Journal article
Using the Minnesota Multiphasic Inventory 2, EEGs, and clinical data to predict nonepileptic events
Epilepsy & behavior, v 11(3), pp 343-346
2007
PMID: 17904912
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
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
Details
- Title
- Using the Minnesota Multiphasic Inventory 2, EEGs, and clinical data to predict nonepileptic events
- Creators
- Carol J. Schramke - Allegheny General HospitalApril Valeri - Allegheny General HospitalJames P. Valeriano - Drexel UniversityKevin M. Kelly - Drexel University
- Publication Details
- Epilepsy & behavior, v 11(3), pp 343-346
- Publisher
- Elsevier
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Neurology
- Web of Science ID
- WOS:000251067800015
- Scopus ID
- 2-s2.0-35748948043
- Other Identifier
- 991019168571804721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Behavioral Sciences
- Clinical Neurology
- Psychiatry