Logo image
Back
Using the Minnesota Multiphasic Inventory 2, EEGs, and clinical data to predict nonepileptic events
Journal article   Peer reviewed

Using the Minnesota Multiphasic Inventory 2, EEGs, and clinical data to predict nonepileptic events

Carol J. Schramke, April Valeri, James P. Valeriano and Kevin M. Kelly
Epilepsy & behavior, v 11(3), pp 343-346
2007
DOI: https://doi.org/10.1016/j.yebeh.2007.06.011
PMID: 17904912
Featured in Collection :   UN Sustainable Development Goals @ Drexel

Abstract

Assessment Minnesota Multiphasic Inventory 2 Nonepileptic Personality Pseudoseizures Psychopathology Seizure like events Video/EEG monitoring, conversion disorder
Minnesota Multiphasic Inventory 2 (MMPI-2) scale 3, duration of illness, and routine EEGs have been used to predict nonepileptic events (NEEs) with a high degree of accuracy in patients referred for video/EEG (vEEG) monitoring. This study tested the Storzbach logistic regression equation in our patients with definitive epileptic seizures ( n = 57) or NEEs without evidence of epileptiform activity ( n = 51) during vEEG monitoring, yielding an overall classification accuracy of 81%, sensitivity of 80%, and specificity of 81%. This study also replicated previous findings of significant group differences in duration (years) of spells, number of elevations on the MMPI-2, MMPI-2 elevations on scales 1, 2, 3, and 8, and incidence of the conversion valley on the MMPI-2. Our findings indicated that combined use of the MMPI-2 and clinical variables was most predictive of patients with NEEs.

Metrics

15 Record Views
17 citations in Web of Science
18 citations in Scopus

Details

UN Sustainable Development Goals (SDGs)

This publication has contributed to the advancement of the following goals:

#3 Good Health and Well-Being

InCites Highlights

Data related to this publication, from InCites Benchmarking & Analytics tool:

Collaboration types
Domestic collaboration
Web of Science research areas
Behavioral Sciences
Clinical Neurology
Psychiatry
Logo image