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nization) of entrained brain sites in SE, a phenomenon we have called dynam-
ical resetting. We herein apply this nonlinear dynamical analysis to scalp EEG
recordings from two patients, one admitted to the EMU and the other to the ED
and ICU and both treated with AEDs, to show that successful administration of
AEDs dynamically disentrains the brain and correlates well with the patients' re-
covery. This result further supports our hypothesis of dynamical resetting of the
brain by AEDs into the recovery regime, and indicates that the proposed mea-
sures/methodology may assist in an objective evaluation of the efficacy of current
and the design of future AEDs for the treatment of SE.
17.1 Introduction
Status epilepticus (SE) is a life-threatening neurological emergency. SE is charac-
terized by recurrent epileptic seizures without recovery of normal brain function
between seizures. Out of the 200,000 cases of SE diagnosed each year in the United
States, the 30-day and 60-day mortality rate in the adult cases are well into the 40%
range [2]. It is estimated that SE accounts for more than $4B annual health-care
costs in USA alone. SE affects all age groups, with higher morbidity and mortality
in older aged adults.
The most perplexing aspect about clinical management of SE is that SE can be-
come refractory to initial, or sometimes any, treatment. In such cases, prompt treat-
ment is the key to preventing catastrophic outcomes. It has been shown that mortal-
ity in children and adults is minimized when SE lasts less than 1 h; however, there-
after, the odds of mortality jump dramatically to close to 38% [19]. Therefore, the
goal of SE treatment is to stop the seizure activity as quickly as possible. The clini-
cal standard for deciding a successful clinical response of SE to AED treatment is by
visual inspection of EEG to determine complete cessation of all seizure (ictal) activ-
ity. Typically, in SE patients who respond to AED medication, successful cessation
of ictal EEG activity occurs within 20 min following AED treatment. On the other
hand, in SE patients who do not respond to AED treatment, patterns of ictal EEG
activity continue or reappear within 60 min following AED treatment [18]. Unfortu-
nately, all too frequently, it is extremely difficult to differentiate such EEG patterns
from those associated with other abnormalities, such as metabolic encephalopathy.
Moreover, it is also difficult to distinguish the relapse of SE ictal activity due to
wearing away of a treatment from other abnormal non-SE EEG patterns. Therefore,
an independent measure of “ictalness,” that could help differentiate morphological
patterns on the EEG that appear ictal is needed. If a brain dynamical analysis corre-
lates well with the electroencephalographer's assessment of the presence or absence
of ictal patterns on the EEG, it could lead to the development of a clinically useful
tool that might independently from the visual analysis of the EEG determine the
presence or absence of SE.
In the last decade, substantial progress has been made toward the study of the hu-
man brain by utilizing concepts and measures from nonlinear dynamics [6]. Within
this framework, a significant amount of effort has been made toward understanding
