An objective score to identify psychogenic seizures based on age of onset and history.

TitleAn objective score to identify psychogenic seizures based on age of onset and history.
Publication TypeJournal Article
Year of Publication2018
AuthorsKerr WT, Janio EA, Braesch CT, Le JM, Hori JM, Patel AB, Gallardo NL, Bauirjan J, Chau AM, Hwang ES, Davis EC, Buchard A, Torres-Barba D, D'Ambrosio S, Banna MAl, Cho AY, Engel J, Cohen MS, Stern JM
JournalEpilepsy Behav
Volume80
Pagination75-83
Date Published2018 Mar
ISSN1525-5069
Abstract

OBJECTIVE: Psychogenic nonepileptic seizure (PNES) is a common diagnosis after evaluation of medication resistant or atypical seizures with video-electroencephalographic monitoring (VEM), but usually follows a long delay after the development of seizures, during which patients are treated for epilepsy. Therefore, more readily available diagnostic tools are needed for earlier identification of patients at risk for PNES. A tool based on patient-reported psychosocial history would be especially beneficial because it could be implemented in the outpatient clinic.

METHODS: Based on the data from 1375 patients with VEM-confirmed diagnoses, we used logistic regression to compare the frequency of specific patient-reported historical events, demographic information, age of onset, and delay from first seizure until VEM in five mutually exclusive groups of patients: epileptic seizures (ES), PNES, physiologic nonepileptic seizure-like events (PSLE), mixed PNES plus ES, and inconclusive monitoring. To determine the diagnostic utility of this information to differentiate PNES only from ES only, we used multivariate piecewise-linear logistic regression trained using retrospective data from chart review and validated based on data from 246 prospective standardized interviews.

RESULTS: The prospective area under the curve of our weighted multivariate piecewise-linear by-sex score was 73%, with the threshold that maximized overall retrospective accuracy resulting in a prospective sensitivity of 74% (95% CI: 70-79%) and prospective specificity of 71% (95% CI: 64-82%). The linear model and piecewise linear without an interaction term for sex had very similar performance statistics. In the multivariate piecewise-linear sex-split predictive model, the significant factors positively associated with ES were history of febrile seizures, current employment or active student status, history of traumatic brain injury (TBI), and longer delay from first seizure until VEM. The significant factors associated with PNES were female sex, older age of onset, mild TBI, and significant stressful events with sexual abuse, in particular, increasing the likelihood of PNES. Delays longer than 20years, age of onset after 31years for men, and age of onset after 40years for women had no additional effect on the likelihood of PNES.

DISCUSSION: Our promising results suggest that an objective score has the potential to serve as an early outpatient screening tool to identify patients with greater likelihood of PNES when considered in combination with other factors. In addition, our analysis suggests that sexual abuse, more than other psychological stressors including physical abuse, is more associated with PNES. There was a trend of increasing frequency of PNES for women during childbearing years and plateauing outside those years that was not observed in men.

DOI10.1016/j.yebeh.2017.11.035
Alternate JournalEpilepsy Behav
PubMed ID29414562
PubMed Central IDPMC5845850
Grant ListT32 GM008042 / GM / NIGMS NIH HHS / United States
P20 NS080181 / NS / NINDS NIH HHS / United States
R90 DA023422 / DA / NIDA NIH HHS / United States
P01 NS002808 / NS / NINDS NIH HHS / United States
R21 DA026109 / DA / NIDA NIH HHS / United States
T90 DA022768 / DA / NIDA NIH HHS / United States
R01 NS033310 / NS / NINDS NIH HHS / United States

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