Cerebral State Index during Propofol Anesthesia: A Comparison with the Bispectral Index and the A-Line ARX Index

The raw data from two previously published studies were used. Both patient databases were exclusively obtained at Ghent University Hospital (Gent, Belgium). For all patients in both protocols, informed consent was obtained after approval from the institutional ethics committee.

Protocol 1 studied deep anesthetic levels reaching high levels of burst suppression during propofol administration.11Protocol 2 studied the correlation between different clinical levels of responsiveness as measured by the OAA/S scale18,versus  the electroencephalogram during steady state propofol administration.7Because the raw electroencephalographic data, vital signs, and pharmacologic data were recorded online and stored electronically in a time-synchronized way, it was possible to reanalyze the raw electroencephalographic data without the requirement of including new patients.

In both protocols, exclusion criteria were weight less than 70% or more than 130% of ideal body weight, neurologic disorder, and recent use of psychoactive medication, including alcohol.

The population for this study protocol was formed by 13 patients (10 women, 3 men; American Society of Anesthesiologists physical status I; aged 18–65 yr) scheduled to undergo ambulatory gynecologic or urologic surgery. Before drug administration was started, all patients were asked to close their eyes and relax for 2 min. After this time, baseline measurements were taken. All patients then received a continuous infusion of propofol at 300 ml/h. Infusion was continued until a burst suppression level of 80% or higher was achieved. However, propofol infusion was stopped earlier if the mean arterial blood pressure became lower than 50 mmHg.

The study population was formed by 20 female patients (American Society of Anesthesiologists physical status I; aged 18–60 yr) scheduled to undergo ambulatory gynecologic surgery. All patients received an effect site compartment target-controlled infusion of propofol. The initial propofol effect site concentration (Ce prop) was set at 1.5 μg/ml and increased every 4 min by 0.5 μg/ml until an OAA/S level of 0 was reached. The level of consciousness, assessed through the OAA/S score, was recorded along with the electronic indices before each increase in effect target concentration. Table 1describes the OAA/S score levels and their clinical interpretation.

In both protocols, a similar clinical setting was used. Propofol was administered as the only drug, through a large left forearm vein, and infusion was conducted via  the computer-assisted continuous-infusion device RUGLOOP II (Demed Engineering, Temse, Belgium). This device drove a Fresenius Modular DPS Infusion Pump connected to a Fresenius Base A (Fresenius Vial Infusion Systems, Brézins, France) through an RS-232 interface. To determine Ce prop, the software uses a three-compartment model enlarged with an effect site compartment, previously published by Schnider et al.  19,20The calculated Ce prop was computed to yield a time to peak effect of 1.6 min after bolus injection,21as also published by Schnider et al.  19,20and clinically confirmed by Struys et al.  22Heart rate and noninvasive blood pressure, pulse oximetry, and capnography were recorded at 1-min time intervals using an S5® monitor (Datex-Ohmeda, Helsinki, Finland). All patients maintained spontaneous ventilation via  a facemask delivering 100% oxygen.

In both protocols, the BIS and the raw electroencephalographic signal with the AEP signal embedded were simultaneously acquired for all patients. The BIS XP® (version 4.0) was derived from the frontal electroencephalogram (At-Fpzt) and calculated by the A-2000 BIS® Monitor using four BIS®-Sensor electrodes (Aspect Medical Systems, Inc.). The smoothening time of the BIS® monitor was set at 15 s. The raw electroencephalographic signal corresponding to each patient was recorded using the A-Line Monitor (Scientific Version; Danmeter A/S) with three electrodes positioned at midforehead (+), left forehead (reference), and left mastoid (−) along with headphones to deliver a train of bilateral clicks at a frequency of 9 Hz with a 2-ms duration and an adaptable intensity set automatically by the monitor.

The electroencephalographic signal was sampled at 900 Hz and band-pass filtered in the 0.5- to 45-Hz band. The AAI1.6 was calculated off-line based on the raw MLAEP data. For all calculations, the AAI has been scaled to a 0–60 interval (AAI⁶⁰). This scale provides the best stability in the awake state, as proven by Vereecke et al.  11The CSI was calculated off-line from the raw electroencephalographic records. Mathematical details from this technology are given in the  appendix. It has already been shown that the embedded AEPs resulting from the click stimuli have no effect on the BIS,23which includes the β ratio in its calculation. Although an influence of the AEP in the raw signal cannot be excluded, in general, the signal-to-noise ratio between the AEP and the electroencephalographic signal is less than 1 to 30; therefore, the influence of the clicks is assumed to be less than approximately 3% of the final value.

The burst suppression values were taken from the specific parameters calculated by each monitor: the suppression ratio (SR) provided by the BIS and BS% for the AAI⁶⁰and CSI calculations.

In protocol 1, a linear regression and its corresponding correlation coefficient was calculated between CSI and BIS. A nonparametric approach, the Spearman rank correlation, R , was calculated to study the relation between Ce prop and CSI, BIS, or AAI. The Spearman rank correlation was calculated on pooled data.

The relation between Ce prop and the electroencephalographic measures of anesthetic drug effect was analyzed using a sigmoid E^maxmodel,

where Effect is the electroencephalographic effect being measured (CSI), E⁰is the baseline measurement when no drug is present, E^maxis the maximum possible drug effect, Ce is the calculated effect site concentration of propofol, Ce⁵⁰is the effect site concentration associated with 50% maximal drug effect, and γ is the steepness of the concentration–response relation curve. The model parameters were estimated using NONMEM V (Globomax LLC, Hanover, MD). The parameters for the BIS and AAI⁶⁰have already been estimated for this population by Vereecke et al.  11The relation between Ce prop and CSI was calculated using the same NONMEM V specifications as described by Vereecke et al.  11 

In protocol 2, the ability of the CSI, BIS, and AAI to predict the response to verbal command, as defined by the OAA/S scale, was evaluated using prediction probability (P^K). Prediction probability was calculated using a custom spreadsheet macro, P^KMACRO, developed by Smith et al.  24,25The P^Kvalue was calculated as the mean from pooled data of all patients. A P^Kof 1 for the CSI indicator would mean that CSI always decreases (increases) as the patient reaches deeper levels of anesthesia according to the OAA/S scale. Such an indicator can perfectly predict the anesthetic state. Alternatively, a P^Kvalue of 0.5 would mean that the indicator is useless for predicting the depth of anesthesia. The jackknife method was used to compute the SE of the estimate.24,25After having evaluated normal distribution, a Student t  test with Bonferroni correction was used to evaluate significant difference between the P^Kmeans. A Friedman analysis was conducted, and if P < 0.05, a Wilcoxon signed rank sum test was used to test for significance between the electronic indices at adjacent OAA/S levels (5 vs.  4, 4 vs.  3 . . .).

All data from the published study11were included in the analysis.

Figure 1shows a pooled scatter plot of the raw data for all patients. A relation between Ce prop and the electronic indices, CSI, BIS, and AAI⁶⁰, is hereby shown in plots A, B, and C, respectively. The behavior of the two spontaneous electroencephalographic indices, CSI and BIS, were comparable, as shown in figure 2. The equation for the regression line was CSI = 1.02 BIS (P < 0.05 for linearity). Table 2shows the results of the Spearman rank correlation between propofol and the three indices. The CSI showed a significantly higher correlation than the other two indices.

The high concentrations of propofol caused considerable amount of burst suppression, as shown in figure 3. Figure 3Ashows CSI versus  its BS%, where the relation is almost linear when BS% is larger than 60. The equation for the regression line, assuming BS% > 1, is shown to have a significant (P < 0.05) linear fit to the data. Less linearity is seen for the BIS and AAI⁶⁰in figures 3A and B, respectively.

The NONMEM analysis (fig. 4) showed that for this population, the typical values (coefficient of variation) for the sigmoid E^maxmodel between Ce prop and CSI were C⁵⁰= 9.85 (65%), E⁰= 94 (4.6%), E^max=−100 (110%), and γ= 3.45 (31%). The SD, depicting the residual intraindividual variability, was 6.79.

All raw data from the published study were included.7 Figure 5shows the CSI, BIS, and AAI⁶⁰versus  OAA/S. To compare the different adjacent OAA/S levels for all three indices, a Mann–Whitney U test was applied. The results are shown in table 3. The table shows that in general the BIS and AAI were able to distinguish between OAA/S levels 5 to 2. For the CSI, a smoother drop was observed between level 3 and 2, whereas at deeper anesthesia, the CSI was the only parameter that showed significant differences between OAA/S levels 0 and 1.

Table 4lists the P^Kvalues of the OAA/S for CSI, BIS, and AAI⁶⁰. All P^Kvalues were above 0.9, and there were no significant differences between the P^Kvalues of the three electronic indices.

The core of the CSI signal processing algorithm is fuzzy logic based. The power of fuzzy logic lies in its ability to perform reasonable and meaningful operations on concepts that cannot be easily codified using a classic logic approach. Such modifications allow for a much more flexible and widespread use of reliable and consistent logic in a variety of applications.

Classic logic relies on something being either true or false. Therefore, either something completely belongs to a set or it is completely excluded from it. Fuzzy logic broadens this definition of membership. The basis of the logic is fuzzy sets. Unlike in “crisp” sets, where membership is full or none, an object is allowed to belong only partly to one set. The membership of an object to a particular set is described by a real value from a range between 0 and 1. Such logic allows a much easier application of many problems that cannot be easily implemented using the classic approach, which only allows a single object to be a member of two mutually exclusive—in the “crisp” sense—sets.

The most common use of fuzzy logic lies in the field of control systems, although the theory seems to have big potential in the different fields of artificial intelligence. The large computational burden of fuzzy logic systems is only justified if a model describing the relation between input and output does not exist. This is the case in the current application, where the relation between the input parameters (β ratio, α ratio, the difference between the two, and BS%) and the clinical state is unknown; therefore, no model is available, which means that the neuro-fuzzy method offers a fast and robust alternative to establish the causal relation between inputs and output. This causal relation may well incorporate nonlinear relations between the linear input parameters, β and α ratio.

When validating a depth of anesthesia monitor, it can only be called accurate if it (1) provides an accurate correlation with cerebral drug effect reflected by its effect site concentration, (2) correlates well with the clinical state of the patients, and (3) informs the clinician when excessive levels of anesthesia are present. In this study, these three aspects were tested using existing databases. The propofol effect site concentration has shown a good correlation to anesthetic depth in several studies, in particular in controlled patient groups; therefore, it was used in this study to evaluate the performance of the CSI as a cerebral drug effect monitor in comparison to BIS and AAI⁶⁰.7–9,26Even more important, a depth of anesthesia monitor should first of all correlate well with the clinical state of the patient, with minimum time delay and variation. To investigate this, we selected the OAA/S score because it provides a good correlation with a clinical reflection of the hypnotic component of anesthesia and has been tested prospectively,27although it has its limitations, as we pointed out in a previous article.28Burst suppression represents a benign pattern frequently seen in a healthy brain at deep levels of the hypnotic component of anesthesia. It can be identified in the raw electroencephalogram and is composed of episodes of electrical quiescence (the “suppression”) alternated with high-frequency, high-amplitude electrical activity (the “bursts”). Increasing anesthetic drug concentration causes increased duration of the suppression periods. Burst suppression patterns of the electroencephalogram are classically quantified as the percentage duration of suppression over a given time period. Because the detection of burst suppression represents an important electroencephalogram component to measure deep levels of anesthesia, its correlation to its univariate parameter is important and must be investigated9 

The current study demonstrated that both a continuous (protocol 1) and a stepwise increase (protocol 2) in Ce prop resulted in a monotonic decrease in the CSI. These results are comparable with those of our previous study,7,8where it was shown that AAI and BIS decrease during increased Ce prop. In protocol 1, CSI showed the highest correlation to the effect site concentration of propofol. The highest concentration of Ce prop was 14 μg/ml which resulted in CSI values approximately from 10 to 20. The higher correlation might be because the CSI system was partially trained with propofol data, so the pharmacologic relation is already installed in the system. More research must be done to test the behavior of the CSI when other drugs and drug combinations are used. The behaviors of the two indices derived from the spontaneous electroencephalogram, CSI and BIS, are shown in figure 2to be similar. In this study, a nearly pure linear relation was found between CSI and BIS. Although scientifically not that important, it is interesting from a clinical point of view to have values in the same range with different monitors when indicating identical clinical hypnotic–anesthetic states. Although the overall correlation between CSI and BIS is high, individual variations were present, e.g. , a CSI value of 35 simultaneously with a BIS of 70, or vice versa , a BIS value of 30 while the CSI was 80. Those individual values are difficult to account for with the current study design; however, it could be due to interference from electromyography in either device. In the awake state, there was a high clustering of data with values of both CSI and BIS above 90. It cannot be ruled out that the CSI has some influence of facialis electromyography. This should be explored in a study where neuromuscular blocking agents are administered.

As said, the behavior of the index at levels of burst suppression was studied. The linear regressions between the indices and their burst suppression shows the highest linearity for CSI, also at low values of BS%, than the corresponding linear regression between BIS and the suppression ratio calculated by the BIS® monitor. The relation between BIS and the suppression ratio seems to be biphasic, as published previously,11which in turn may indicate a better detection of the onset of suppression by the CSI. The AAI⁶⁰has less correlation, but monophasic, to the BS% because the BS% has less weight in the AAI algorithm. As shown in figure 5and table 3, a decrease in the OAA/S score resulted in a monotonic decrease in the three indices, CSI, BIS, and AAI⁶⁰. A difference between the ability to differentiate the adjacent levels of the OAA/S scale was significant. As seen in previous work,11BIS and AAI revealed relevant information until loss of consciousness but did not become significant at deeper levels of anesthesia because of the wide variability among patients. The CSI was less significant at the intermediate levels 2 and 3 but was able to distinguish the lowest levels of the OAA/S scale, indicating both loss of responsiveness to verbal and tactile stimuli.

The P^Kis widely used to investigate the overall relative performance of the different electroencephalogram-derived indices to measure the hypnotic component of anesthesia.24,25Therefore, P^Kanalysis was conducted on the study data of protocol 2. Table 4shows that the CSI has a similar performance to BIS and AAI⁶⁰in terms of predicting the clinical state of the patient assessed by the OAA/S scale. Interestingly, the P^Kvalue for AAI⁶⁰(0.91), hereby using the new composite index based on MLAEP and electroencephalographic components, performed somewhat better than the original solitary used fast extracting AEP index (AAI version 1.4, scaled from 0 to 100) as published in the original article7using the same data sets (P^K= 0.89).

In conclusion, this study shows that the CSI produces a highly significant correlation with the propofol effect site concentration and has a high P^Kfor the OAA/S. Further studies are needed to validate the CSI to establish its reliability in clinical practice applying other types of anesthetics and other patient groups.

The objective of the Cerebral State Index (CSI) is to monitor the level of consciousness during general anesthesia. The CSI is a unitless scale from 0 to 100, where 0 indicates a flat electroencephalographic signal and 100 indicates the awake state. The range of adequate anesthesia is designed as the 40–60 range (table A1).

The CSI requires three electrodes positioned at the middle forehead, left forehead, and left mastoid. Alternatively, the right forehead and right mastoid can be used.

The CSI is calculated based on four subparameters of the electroencephalogram: β ratio, α ratio, β ratio −α ratio, and burst suppression, defining an index from 0 to 100. The novelty of the CSI is that a fuzzy inference system was used to define the index.

The particular method used was the Adaptive Neuro Fuzzy Inference System (ANFIS). The ANFIS was trained with prerecorded electroencephalographic data, where 20 were from propofol and remifentanil anesthesia, 15 were from propofol infusion until 80% of burst suppression occurred, and 15 were from sevoflurane anesthesia, giving a total of 50 patients. The total number of training points was more than 200,000, sufficient to achieve convergence for the 104 parameters in the 4 input 2 membership ANFIS model. All data were recorded at Gent University Hospital (Ghent, Belgium).

During burst suppression, the α and β ratios are no longer monotonously decreasing as a function of anesthetic depth, and therefore, they cannot be used in the calculation of the final index. Figure A1shows the power spectrum of the electroencephalographic signal with the bands of the β ratio marked.

The four subparameters were defined as follows:

Burst suppression (BS%): defined as the percentage of time in a 30-s window where the amplitude of the electroencephalographic signal was less than 3.5 μV.

Each of the three energy ratios correlates individually to the depth of anesthesia. This has been shown in numerous publications. However, by combining the parameters, a higher correlation coefficient can be reached. An intuitive explanation to this fact is that the ANFIS system, shown in figure A2, automatically uses the best parameter, meaning that when one fails, another might still be a good correlate. The burst suppression parameter indicates deep anesthesia; in this case, the weight on the spectral parameters will be less because they are not good correlates during deep anesthesia with burst suppression due to the nonstationary nature of the electroencephalogram in this situation. The structure of the ANFIS systems ensures that each linguistic term is represented by only one fuzzy set. The parameters of the ANFIS model were determined by training using 50 patients anesthetized with propofol, remifentanil, and inhalational agents. The total update delay of the index is approximately 15 s.