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Identifying psychogenic seizures through comorbidities and medication history.
Kerr, Wesley T; Janio, Emily A; Braesch, Chelsea T; Le, Justine M; Hori, Jessica M; Patel, Akash B; Gallardo, Norma L; Bauirjan, Janar; D'Ambrosio, Shannon R; Chau, Andrea M; Hwang, Eric S; Davis, Emily C; Buchard, Albert; Torres-Barba, David; Al Banna, Mona; Barritt, Sarah E; Cho, Andrew Y; Engel, Jerome; Cohen, Mark S; Stern, John M.
Afiliación
  • Kerr WT; Department of Internal Medicine, Eisenhower Medical Center, Rancho Mirage, California, U.S.A.
  • Janio EA; Department of Biomathematics, David Geffen School of Medicine at UCLA, Los Angeles, California, U.S.A.
  • Braesch CT; Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, California, U.S.A.
  • Le JM; Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, California, U.S.A.
  • Hori JM; Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, California, U.S.A.
  • Patel AB; Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, California, U.S.A.
  • Gallardo NL; Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, California, U.S.A.
  • Bauirjan J; Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, California, U.S.A.
  • D'Ambrosio SR; Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, California, U.S.A.
  • Chau AM; Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, California, U.S.A.
  • Hwang ES; Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, California, U.S.A.
  • Davis EC; Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, California, U.S.A.
  • Buchard A; Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, California, U.S.A.
  • Torres-Barba D; Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, California, U.S.A.
  • Al Banna M; Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, California, U.S.A.
  • Barritt SE; Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, California, U.S.A.
  • Cho AY; Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, California, U.S.A.
  • Engel J; Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, California, U.S.A.
  • Cohen MS; Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, California, U.S.A.
  • Stern JM; Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, California, U.S.A.
Epilepsia ; 58(11): 1852-1860, 2017 11.
Article en En | MEDLINE | ID: mdl-28895657
OBJECTIVE: 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.
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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Convulsiones / Trastornos Somatomorfos / Conciliación de Medicamentos Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Adult / Female / Humans / Male / Middle aged Idioma: En Revista: Epilepsia Año: 2017 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Convulsiones / Trastornos Somatomorfos / Conciliación de Medicamentos Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Adult / Female / Humans / Male / Middle aged Idioma: En Revista: Epilepsia Año: 2017 Tipo del documento: Article País de afiliación: Estados Unidos