Year : 2012 | Volume
| Issue : 2 | Page : 131-135
Spectral entropy as an objective measure of sedation state in midazolam-premedicated patients
Hany A Mowafi
Department of Anaesthesia, Faculty of Medicine, King Faisal University, Saudi Arabia
Hany A Mowafi
Department of Anaesthesiology, King Fahd University Hospital, PO Box 40081, Al-Khobar, 31952
Source of Support: None, Conflict of Interest: None
|Date of Web Publication||8-Jun-2012|
Context: Objective assessment of sedation depth is a valuable target. Spectral entropy is an anesthetic depth monitor based on the analysis of the electroencephalogram signal. Aims: To evaluate the performance of spectral entropy as an objective measure of sedation state in midazolam-premedicated patients and to correlate it with a clinically assessed sedation score. Settings and Design: This prospective double-blind placebo-controlled study was performed in King Fahd Hospital of the university. Methods: Eighty adult ASA I-II patients were randomly assigned into 4 groups. Patients were premedicated using 0.02, 0.04, or 0.06 mg/kg midazolam or saline intramuscularly. The effect of these doses on the Observer's Assessment of Alertness and Sedation (OAA/S) scale, hemodynamic variables, response entropy (RE), and state entropy (SE), was evaluated at 10, 20, and 30 min after premedication. Statistical analysis: Spearman Rank-order correlation analysis to examine the relation between OAA/S and entropy. The ability of spectral entropy to predict the depth of sedation was evaluated using Smith prediction probability. Results: Midazolam doses ≥0.04 mg/kg produced significant decreases in RE, SE, and OAA/S scores. There was a strong correlation between midazolam dose and OAA/S scale, RE, and SE since Spearman Rank R values were 0.792, 0.822, and 0.745, respectively (P<0.001). In addition, RE and SE were strong predictors of OAA/S level during midazolam sedation with no significant difference in prediction between the 2 entropy components. Conclusions: Spectral entropy is a reliable measure for the sedative premedication. It may be used to objectively assess the adequacy of midazolam premedication and to determine the dose requirement.
Keywords: Monitoring, depth of anaesthesia, observer′s assessment of alertness and sedation, premedication, midazolam, sedation
|How to cite this article:|
Mowafi HA. Spectral entropy as an objective measure of sedation state in midazolam-premedicated patients. Saudi J Anaesth 2012;6:131-5
|How to cite this URL:|
Mowafi HA. Spectral entropy as an objective measure of sedation state in midazolam-premedicated patients. Saudi J Anaesth [serial online] 2012 [cited 2020 Nov 25];6:131-5. Available from: https://www.saudija.org/text.asp?2012/6/2/131/97025
| Introduction|| |
Sedative premedication is required to avoid psychologic discomfort and allay anxiety of patients. The efficacy of anesthetic premedication has been evaluated using several sedative scores, including the Ramsay and Observer's Assessment of Alertness/Sedation (OAA/S) scales. , These estimation tools might be affected by the evaluators' variability or subjects' presumption causing a placebo effect. , An additional defect during clinical application of such methods is the repeated verbal or tactile stimulation of the subject to elicit a response. , Objective assessment of the efficacy of anesthetic premedication is still difficult.
Several systems based on the electroencephalogram (EEG) have been developed as depth of anesthesia monitors. , The spectral entropy has been developed to objectively assess the depth of anesthesia during clinical practice. , The monitor derives 2 indices: the state entropy (SE), which reflects the cortical activity of the subject, and the response entropy (RE), which also includes frontal electromyographic (EMG) activity. , Entropy parameters may determine the effect of anesthetics on the subject's central nervous system.  However, the validity and utility of spectral entropy as an objective tool to examine the efficacy of sedative premedication have not been evaluated. The aim of this study was to assess whether entropy can be used to measure the sedation status in midazolam-premedicated adult patients by correlating entropy values to the dose of midazolam used and with a clinical sedation scale.
| Methods|| |
Following the local research ethics committee approval and an informed written patient consent, 80 adult subjects of ASA I or II, scheduled for elective orthopedic or general surgical procedures were included in the study. Patients were excluded if they were older than 60 years, had a body weight more than 150% of their ideal body weight using Broca's index, neurologic disease, endocrine disorders, psychiatric illness, hearing defect, or a history of drug abuse and those on drugs with sedative or central nervous system effects. Patients were randomly allocated using an online research randomizer (http://www.randomizer.org) into 4 groups (20 patients each). Forty-five minutes before surgery, patients were admitted to an isolated quiet room in the operating theater suite. Ambient temperature was kept at 21-24°C. Subjects were monitored with an electrocardiograph (ECG), noninvasive blood pressure, peripheral pulse oximetry (SpO 2 ), and spectral entropy (Datex-Ohmeda S/5 Anaesthesia Monitor, Helsinki, Finland). An entropy sensor was applied to the patients' forehead according to the manufacturer's specifications and passed the initial impedance check. The spectral entropy plug-in module calculated state entropy (SE) and response entropy (RE) variables. An anesthesiologist used the OAA/S [Table 1] to measure the sedation depth clinically.  After resting for a minimum of 5 min and before injection of premedication, baseline heart rate, mean arterial pressure, RE, SE, and OAA/S were obtained for each patient. Patients were then premedicated with either saline (control group) or midazolam 0.02, 0.04, and 0.06 mg/kg intramuscularly in the deltoid muscle. After premedication, at 10, 20, and 30 min, OAA/S scores, the hemodynamic and entropy data were recorded. An observer who was blinded to the patient allocation recorded all data. To minimize potential observer bias, another investigator, blinded to entropy values and treatment plan, performed all OAA/S assessments. The RE and SE at each OAA/S score were calculated by averaging 3 values immediately before OAA/S score assessment.
Data were analyzed using Statistica software version 7.0 for windows (Statsoft, Inc. Tulsa, USA). After testing for normal distribution using the Kolmogorov-Smirnov test, the demographic data were analyzed using one-way analysis of variance or Chi-square analysis as appropriate. Entropy values and OAA/S scores were compared at different doses of midazolam using Kruskal-Wallis analysis of variance on ranks with post hoc analysis. Spearman Rank-order correlation analysis was performed to evaluate the relationship between the doses of midazolam and the different measures of sedation. It was also used to examine the relationship between OAA/S and RE and SE components of entropy. To evaluate the significance between the obtained Spearman rank correlations, the method described by Steiger  was used. A P value<0.05 was considered significant.
The ability of spectral entropy to predict the depth of sedation using the OAA/S was evaluated using P K OAA/S . P K is the probability that an indicator correctly predicts the depth of sedation. An indicator that predicts perfectly the depth of sedation has a P K value of 1.0, whereas an indicator that performs no better than chance has a P K value of 0.5. The mathematical basis of P K was described by Smith et al.  To compute the P K, the RE and SE entropy scores were analyzed as the predicting variables and the OAA/S scale was the value of the variable to be predicted. The P K computed in this case is the estimate of the probability that the RE or SE will correctly predict the OAA/S score. The jack-knife method was used to compute the standard error of the P K estimate. P K calculations were performed with Excel software using a custom spreadsheet macro, PKMACRO, and were compared using PKDMACRO. Smith and colleagues developed both the macros. 
| Results|| |
Our study included 34 females and 46 males, with age ranging between 21 and 50 years, a mean height of 167 ± 14 cm, and weight of 72 ± 11 kg. There were no significant differences in all demographic characteristics between the 4 groups.
[Figure 1] shows entropy and OAA/S values in the control group and at different midazolam doses. There were no significant differences between the control and 0.02 mg/kg groups. Increasing the dose of midazolam decreases the RE, SE, and OAA/S values significantly. However, there was no significant difference between 0.04 and 0.06 mg/kg doses. There were strong significant correlations between midazolam doses and RE, SE, and OAA/S, where the Spearman Rank R values were 0.822, 0.745, and 0.792, respectively (P<0.001).
|Figure 1: Box plot graphic of response entropy (RE) and state entropy (SE) represented on the left Y axis, and Observer's Assessment of Alertness/Sedation (OAA/S) Scale scores represented on the right Y axis at different midazolam doses in mg/kg. Data points represent medians, boxes are interquartile ranges, and whiskers are nonoutlier ranges. *Significant difference in comparison with 0 mg/kg; #significant difference in comparison with 0.02 mg/kg|
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There was a strong significant correlation between entropy and OAA/S values. Spearman Rank R values for RE and SE were 0.717 and 0.637 (P<0.0001), respectively. Entropy was effective in predicting the OAA/S level of sedation during midazolam premedication. The prediction probability P K OAA/S (SEM) values for RE and SE were 0.841 (0.015) and 0.808 (0.021), respectively, with no significant difference between the 2 entropy components in predicting the OAA/S level.
No significant correlations were found between the hemodynamic variables and midazolam dose or the sedation level as measured by the entropy or OAA/S.
| Discussion|| |
The main finding in this study was that spectral entropy could be used as a reliable objective measure of the sedative effects of midazolam premedication. RE and SE predicted efficiently the level of sedation as measured by OAA/S and were strongly correlated with the doses of midazolam used.
Midazolam premedication can relieve patients' anxiety, decrease intraoperative awareness, and provide an appropriate sedation level. The effect of midazolam on the consciousness level differs between patients.  An "ideal" sedation scoring tool does not exist. Several subjective scores have been developed as tools to assess sedation.  The aim is to avoid oversedation with its many potential deleterious side effects, such as delayed recovery, loss of airway, respiratory arrest, and aspiration. They describe the response to graduated reproducible stimuli. To facilitate the clinical evaluation of midazolam-induced sedation, Chernik et al developed the Observers' Assessment of Alertness/Sedation (OAA/S) scale.  This method of assessment necessitates that the patient will be stimulated at frequent intervals, a practice that may disturb patients. A further limitation of the OAA/S scale is that it depends on the patients' cooperation and is subject to testing fatigue.  Therefore, objective assessment of sedation depth using a consistent, noninvasive sedation monitor is an appealing goal. Many approaches have been evaluated, but most suffer from poor validation with scoring systems or have large intra- and inter-patient variability.  We select the OAAS scale, as a reference monitor of sedation, because it provides a good correlation with the clinical evaluation of sedation state and has been previously confirmed in several studies. ,
Our assumption was that this scale, which was previously correlated with the observed clinical effects of sedation, would be linearly related to the different midazolam doses and to spectral entropy that can be used as an objective measure of sedation.
Spectral entropy is a commercially available monitor based on the analysis of the EEG signal.  Entropy, as a physical concept, is a measure of irregularity, complexity, or amount of disorder.  With increasing the depth of anesthesia, the EEG changes to more regular patterns, decreasing entropy.  State entropy (SE) is computed over the frequency range from 0.8 to 32 Hz and primarily reflects the state of the cortical activity of the subject. The response entropy (RE) is computed over a frequency range from 0.8 to 47 Hz, and includes both the EEG-dominant and EMG-dominant part of the spectrum. Entropy has a range of 0-100 for RE and a range of 0-90 for SE. The closer to 0, the deeper the level of sedation/anesthesia is. 
Entropy parameters were developed for use during anesthesia, when the main goal is avoidance of awareness. During anesthesia, entropy variables correlate well with surgical anesthetic level and hypnosis. , The system was not developed to monitor patients premedicated with sedative drugs. However, entropy was tested as a monitor of sedation status in the operating room and intensive care unit (ICU) settings. Entropy monitoring showed high performance in assessing the level of dexmedetomidine-induced sedation in healthy subjects.  Acupuncture stimulation at sedative points decreased SE and RE values significantly.  RE and SE discriminated well between sound responses at the different sedation levels using propofol and remifentanil.  Entropy, BIS, and Ramsay score values were significantly correlated in sedated postoperative ICU patients.  The spectral entropy decreased also with deepening of sedation similar to Ramsay score in ICU patients.  In addition, a strong correlation between these 2 indices has been found similarly to the sedation scores described in the operating room. , It was, also, found reliable during propofol and fentanyl sedation in monitored anesthesia care  and to monitor conscious sedation in endstage cancer patients at home.  Moreover, Anderson and Jakobsson demonstrated that increasing levels of sedation provided by propofol during induction of anesthesia decreased the entropy indices significantly and that entropy values at loss of response to verbal commands was significantly different from fully awake values.  The current study is the first study to evaluate spectral entropy as a measure of sedative premedication. Our study demonstrated a correlation relationship between entropy values and OAA/S in adults. Contrary to our study and previous findings, where spectral entropy was correlated to sedation level, entropy measured from frontal EEG had low validity to differentiate clinical sedation state in critically ill patients managed under routine clinical conditions. , The conflicting results in ICU patients may be due to the fact that these patients may have metabolic disorders, encephalopathies, and brain injuries that can affect the EEG. In addition, several centrally acting drugs that confound the EEG signal may be used during ICU sedation.
In a previous study, Smith et al evaluated performance of anesthetic depth indicators. They proposed calculating a prediction probability value, which may provide a better measure to monitor performance. Values provided by an "ideal depth of sedation monitor" should monotonically decrease with increasing sedation depth. The high prediction probability (P K) of sedation level by entropy reflects its high performance and facilitates comparison with other monitors. Additionally, similar to OAA/S values, RE and SE discriminated well between different midazolam doses in premedicated patients. The good correlation between entropy and dose of midazolam used for premedication, coupled with the excellent prediction probability values for the level of sedation, support the value of the spectral entropy as a monitor of sedation level during premedication.
Our findings have some limitations. First, we are not aware of the availability of a portable version of entropy monitor to evaluate the depth of sedation in the ward where sedative premedication is usually given. Second, to eliminate the effect of interindividual pharmacokinetic differences with midazolam premedication correlation of RE, SE, and OAA/S with the serum level of midazolam would have been a logic alternative. Third, our results apply only to midazolam in the dose range used. Further studies may be required to evaluate spectral entropy with other sedatives used as premedication and in different doses.
In conclusion, our study suggests that spectral entropy may have an adequate validity as a measure of sedation state during midazolam premedication.
| References|| |
|1.||McCormick AS, Thomas VL, Berry D, Thomas PW. Plasma concentrations and sedation scores after nebulized and intranasal midazolam in healthy volunteers. Br J Anaesth 2008;100:631-6. |
|2.||Chernik DA, Gillings D, Laine H, Hendler J, Silver JM, Davidson AB, et al. Validity and reliability of the observer's assessment of alertness/sedation scale: Study with intravenous midazolam. J Clin Psychopharmacol 1990;10:244-51. |
|3.||Hirota K, Matsunami K, Kudo T, Ishihara H, Matsuki A. Relation between bispectral index and plasma catecholamines after oral diazepam premedication. Eur J Anaesthesiol 1999;16:516-8. |
|4.||Hogarth DK, Hall J. Management of sedation in mechanically ventilated patients. Curr Opin Crit Care 2004;10:40-6. |
|5.||Voss L, Sleigh J. Monitoring consciousness: The current status of EEG-based depth of anaesthesia monitors. Best Pract Res Clin Anaesthesiol 2007;21:313-25. |
|6.||Davidson AJ, Huang GH, Rebmann CS, Ellery C. Performance of entropy and Bispectral Index as measures of anaesthesia effect in children of different ages. Br J Anaesth 2005;95:674-9. |
|7.||Viertiö-Oja H, Maja V, Särkelä M, Tenkanen N, Tolvanen-Laakso H, Paloheimo M, et al. Description of the entropy algorithm as applied in the Datex-Ohmeda S/5 Entropy Module. Acta Anaesthesiol Scand 2004;48:154-61. |
|8.||Iannuzzi M, Iannuzzi E, Rossi F, Berrino L, Chiefari M. Relationship between bispectral index, electroencephalo-graphic state entropy and effect-site EC50 for propofol at different clinical endpoints. Br J Anaesth 2005;94:492-5. |
|9.||Vakkuri A, Yli-Hankala A, Talja P, Mustola S, Tolvanen-Laakso H, Sampson Tl, et al. Time-frequency balanced spectral entropy as a measure of anaesthetic drug effect in central nervous system during sevoflurane, propofol, and thiopental anesthesia. Acta Anaesthesiol Scand 2004;48:145-53. |
|10.||Steiger J. Tests for comparing elements of a correlation matrix. Psych Bull 1980;87:245-51. |
|11.||Smith WD, Dutton RC, Smith NT. Measuring the performance of anesthetic depth indicators. Anesthesiology 1996;84:38-51. |
|12.||Nishiyama T, Matsukawa T, Hanaoka K. The effects of age and gender on the optimal premedication dose of intramuscular midazolam. Anesth Analg 1998;86:1103-8. |
|13.||Mirski MA, Hemstreet MK. Critical care sedation for neuroscience patients. J Neurol Sci 2007;261:16-34. |
|14.||Tonner PH, Paris A, Scholz J. Monitoring consciousness in intensive care medicine. Best Pract Res Clin Anaesthesiol 2006;20:191-200. |
|15.||Mourisse J, Gerrits W, Lerou J, VanEgmond J, Zwarts MJ, Booij L. Electromyographic assessment of blink and corneal reflexes during midazolam administration: Useful methods for assessing depth of anaesthesia? Acta Anaesthesiol Scand 2003;47:593-600. |
|16.||Mourisse J, Lerou J, Zwarts M, Booij L. Electromyographic assessment of blink reflexes correlates with a clinical scale of depth of sedation/anaesthesia and BIS during propofol administration. Acta Anaesthesiol Scand 2004;48:1174-9. |
|17.||Bruhn J, Röpcke H, Hoeft A. Approximate Entropy as an electroencephalographic measure of anesthetic drug effect during desflurane anesthesia. Anesthesiology 2000;92:715-26. |
|18.||Vanluchene AL, Struys MM, Heyse BE, Mortier EP. Spectral entropy measurement of patient responsiveness during propofol and remifentanil: A comparison with the bispectral index. Br J Anaesth 2004;93:645-54. |
|19.||Maksimow A, Snapir A, Särkelä M, Kentala E, Koskenvuo J, Posti J, et al. Assessing the depth of dexmedetomidine-induced sedation with electroencephalogram (EEG)-based spectral entropy. Acta Anaesthesiol Scand 2007;51:22-30. |
|20.||Litscher G. Electroencephalogram-entropy and acupuncture. Anesth Analg 2006;102:1745-51. |
|21.||Gjerstad AC, Storm H, Hagen R, Huiku M, Qvigstad E, Raeder J. Skin conductance or entropy for detection of non-noxious stimulation during different clinical levels of sedation. Acta Anaesthesiol Scand 2007;51:1-7. |
|22.||Hernández-Gancedo C, Pestaña D, Pérez-Chrzanowska H, Martinez-Casanova E, Criado A. Comparing entropy and bispectral index with the Ramsay score in sedated ICU patients. J Clin Monit Comput 2007;21:295-302. |
|23.||Ferenets R, Lipping T, Anier A, Jäntti V, Melto S, Hovilehto S. Comparison of entropy and complexity measures for the assessment of depth of sedation. IEEE Trans Biomed Eng 2006;53:1067-77. |
|24.||White P, Tang J, Romero G, Wender RH, Naruse R, Sloninsky A, et al. A comparison of state and response entropy versus bispectral index values during the perioperative period. Anesth Analg 2006;102:160-7. |
|25.||Schmidt G, Bischoff P, Standl T, Hellstern A, Teuber O, Schulte J. Comparative evaluation of the Datex-Ohmeda S/5 entropy module and the bispectral index monitor during propofol-remifentanil anesthesia. Anesthesiology 2004;101:1283-90. |
|26.||Balci C, Karabekir HS, Kahraman F, Sivaci RG. Comparison of entropy and bispectral index during propofol and fentanyl sedation in monitored anaesthesia care. J Int Med Res 2009;37:1336-42. |
|27.||Michelagnoli G, Consales G, Morino P, De Gaudio AR. Entropy: An unusual method to titrate the administration of palliative sedation. Minerva Anestesiol 2010;76:561-2. |
|28.||Anderson RE, Jakobsson JG. Entropy of EEG during anaesthetic induction: A comparative study with propofol or nitrous oxide as sole agent. Br J Anaesth 2004;92:167-70 |
|29.||Walsh TS, Ramsay P, Petteri Lapinlampi T, Särkelä MO, Viertiö-Oja HE, Meriläinen PT. An assessment of the validity of spectral entropy as a measure of sedation state in mechanically ventilated critically ill patients. Intensive Care Med 2008;34:308-15. |
|30.||Haenggi M, Ypparila-Wolters H, Buerki S, Schlauri R, Korhonen I, Takala J, et al. Auditory event-related potentials, bispectral index, and entropy for the discrimination of different levels of sedation in intensive care unit patients. Anesth Analg 2009;109:807-16. |