Inventory (PAI; p [lt] .001) and WMS-III General Memory Index (p [lt] .001). A stepwise logistic multiple regression analysis using the entire variable set was then undertaken to ascertain which variable(s) best predicated group membership. Results revealed a past history of sexual/physical abuse (p [lt] .001) to be the strongest predictor with an overall correct classification rate of 78%. The Conversion subscale of the PAI approached significance (p = .054) but when combined with history of sexual/physical abuse failed to add any additional predictive power. Odds-ratio calculations of these data revealed that patients with a history of sexual and/or physical abuse who present to an inpatient epilepsy monitoring unit are 13 times more likely to be ultimately diagnosed with PNES rather than ES.
CONCLUSIONS: As has been previously reported in the literature, we found that a history of sexual/physical abuse is strongly associated with PNES and according to our data, is the most salient variable in predicting this diagnosis. The PAI, age of seizure onset, and history of psychiatric illness are variables that may also be useful in contributing diagnostic clarity to patients presenting for evaluation of seizures.