Abstracts

Rationale: An EEG is important to diagnose non-convulsive status epilepticus and to distinguish convulsive SE from psychogenic SE. Delays in the diagnosis and treatment of SE or inappropriate treatment for convulsive SE in the setting of psychogenic SE may result in increased morbidity and mortality. Currently, an EEG is often difficult to obtain due to lack of technologist availability, particularly at night, and the typical setup is time consuming. Thus, a system which can be rapidly applied by a non-EEG technologist is highly desirable. The StatNet device is a lightweight, reduced set of electrodes with a self-adhesive backing that can be quickly applied by untrained personnel and may potentially hasten the diagnosis of SE. The purpose of this study is to assess the performance of the StatNet device for EEG recordings. Methods: Twenty patients who demonstrated frequent focal or generalized EEG abnormalities, such as slowing or epileptiform activity, while undergoing a conventional EEG were enrolled in the study. At the end of their conventional EEG, subjects then had an additional 10-minute EEG recording using the StatNet electrode set. Both EEG recordings were then reviewed by four board-certified neurophysiologists in a blinded fashion, and assessed using the following parameters: quality of recordings, duration of artifacts (electrode, electrical, movement, and muscle artifacts), and ability to detect abnormal findings, such as epileptiform discharges, electrographic seizures, and focal or generalized slowing. The set up time for both types of electrodes was compared. Results: No difference was noted in the quality of the recordings or the duration of artifacts between the StatNet and the conventional EEG group. The mean setup time was 7.18 minutes for the StatNet group and 22.44 minutes for the conventional group and the difference was statistically significant (p<0.0001). None of the studies with clear epileptiform activity (focal or generalized spike-and-wave or polyspike-and-wave activity) were misinterpreted using the StatNet electrodes. Both inter-rater and intra-rater variabilities were noted with respect to the location and presence of focal or generalized slowing. A penalty factor was assigned to studies for which the StatNet reading differed from that of the conventional recording. After this adjustment, a two-sample t-test yielded statistically significant time advantage using the StatNet device (p=0.017). Conclusions: The StatNet electrode set represents a faster and easier method of obtaining high quality EEG recordings that are comparable to those using conventional electrodes. The device also has the potential for widespread use since application by trained personnel is not essential. Thus, it may be a more desirable alternative to conventional EEG electrodes and may be more suitable for use in emergency settings, such as the emergency room, the intensive care unit, or even in pre-hospital settings, where rapid diagnosis of SE is critical. Further research is needed to evaluate of the performance of the StatNet electrodes and the clinical impact of their use in these emergent situations.