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Identifying psychogenic seizures through comorbidities and medication history

Authors :
Mona Al Banna
Chelsea T. Braesch
Shannon R. D'Ambrosio
John M. Stern
Wesley T. Kerr
Sarah E. Barritt
Eric S. Hwang
David Torres-Barba
Emily C. Davis
Jerome Engel
Janar Bauirjan
Andrea M. Chau
Andrew Y. Cho
Norma L. Gallardo
Jessica M. Hori
Mark S. Cohen
Albert Buchard
Justine M. Le
Emily A. Janio
Akash B. Patel
Source :
Epilepsia, vol 58, iss 11
Publication Year :
2017
Publisher :
eScholarship, University of California, 2017.

Abstract

SummaryObjective Low-cost evidence-based tools are needed to facilitate the early identification of patients with possible psychogenic nonepileptic seizures (PNES). Prior to accurate diagnosis, patients with PNES do not receive interventions that address the cause of their seizures and therefore incur high medical costs and disability due to an uncontrolled seizure disorder. Both seizures and comorbidities may contribute to this high cost. Methods Based on data from 1,365 adult patients with video-electroencephalography–confirmed diagnoses from a single center, we used logistic and Poisson regression to compare the total number of comorbidities, number of medications, and presence of specific comorbidities in five mutually exclusive groups of diagnoses: epileptic seizures (ES) only, PNES only, mixed PNES and ES, physiologic nonepileptic seizurelike events, and inconclusive monitoring. To determine the diagnostic utility of comorbid diagnoses and medication history to differentiate PNES only from ES only, we used multivariate logistic regression, controlling for sex and age, trained using a retrospective database and validated using a prospective database. Results Our model differentiated PNES only from ES only with a prospective accuracy of 78% (95% confidence interval =72–84%) and area under the curve of 79%. With a few exceptions, the number of comorbidities and medications was more predictive than a specific comorbidity. Comorbidities associated with PNES were asthma, chronic pain, and migraines (p < 0.01). Comorbidities associated with ES were diabetes mellitus and nonmetastatic neoplasm (p < 0.01). The population-level analysis suggested that patients with mixed PNES and ES may be a population distinct from patients with either condition alone. Significance An accurate patient-reported medical history and medication history can be useful when screening for possible PNES. Our prospectively validated and objective score may assist in the interpretation of the medication and medical history in the context of the seizure description and history.

Details

Database :
OpenAIRE
Journal :
Epilepsia, vol 58, iss 11
Accession number :
edsair.doi.dedup.....54f8de012915ad800d6155fd2a8ee2d3