Abstracts

Rationale: Psychogenic nonepileptic seizures (PNES) are challenging to differentiate from epileptic seizures (ES) based on the information available at an outpatient clinical visit because, to patients and untrained observers, the seizures themselves are similar. Multiple objective methods exist to interpret the information available in the first outpatient clinical visit, but there remains a question of how to combine these into a comprehensive, evidence-based tool to identify patients that may benefit from early triage to more extensive diagnostic assessment. Early diagnosis of PNES may improve long-term seizure control, quality of life and healthcare utilization, thereby substantially reducing both indirect and direct costs. Methods: Based on data from 1,118 patients with video-electroencephalography confirmed diagnoses, we used information available at a single outpatient neurology visit to compare patients with ES and PNES. We used data-driven methods to determine the separate and combined diagnostic utility of objective scores based on each part of the clinical history in prospective standardized interviews including peri-ictal behavior, historical factors, and comorbidities. These objective scores were developed using retrospective chart review and validated using prospective standardized interviews. Results: Our logistic regression combination illustrated that comorbidities and historical factors both significantly predicted the likelihood of a patient’s seizure etiology (p<0.003) but semiology did not provide conditionally independent information (p=0.14). The accuracy of these prospective predictions was 77%, which was not significantly different than any of the individual scores based on comorbidities (78%), historical factors (71%) or peri-ictal behaviors (72%). This accuracy was limited by the finding that 22% of patients with PNES were not identified by any of the three scores, with the number of patients with PNES with a certain number of accuracy scores being significantly lower than expected by chance (p=0.04). Conversely, 87% of patients with ES were identified by at least two scores, which was significantly higher than chance (p=0.03). Conclusions: The reliable identification of patients with PNES based on clinical history alone is challenging, with as much as 22% of patients not reporting comorbidities, historical factors or peri-ictal behaviors that raised suspicion for PNES. The reliability of witness and patient descriptions of peri-ictal behavior likely limited the utility of this information. In contrast to the patient with PNES, it was rare for patients with ES to report multiple findings that raised a suspicion for PNES.  Funding: This work was supported by the UCLA-California Institute of Technology Medical Scientist Training Program (NIH T32 GM08042), the Neuroimaging Training Program (NIH T90 DA022768, R90 DA022768 & R90 DA023422 to MSC), the William M. Keck Foundation, research grants to JE (NS03310 & NS080181), the UCLA Departments of Psychiatry & Biobehavioral Sciences and Biomathematics, and the Eisenhower Medical Center Department of Internal Medicine.