Effects of epidural anesthesia with 0.2% and 1% ropivacaine on predicted propofol concentrations and bispectral index values at three clinical end points.
ABSTRACT To compare the effects of 0.2% epidural ropivacaine and those of 1% epidural ropivacaine on predicted propofol concentrations and bispectral index scores (BISs) at three clinical end points.
Randomized double-blind study.
Thirty-five (35) ASA physical status I and II patients scheduled for elective surgery of the lower abdomen.
Patients were randomly divided into 2 groups to receive epidurally 8 mL of 0.2% or 1% ropivacaine followed by the same solution at a rate of 6 mL/h.
Twenty minutes after starting ropivacaine, a target-controlled infusion of propofol was started to provide a predicted blood concentration of 3 microg/mL; it increased by 0.5 microg/mL every 60 seconds until all 3 clinical end points were reached, as follows: P1, when patients lost consciousness; P2, when patients failed to show pupillary dilation and skin vasomotor reflex to transcutaneous electric stimulation applied to the upper level of loss of cold sensation; and P3, when patients failed to show pupillary dilation and skin vasomotor reflex to transcutaneous electric stimulation applied to C5.
The effective concentration 50 values for both predicted blood and effect-site propofol concentrations were significantly larger in the 0.2% group than in the 1% group at all end points. The BIS at every end point was significantly smaller in the 0.2% group than in the 1% group.
During combined epidural-propofol anesthesia, unconsciousness and lack of response to noxious stimulation occurred at lower predicted concentrations with 1% epidural ropivacaine than with 0.2% epidural ropivacaine. The results also suggest that the BIS may not be a good indicator when propofol anesthesia is combined with epidural anesthesia.
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ABSTRACT: We investigated the problem of automatic depth of anesthesia (DOA) estimation from electroencephalogram (EEG) recordings. We employed Time Encoded Signal Processing And Recognition (TESPAR), a time-domain signal processing technique, in combination with multi-layer perceptrons to identify DOA levels. The presented system learns to discriminate between five DOA classes assessed by human experts whose judgements were based on EEG mid-latency auditory evoked potentials (MLAEPs) and clinical observations. We found that our system closely mimicked the behavior of the human expert, thus proving the utility of the method. Further analyses on the features extracted by our technique indicated that information related to DOA is mostly distributed across frequency bands and that the presence of high frequencies (> 80 Hz), which reflect mostly muscle activity, is beneficial for DOA detection.Computer methods and programs in biomedicine 04/2009; 95(3):191-202. · 1.14 Impact Factor
BMC Neuroscience. 01/2009;