Rapid Electroencephalography and Artificial Intelligence in the Detection and Management of Nonconvulsive Seizures

Abstract

Nonconvulsive status epilepticus is a commonly overlooked cause of altered mental status. This study assessed nonconvulsive status epilepticus prevalence in emergency department (ED) patients with acute neurologic presentations using limited electroencephalogram (EEG) coupled with artificial intelligence (AI)-enhanced seizure detection technology. We then compared the accuracy of the AI EEG interpretations to those performed by an epileptologist. In a prospective observational cohort analysis, adult patients with unexplained mental status changes identified by emergency physicians received expedited placement of a limited EEG. Data collected encompassed patient demographics, clinical history, EEG interpretations by the AI algorithm and epileptologists, treatments, and disposition determinations. There were 134 device applications on 132 patients (2 received the device twice) enrolled in the study, but 16 were missing data critical for identification or analysis and 9 did not meet the selection criteria. Of the 108 limited EEGs interpreted by an epileptologist, 69 were abnormal (diffuse slowing, highly epileptiform patterns, or spikes and sharps), 41 were normal, 5 were uninterpretable, and 3 captured episodes of seizure or status epilepticus. Limited EEG AI interpretation detected >90% seizure burden in 2 of 3 cases of seizure or status epilepticus as well as in 2 abnormal EEGs and 1 normal EEG, providing a sensitivity of 66.7% (95% confidence interval 9.4 to 99.2), a specificity of 97.0% (95% confidence interval 91.5 to 99.4), and a disease prevalence of 2.9%. Limited AI-enhanced EEG can detect nonconvulsive status epilepticus in the ED; however, the technology tended to overestimate seizure burden in our cohort. This study found a lower nonconvulsive status epilepticus prevalence compared to prior literature reports.