Klinische Neurophysiologie 2014; 45 - P58
DOI: 10.1055/s-0034-1371271

New approach in quantitative EEG monitoring of critical care patients: Neurological trending based on the ACNS terminology

F Fürbass 1, C Baumgartner 2, J Koren 2, M Hartmann 1, M Weinkopf 1, J Halford 3, K Schnabel 3, J Herta 4, A Gruber 4, T Kluge 1
  • 1AIT Austrian Institute of Technology, Safety & Security, Wien, Österreich
  • 2General Hospital Hietzing with Neurological Center Rosenhuegel, 2nd Neurological Department, Wien, Oesterreich
  • 3Medical University of South Carolina, Comprehensive Epilepsy Center, Charleston, SC, USA
  • 4Medical University of Vienna, Department of Neurosurgery, Wien, Österreich

Question:

EEG long-term monitoring of critically ill patients has received increasing attention but the problem of time efficient evaluation and interpretation of the EEG remains. A computational method called NeuroTrend is presented that analyses the EEG in real-time according to the ACNS terminology for critically ill patients.

Methods:

NeuroTrend scans the EEG for periodic discharges, rhythmic delta activity, and spike-and-wave patterns and display them graphically for several hours or even days. In addition to standardized patterns unequivocal rhythmic activity above 4 Hertz is shown to support recognition of nonconvulsive seizures and status epileptici. Amplitude and frequency of the patterns are presented to gain insight in dynamic changes of the EEG and to allow prediction of future trends. To assess sensitivity the results of NeuroTrend were compared to the results of a manual EEG analysis from 143 routine EEGs and 21 long-term recordings of critically ill patients. The comparison was done in a 10 minute granularity using standardized ACNS patterns only.

Results:

The agreement between NeuroTrend and manual review was 90% for periodic patterns, 82% for rhythmic delta activity and 61% for spike-and-wave patterns. In addition all seizures and stati of the long term EEGs were clearly visible through rhythmic or spike-wave patterns.

Conclusion:

The results of the computational EEG surveillance method NeuroTrend show high sensitivity for standardized ACNS patterns and unequivocal ictal activity. The fully automatic evaluation allows visual detection of short-term patterns and deduction of the neurological long-term trends at the same time. Further evaluation including several EEG experts will be the next step.