Time-dependent risk of seizures in critically ill patients on continuous electroencephalogram

Objective Find the optimal continuous electroencephalographic (CEEG) monitoring duration for seizure detection in critically ill patients. Methods We analyzed prospective data from 665 consecutive CEEGs, including clinical factors and time-to-event emergence of electroencephalographic (EEG) findings over 72 hours. Clinical factors were selected using logistic regression. EEG risk factors were selected a priori. Clinical factors were used for baseline (pre-EEG) risk. EEG findings were used for the creation of a multistate survival model with 3 states (entry, EEG risk, and seizure). EEG risk state is defined by emergence of epileptiform patterns. Results The clinical variables of greatest predictive value were coma (31% had seizures; odds ratio [OR] = 1.8, p