Evidence map›Paper›PMID 29414562›Full record

ArticleEpilepsy & behavior : E&B2018

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

Wesley T Kerr, Emily A Janio, Chelsea T Braesch, Justine M Le, Jessica M Hori, Akash B Patel, Norma L Gallardo, Janar Bauirjan, Andrea M Chau, Eric S Hwang and 9 more

Open access · greenAbstract read
In one paragraph

Article in Epilepsy & behavior : E&B, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
4.1field-weighted citation impact, top 5% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed, 41 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

19 authors at 2 institutions in 1 country.

Wesley T KerrDepartment of Biomathematics, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States; Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, United States; Department of Internal Medicine, Eisenhower Medical Center, Rancho Mirage, CA, United States. Electronic address: WesleyTK@UCLA.edu.
Emily A JanioDepartment of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, United States.
Chelsea T BraeschDepartment of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, United States.
Justine M LeDepartment of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, United States.
Jessica M HoriDepartment of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, United States.
Akash B PatelDepartment of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, United States.
Norma L GallardoDepartment of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, United States.
Janar BauirjanDepartment of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, United States.
Andrea M ChauDepartment of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, United States.
Eric S HwangDepartment of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, United States.
Emily C DavisDepartment of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, United States.
Albert BuchardDepartment of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, United States.
David Torres-BarbaDepartment of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, United States.
Shannon D'AmbrosioDepartment of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, United States.
Mona Al BannaDepartment of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, United States.
Andrew Y ChoDepartment of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, United States.
Jerome EngelDepartment of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, United States; Departments of Neurology and Neurobiology, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States; Brain Research Institute, University of California Los Angeles, Los Angeles, CA, United States.
Mark S CohenDepartment of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, United States; Departments of Neurology and Neurobiology, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States; Departments of Radiology, Psychology, Biomedical Physics, and Bioengineering, University of California Los Angeles, Los Angeles, CA, United States; California NanoSystems Institute, University of California Los Angeles, Los Angeles, CA, United States.
John M SternDepartments of Neurology and Neurobiology, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States.
University of California, Los Angeles · USNeurobehavioral Systems · US

Funding

UCLA-Caltech Medical Scientist Training ProgramT32GM008042 · NIGMS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI AJIJOLA, OLUJIMI A, DAWSON, DAVID WAYNE · 1985 to 2023
$29.9M
SYSTEMS PATHOPHYSIOLOGYP01NS002808 · NINDS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI BRAGIN, ANATOL · 1985 to 2010
$13.5M
IN VIVO STUDIES OF THE EPILEPTIC HIPPOCAMPUSR01NS033310 · NINDS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI JEROME NONE ENGEL, Richard Staba · 1994 to 2026
$7.5M
Comprehensive Training in Neuroimaging Fundamentals and ApplicationsR90DA023422 · NIDA · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI COHEN, MARK STEVEN · 2006 to 2015
$1.7M
The Epilepsy Bioinformatics Study (EpiBioS)P20NS080181 · NINDS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI ENGEL, JEROME NONE, HOVDA, DAVID A · 2012 to 2014
$1.7M
Comprehensive Training in Neuroimaging Fundamentals and ApplicationsT90DA022768 · NIDA · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI COHEN, MARK STEVEN · 2006 to 2015
$1.5M
Real-Time Automated Detection of Craving States with fMRI and EEGR21DA026109 · NIDA · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI COHEN, MARK STEVEN · 2008 to 2009
$591k
NIDA NIH HHS R21 DA026109NIDA NIH HHS R90 DA023422NIDA NIH HHS T90 DA022768NIGMS NIH HHS T32 GM008042NINDS NIH HHS P01 NS002808NINDS NIH HHS P20 NS080181NINDS NIH HHS R01 NS033310
6 · The paper itself

Abstract

objectivePsychogenic 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.

methodsBased 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.

resultsThe 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.

Indexed as

AdultAge of OnsetDissociative DisordersElectroencephalographyEpilepsyFemaleHumansMaleMiddle AgedMonitoring, PhysiologicProspective StudiesRetrospective StudiesSeizuresSeizures, FebrileSomatoform DisordersVideo RecordingDiagnostic scoreDissociative seizuresLogistic regressionMultiple imputation

Identifiers

PMID29414562
PMCPMC5845850
OpenAlexW2792063171

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.