The semiology of psychogenic nonepileptic seizures revisited: Can video alone predict the diagnosis? Preliminary data from a prospective feasibility study.

ABSTRACT

OBJECTIVE: To investigate if, when, and to what extent visual information contained in a video-recorded event allows experienced epileptologists to predict the diagnosis of psychogenic nonepileptic seizures (PNES) without the aid of electroencephalography (EEG). METHODS: Five neurologists actively practicing in epilepsy centers in Italy and the United States were asked to review 23 videos capturing representative events of 21 unselected consecutive patients admitted for long-term video-EEG monitoring (VEM). Four raters were blind to EEG and clinical information; one rater was not. They were requested to (1) rate the videos for quality and content; (2) choose among four diagnoses (a) epileptic seizures (ES); (b) PNES; (c) Other nonepileptic seizures (NES; (syncope, movement disorder, migraine, etc.); (d) "Cannot Say"; and (3) explain in their own words the main reasons leading to the diagnosis of choice. RESULTS: All raters predicted the diagnosis correctly in 7 of 23 videos (all ES or PNES) (30.4%), whereas all raters failed in 5 of 23 cases (three Other NES, one PNES, one Cannot Say) (21.7%). The conditions that facilitate, and those that interfere with, a confident diagnosis were predictable. Degree of accuracy among raters was not uniform and was consistently better in three raters. Two among the four blind raters were as accurate as the rater who was not blinded. Interrater agreement was "moderate" (k = 0.52) for the overall group; "moderate" for ES (k = 0.53); "substantial" for PNES (k = 0.63); "fair" for Other NES (k = 0.21)-similar to the results obtained in a previous study evaluating the reliability of combined video-EEG. SIGNIFICANCE: In about one third of cases, a confident diagnosis of PNES/ES can be established on clinical grounds based on video data alone. Our results benefit all affected patients, particularly those with no access to video-EEG monitoring units.