Abstract
Objectives: Several sedation scores have been developed,
but still a need exists for an objective method to
monitor sedation level during intensive care. Our study
presents a procedure for finding a combination of
electroencephalogram (EEG) characteristics, which could
be used in estimating sedation level.
Methods: We measured EEG in 29 cardiac surgical patients
prior to and after the cardiac bypass grafting operation
at different sedation levels. The clinical assessment of
sedation levels was evaluated with the Ramsay Score.
Spectral EEG parameters were computed and a linear model
to predict postoperative se-dation level was constructed
by using principal component analysis and regression
analysis.
Results: Sedation levels modified all computed spectral
EEG parameters. The model based on optimal combination of
EEG parameters predicted the observed Ramsay Score value
with a prediction probabil-ity of 88%.
Conclusions: This study suggests that a combination of
spectral EEG parameters may discriminate be-tween 3
sedation levels: awake, moderate sedation and deep
sedation.
| Original language | English |
|---|---|
| Pages (from-to) | 1633-1639 |
| Journal | Clinical Neurophysiology |
| Volume | 113 |
| Issue number | 10 |
| DOIs | |
| Publication status | Published - 2002 |
| MoE publication type | A1 Journal article-refereed |
Keywords
- electroencephalogram
- sedation
- propofol
- principal component analysis
- regression analysis
- prediction probability