Wesley T Kerr1, Emily A Janio2, Andrea M Chau2, Chelsea T Braesch2, Justine M Le2, Jessica M Hori2, Akash B Patel2, Norma L Gallardo2, Corinne H Allas2, Amir H Karimi2, Ishita Dubey2, Siddhika S Sreenivasan2, Janar Bauirjan2, Eric S Hwang2, Emily C Davis2, Shannon R D'Ambrosio2, Mona Al Banna3, Rajarshi Mazumder4, Ting Wu4, Zachary A DeCant4, Michael G Gibbs4, Edward Chang4, Xingruo Zhang2, Andrew Y Cho2, Nicholas J Beimer5, Jerome Engel6, Mark S Cohen7, John M Stern4. 1. Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA; Department of Internal Medicine, Eisenhower Medical Center, Rancho Mirage, CA, USA; Department of Biomathematics, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA; Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA. Electronic address: WesleyTK@g.UCLA.edu. 2. Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA. 3. Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA; Department of Neurology, University of Minnesota, Minneapolis, MN, USA. 4. Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA. 5. Department of Neurology, University of Michigan, Ann Arbor, MI, USA. 6. Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA; Department of Neurobiology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA; Brain Research Institute, University of California Los Angeles, Los Angeles, California, USA. 7. Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA; Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA; Brain Research Institute, University of California Los Angeles, Los Angeles, California, USA; Departments of Radiology, Psychology, Biomedical Physics, and Bioengineering, University of California, Los Angeles, Los Angeles, CA, USA; California NanoSystems Institute, University of California, Los Angeles, Los Angeles, CA, USA.
Abstract
OBJECTIVE: To develop a Dissociative Seizures Likelihood Score (DSLS), which is a comprehensive, evidence-based tool using information available during the first outpatient visit to identify patients with "probable" dissociative seizures (DS) to allow early triage to more extensive diagnostic assessment. METHODS: Based on data from 1616 patients with video-electroencephalography (vEEG) confirmed diagnoses, we compared the clinical history from a single neurology interview of patients in five mutually exclusive groups: epileptic seizures (ES), DS, physiologic nonepileptic seizure-like events (PSLE), mixed DS plus ES, and inconclusive monitoring. We used data-driven methods to determine the diagnostic utility of 76 features from retrospective chart review and applied this model to prospective interviews. RESULTS: The DSLS using recursive feature elimination (RFE) correctly identified 77% (95% confidence interval (CI), 74-80%) of prospective patients with either ES or DS, with a sensitivity of 74% and specificity of 84%. This accuracy was not significantly inferior than neurologists' impression (84%, 95% CI: 80-88%) and the kappa between neurologists' and the DSLS was 21% (95% CI: 1-41%). Only 3% of patients with DS were missed by both the fellows and our score (95% CI 0-11%). SIGNIFICANCE: The evidence-based DSLS establishes one method to reliably identify some patients with probable DS using clinical history. The DSLS supports and does not replace clinical decision making. While not all patients with DS can be identified by clinical history alone, these methods combined with clinical judgement could be used to identify patients who warrant further diagnostic assessment at a comprehensive epilepsy center.
OBJECTIVE: To develop a Dissociative Seizures Likelihood Score (DSLS), which is a comprehensive, evidence-based tool using information available during the first outpatient visit to identify patients with "probable" dissociative seizures (DS) to allow early triage to more extensive diagnostic assessment. METHODS: Based on data from 1616 patients with video-electroencephalography (vEEG) confirmed diagnoses, we compared the clinical history from a single neurology interview of patients in five mutually exclusive groups: epileptic seizures (ES), DS, physiologic nonepileptic seizure-like events (PSLE), mixed DS plus ES, and inconclusive monitoring. We used data-driven methods to determine the diagnostic utility of 76 features from retrospective chart review and applied this model to prospective interviews. RESULTS: The DSLS using recursive feature elimination (RFE) correctly identified 77% (95% confidence interval (CI), 74-80%) of prospective patients with either ES or DS, with a sensitivity of 74% and specificity of 84%. This accuracy was not significantly inferior than neurologists' impression (84%, 95% CI: 80-88%) and the kappa between neurologists' and the DSLS was 21% (95% CI: 1-41%). Only 3% of patients with DS were missed by both the fellows and our score (95% CI 0-11%). SIGNIFICANCE: The evidence-based DSLS establishes one method to reliably identify some patients with probable DS using clinical history. The DSLS supports and does not replace clinical decision making. While not all patients with DS can be identified by clinical history alone, these methods combined with clinical judgement could be used to identify patients who warrant further diagnostic assessment at a comprehensive epilepsy center.
Authors: Wesley T Kerr; Eric S Hwang; Kaavya R Raman; Sarah E Barritt; Akash B Patel; Justine M Le; Jessica M Hori; Emily C Davis; Chelsea T Braesch; Emily A Janio; Edward P Lau; Andrew Y Cho; Ariana Anderson; Daniel H S Silverman; Noriko Salamon; Jerome Engel; John M Stern; Mark S Cohen Journal: Int Workshop Pattern Recognit Neuroimaging Date: 2014-06
Authors: Alistair Wardrope; Jenny Jamnadas-Khoda; Mark Broadhurst; Richard A Grünewald; Timothy J Heaton; Stephen J Howell; Matthias Koepp; Steve W Parry; Sanjay Sisodiya; Matthew C Walker; Markus Reuber Journal: Neurol Clin Pract Date: 2020-04
Authors: Wesley T Kerr; Xingruo Zhang; Chloe E Hill; Emily A Janio; Andrea M Chau; Chelsea T Braesch; Justine M Le; Jessica M Hori; Akash B Patel; Corinne H Allas; Amir H Karimi; Ishita Dubey; Siddhika S Sreenivasan; Norma L Gallardo; Janar Bauirjan; Eric S Hwang; Emily C Davis; Shannon R D'Ambrosio; Mona Al Banna; Andrew Y Cho; Sandra R Dewar; Jerome Engel; Jamie D Feusner; John M Stern Journal: Seizure Date: 2021-02-15 Impact factor: 3.184
Authors: Wesley T Kerr; Xingruo Zhang; Chloe E Hill; Emily A Janio; Andrea M Chau; Chelsea T Braesch; Justine M Le; Jessica M Hori; Akash B Patel; Corinne H Allas; Amir H Karimi; Ishita Dubey; Siddhika S Sreenivasan; Norma L Gallardo; Janar Bauirjan; Eric S Hwang; Emily C Davis; Shannon R D'Ambrosio; Mona Al Banna; Andrew Y Cho; Sandra R Dewar; Jerome Engel; Jamie D Feusner; John M Stern Journal: Seizure Date: 2021-02-09 Impact factor: 3.184
Authors: Steven Lenio; Wesley T Kerr; Meagan Watson; Sarah Baker; Chad Bush; Alex Rajic; Laura Strom Journal: Epilepsy Behav Date: 2021-02-02 Impact factor: 2.937
Authors: Wesley T Kerr; Xingruo Zhang; Emily A Janio; Amir H Karimi; Corinne H Allas; Ishita Dubey; Siddhika S Sreenivasan; Janar Bauirjan; Shannon R D'Ambrosio; Mona Al Banna; Andrew Y Cho; Jerome Engel; Mark S Cohen; Jamie D Feusner; John M Stern Journal: Epilepsy Behav Date: 2021-01-01 Impact factor: 2.937