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Anesthesia & Analgesia:
doi: 10.1213/ANE.0b013e31825801ea
Technology, Computing, and Simulation: Technical Communication

Time Delay of Monitors of the Hypnotic Component of Anesthesia: Analysis of State Entropy and Index of Consciousness

Kreuzer, Matthias MSc*; Zanner, Robert MD; Pilge, Stefanie MD; Paprotny, Sabine MD*; Kochs, Eberhard F. MD*; Schneider, Gerhard MD

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Author Information

From the *Department of Anesthesiology, Technische Universität München, Munich, Germany; Department of Anesthesiology, Witten/Herdecke University, HELIOS Clinic, Wuppertal, Germany.

Funding: None

Reprints will not be available from the authors.

This report was previously presented, in part, at the SNACC 2009.

Matthias Kreuzer, MSc and Robert Zanner, MD contributed equally to this work and are co-first authors.

Address correspondence to Gerhard Schneider, MD, Department of Anesthesiology, Witten/Herdecke University, HELIOS Clinic Wuppertal, Heusnerstr. 40, 42283 Wuppertal, Germany. Address e-mail to Gerhard.Schneider@uni-wh.de.

Accepted March 29, 2012

Published ahead of print May 14, 2012

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Abstract

Monitors evaluating the hypnotic component of anesthesia by analyzing the electroencephalogram (EEG) may help to decrease the incidence of intraoperative awareness with recall. To calculate an index representing the anesthetic level, these monitors have different time delays until the correct index is displayed. In previous studies, intraoperatively recorded real and simulated EEG signals were used to determine time delays of cerebral state and Narcotrend and Bispectral indices. In the present study, we determined time delays of state entropy and index of consciousness. For this purpose, recorded real and simulated EEG sequences representing different anesthetic levels were played back to the tested monitors.

Simulated and real perioperatively recorded EEG signals indicating stable states “awake,” “general anesthesia,” and “cortical suppression” were used to evaluate the time delays. Time delays were measured when switching from one state to another and were defined as the required time span of the monitor to reach the stable target index. Comparable results were obtained using simulated and real EEG sequences. Time delays were not constant and ranged from 18 to 152 seconds. They were also different for increasing and decreasing values. Time delays were dependent on starting and target index values. Time delays of index calculation may limit the investigated monitor's ability to prevent interoperative awareness with recall. Different time delays for increasing and decreasing transitions could be a problem if the monitors are used for pharmacodynamic studies.

Monitoring the hypnotic component of anesthesia has gained popularity over recent years and may help reduce the incidence of awareness with recall. Numerous devices are available, which use electroencephalogram (EEG) data to indicate the monitored patient's anesthetic state.

State entropy (SE) is implemented in the Entropy Module (GE Healthcare, Helsinki, Finland) and is based on spectral entropy that can be calculated from Shannon Entropy1 transferred to the frequency scale. SE analyzes the frequency range from 0.8 to 32 Hz. Higher frequencies are excluded to eliminate electromyogram artifacts. It is calculated over varying time windows from 15 seconds to 60 seconds depending on the frequency components. For a detailed explanation of the algorithm, see Viertiö-Oja et al.2 SE is displayed as a dimensionless number where a maximal value of 91 indicates an awake and fully responsive patient. The index range from 40 to 60 is recommended for clinical meaningful anesthesia. Suppression of cortical activity results in a SE equal to 0.

The index of consciousness (IoC; Morpheus Medical, Barcelona, Spain) is designed from a combination of symbolic dynamics, β-ratio, and EEG suppression rate. A detailed description of IoC generation can be found in the Appendix of Revuelta et al.3 The IoC ranges from 0 to 99, where 99 indicates an awake patient, 80 stands for sedation, and the range from 40 to 60 is defined as the state recommended for general anesthesia. An IoC of 0 indicates isoelectric EEG.

For every monitor, calculation and display of index values require a certain amount of time. This results in a delayed display of a new index value after a change in the anesthetic state of a patient. In previous studies, we determined time delays for Bispectral (BIS), cerebral state (CSI), and Narcotrend (NCT) indices at the transition of different states of consciousness using simulated and perioperatively recorded real EEG signals4,5 and found considerable time delays for all tested monitors. The aim of our present investigation was to determine time delays for SE and IoC.

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METHODS

Monitors

The following monitors were investigated: Entropy Module (GE Healthcare, Helsinki, Finland) providing SE values, and IoC View (Morpheus Medical, Barcelona, Spain) providing IoC values.

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EEG Signals

Artificial EEG sequences were generated using LabView 6.0 (National Instruments, Austin, TX) as described previously.5 Briefly, “sine wave” and “periodic random noise waveform” (PRN) modules were used to generate artificial EEG sequences. Therefore, 2 sine waves and 1 periodic random noise signal were added and replayed to tested monitors with 1 kHz sampling rate. For “cortical suppression,” no input signal was used.

The input signals created stable index values for “cortical suppression” (IoC <3, SE = 0), “general anesthesia” (IoC = 48/49, SE = 50/51), and “awake” (IoC = 99, SE = 91). Different signals were used for IoC and SE, because a stable index in monitor A did not necessarily result in a stable index in monitor B. For example, the signals used for SE evaluation returned invalid IoC values, the signals used for the IoC resulted in SE values indicating a deeper anesthetic level. All artificially generated signals were replayed for 3 minutes.

Methods for using recorded real EEG data have been described in detail elsewhere.6 Briefly, EEG sequences recorded during volunteer studies were extracted from the institute's database and sequences of 5 minutes length generating index values with minimal oscillations were played to IoC View and Entropy Module. For “awake” and “general anesthesia,” 5 sequences for each state of consciousness and monitor were used. The 5 sequences indicating “general anesthesia” were different for each monitor, whereas 4 EEG sequences indicating “awake” were used for both monitors. Different sequences had to be used because monitors reacted differently to EEG sequences, e.g., an EEG sequence that led to a stable SE indicating “general anesthesia” resulted in unstable IoC values in the “light anesthesia” range. For “cortical suppression” 1 recorded signal was used for both monitors.

Sequences of different anesthetic states were concatenated using LabView and played back to the monitors, i.e., there was a sudden switch in the signal from EEG representing state A to EEG representing state B. Transitions were from (a) “cortical suppression” to “general anesthesia, (b) “cortical suppression” to “awake,” and (c) “general anesthesia” to “awake” and vice versa for real and artificial EEG sequences. These concatenated sequences were replayed to the monitors using the EEG player.6 The player stores the data to be played back in a buffer and plays it back to the monitor after a 1 kHz digital to analog conversion, which complies with the sampling rate during recording of the EEG sequences.

The time span from switching the EEG sequences to reaching the target index value was measured and defined as the time delay. Because all selected sequences showed some variation over time, reference points for measurements were identified as described previously.6 Furthermore, the time delays of the indices to reach the index range for “awake” (index ≥ 80) and “general anesthesia” (40 ≤ index ≤ 60) were measured.

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Data Collection

Monitor data were recorded with IoC Graph v1.0 software (Morpheus Medical, Barcelona, Spain) via Bluetooth and S/5 L-Collect (GE Healthcare, Helsinki, Finland) software via RS232 serial connection for IoC and SE, respectively. Update rate of the monitors was 1 second for the IoC and 10 second for SE.

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Data Analysis

Index trend data and time were exported from the IoC Graph and L-Collect software and imported to Microsoft Excel 2000 (Microsoft Corporation, Redmond, WA). Time delays were manually extracted to Excel from the imported index and time vectors. Therefore, the following time points were marked in the Excel sheet: starting replay of input signal, change of input signal, and reaching of target value. The R 2.8.0 software (The R Foundation for Statistical Computing, Vienna, Austria) was used for generating the figures. Time delays are expressed as mean (±SD).

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RESULTS

Time delays of the tested monitors ranged from 21(3) to 152 (3) seconds. Time delays for simulated EEG input signals are shown in Tables 1 and 2 and Figure 1, time delays for recorded EEG signals in Tables 3 and 4 and Figure 2.

Table 1
Table 1
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Table 2
Table 2
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Figure 1
Figure 1
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Table 3
Table 3
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Table 4
Table 4
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Figure 2
Figure 2
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Simulated EEG

SE showed fast transitions from anesthetic stages “awake” and “general anesthesia” to “cortical suppression” with a delay of 23 and 21 seconds, respectively. We measured longer time delays for transitions between increasing index values than for transitions between decreasing index values for both, reaching stable index values, and the index range representing a specific anesthetic state. Reaction time for the transition from “cortical suppression” to “awake” was longest with 107 seconds to reach the stable value and 57 seconds to gain values above 80. SE rapidly increased to a value above 89 indicating a sedated patient but then only slowly reached the target value of 91.

Time delays measured for IoC were longer for decreasing index values and for the transition from “general anesthesia” to “awake.” Time delays for transition from “cortical suppression” to “general anesthesia” and “awake” appeared shorter for IoC than for SE. For the transition from “anesthesia” to “awake,” IoC required 68 seconds to reach the stable index but only 21 seconds to surpass an index of 80.

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Real EEG

We measured longer time delays for real EEG sequences compared to simulated EEG input signals. Time delays generally appeared longer for IoC than for SE with the only exception being the transition from “cortical suppression” to “awake.”

The time delays found for real EEG sequences are in concordance with results obtained when using simulated EEG. Delay times to reach the desired index levels were only slightly shorter than to reach stable index values.

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DISCUSSION

The results of our present study show that both indices, SE and IoC, show considerable time delays for both reaching stable index values as well as the desired index range representing a specific anesthetic level. Compared to our previous studies investigating time delays of index calculation for BIS, NCT, and CSI, index calculation times of SE and IoC in the present study were in a similar range, i.e.,14 seconds to 155 seconds for artificial and 24 seconds to 122 seconds for recorded EEG signals, as those found for BIS, NCT, and CSI (Table 5).4,5 Time delays of SE and IoC were not constant and differed for the transitions between different stages of anesthesia. Calculation times were also different between increasing and decreasing index values.

Table 5
Table 5
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Morpheus Medical published an article on their website where IoC time delay was evaluated for abrupt changes from “awake” to isoelectric EEG and vice versa and from “awake” to IoC = 73 and vice versa.a Time delay for transition between “awake” and “isoelectric EEG” was 91 seconds and 53 seconds from “isoelectric EEG” to “awake.” These results are comparable to the time delays found in our present study.

Limitations of our approach may be the use of simulated/recorded EEG and the appearance of “switch” discontinuities when concatenating the sequences representing different anesthetic levels. Still, this approach seems to be the only way to perform a sudden switch from one state to another and evaluate the monitor's reaction to it. The monitor's time delay cannot be precisely evaluated in patients because, in addition to the monitor's time delay, hysteresis effects must be considered. One would expect the typical hysteresis effect to increase the delay time. Hysteresis may strongly vary from case to case and can hence not be calculated. The long and varying time delays, which are also different for increasing and decreasing transition, may be a major limitation in the use for pharmacodynamic modeling, particularly if the detailed parameter setting of the monitor's algorithms remains unknown to the user.

In summary, SE and IoC, both indices reflecting the hypnotic component of anesthesia, show a considerable time delay in reflecting the actual anesthetic level. This delay may be a limitation in detecting events like intraoperative awareness in time to prevent an adverse event. Different time delays for changes between different anesthesia levels and for changes between identical anesthesia levels in the opposite direction may also limit the application of these monitors for pharmacodynamic modeling.

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DISCLOSURES

Name: Matthias Kreuzer, MSc.

Contribution: This author helped analyze the data, write the manuscript, and extract recorded EEG and EEG simulation.

Attestation: Matthias Kreuzer approved the final manuscript.

Conflicts of Interest: This author has no conflicts of interest to declare.

Name: Robert Zanner, MD.

Contribution: This author helped design the study, analyze the data, and write the manuscript.

Attestation: Robert Zanner approved the final manuscript.

Conflicts of Interest: This author has no conflicts of interest to declare.

Name: Stefanie Pilge, MD.

Contribution: This author helped analyze the data and write the manuscript.

Attestation: Stefanie Pilge approved the final manuscript.

Conflicts of Interest: This author has no conflicts of interest to declare.

Name: Sabine Paprotny, MD.

Contribution: This author helped analyze the data and data acquisition.

Attestation: Sabine Paprotny approved the final manuscript.

Conflicts of Interest: This author has no conflicts of interest to declare.

Name: Eberhard F. Kochs, MD.

Contribution: This author helped design the study and write the manuscript.

Attestation: Eberhard F. Kochs approved the final manuscript.

Conflicts of Interest: This author has no conflicts of interest to declare.

Name: Gerhard Schneider, MD.

Contribution: This author helped design the study and write the manuscript.

Attestation: Gerhard Schneider approved the final manuscript.

Conflicts of Interest: This author has no conflicts of interest to declare.

This manuscript was handled by: Dwayne R. Westenskow, PhD.

a http://www.morpheus-medical.com/fileadmin/morpheus_files/ioc_view/update_delay_over_time.pdf. Cited Here...

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REFERENCES

1. Shannon C. A mathematical theory of communication. Bell System Techn J 1948;27:379–423, 623–56

2. Viertio-Oja H, Maja V, Sarkela M, Talja P, Tenkanen N, Tolvanen-Laakso H, Paloheimo M, Vakkuri A, Yli-Hankala A, Merilainen P. Description of the entropy algorithm as applied in the Datex-Ohmeda S/5 Entropy Module. Acta Anaesthesiol Scand 2004;48:154–61

3. Revuelta M, Paniagua P, Campos JM, Fernandez JA, Martinez A, Jospin M, Litvan H. Validation of the index of consciousness during sevoflurane and remifentanil anaesthesia: a comparison with the bispectral index and the cerebral state index. Br J Anaesth 2008;101:653–8

4. Zanner R, Pilge S, Kochs EF, Kreuzer M, Schneider G. Time delay of electroencephalogram index calculation: analysis of cerebral state, bispectral, and Narcotrend indices using perioperatively recorded electroencephalographic signals. Br J Anaesth 2009;103:394–9

5. Pilge S, Zanner R, Schneider G, Blum J, Kreuzer M, Kochs E. Time delay of index calculation: analysis of cerebral state, bispectral, and narcotrend indices. Anesthesiology 2006;104:488–94

6. Kreuzer M, Kochs EF, Pilge S, Stockmanns G, Schneider G. Construction of the electroencephalogram player: a device to present electroencephalogram data to electroencephalogram-based anesthesia monitors. Anesth Analg 2007;104:135–39

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