Feasibility of online seizure detection with continuous EEG monitoring in the intensive care unit.
BACKGROUND
Continuous EEG (cEEG) is of great interest in view of the reported high prevalence of non-convulsive seizures on intensive care units (ICUs). Here, we describe our experiences applying a seizure warning system using cEEG monitoring.


METHODS
Fifty comatose ICU patients were included prospectively and monitored. Twenty-eight patients had post-anoxic encephalopathy (PAE) and 22 had focal brain lesions. A measure of neuronal interactions, synchronization likelihood, was calculated online over 10s EEG epochs and instances when the synchronization likelihood exceeded a threshold where marked as seizures.


RESULTS
Five patients developed seizures. Our method detected seizures in three patients, in the other patients seizures were missed because of they were non-convulsive and had a focal character. The average false positive rate was 0.676/h.


CONCLUSIONS
This is our first attempt to implement online seizure detection in the ICU. Despite problems with artifacts and that we missed focally oriented seizures, we succeeded in monitoring patients online. Given the relatively high occurrence of seizures, online seizure detection with cEEG merits further development for use in ICUs.
Ponten
S C
SC
Department of Clinical Neurophysiology, VU University Medical Center, PO Box 7057, 1007 MB, Amsterdam, The Netherlands. sc.ponten@vumc.nl
Ronner
H E
HE
Strijers
R L M
RL
Visser
M C
MC
Peerdeman
S M
SM
Vandertop
W P
WP
Beishuizen
A
A
Girbes
A R J
AR
Stam
C J
CJ
D000368:Aged; D001921:Brain / Q000503:physiopathology; D003128:Coma / Q000503:physiopathology; D004569:Electroencephalography / Q000379:methods*; D005260:Female; D006801:Humans; D007362:Intensive Care Units; D008297:Male; D008875:Middle Aged; D008991:Monitoring, Physiologic / Q000379:methods; D011446:Prospective Studies; D012640:Seizures / Q000175:diagnosis* / Q000503:physiopathology