From the *Department of Anaesthesiology, Waikato Clinical School, University of Auckland, Hamilton, New Zealand; †Department of Anaesthesia, Imperial College NHS Healthcare Trust; ‡Wellcome Department of Imaging Neuroscience, University College London; and §Surgical Outcomes Research Centre, University College London Hospital, London, United Kingdom.
The authors declare no conflicts of interest.
Accepted for publication April 24, 2014.
Reprints will not be available from the authors.
Address correspondence to Jamie W. Sleigh, MD, Department of Anaesthesiology, Waikato Clinical School, University of Auckland, Hamilton, New Zealand. Address e-mail to email@example.com.
It is a truism that general anesthesia involves suppression of the central nervous system’s responses to noxious stimulation. It is not enough to know the state of the patient at any particular moment; it is more important to know how the patient will react to future changes in the level of noxious stimulation: the arousability of the patient. In this edition of Anesthesia & Analgesia, there is an article by Sahinovic et al.,1 which investigates the validity of an electroencephalographic (EEG) measure of the balance between nociception and antinociception in the anesthetized patient. They were evaluating the composite variability index (CVI) and found that it was better in predicting a somatic movement response to a noxious stimulation than a variety of other commonly used measures of depth of anesthesia (the analgesic and hypnotic drug concentrations, bispectral index [BIS], mean arterial blood pressure, and heart rate). The CVI is a proprietary index that uses information from the frontal EEG to quantify the state of relative “analgesia” of the anesthetized patient. The index incorporates information from 3 variables; namely, the short-term variation of the BIS, the frontal electromyograph signals, and the mean BIS value. In essence, it detects a combination of patient grimaces and short EEG arousals. The signal processing and the actual weights for each variable are commercial secrets. The CVI was developed heuristically from a surgical patient database to discriminate between movement and nonmovement. It seems to be about 80% to 90% effective.2
Certainly, the failure of anesthesia to suppress noxious stimulus-induced arousal may be manifest in a variety of ways. These include wakefulness, increased muscle tone and somatic movement, and autonomic system effects (tachycardia, hypertension, and sweating). Accordingly, the various measures of relative analgesia that have been reported in the literature can be broadly categorized into 3 groups. The first method quantifies changes in the autonomic nervous system, such as nociception-induced suppression of heart rate variability (the analgesia nociception index),3 or digit vasoconstriction (surgical pleth index).4 The second looks for nociception-induced changes in the EEG or facial electromyograph (the CVI, but also the gap between the response entropy and state entropy of EEG).2,5,6 The third relies solely on population pharmacokinetic-pharmacodynamic modeling of drug concentrations as surrogates for analgesia and ignore the interindividual variability.7 In some ideal world, these indices might allow individualized titration of general anesthetic drugs to achieve a quicker4 and more comfortable8 recovery period, better intraoperative suppression of stress hormones,9 better intraoperative cardiovascular stability,10 a reduction in unexpected somatic movement, and a reduced likelihood of intraoperative awareness with pain. Practically, these goals are still a long way off. It is unclear which of the indices performs best in clinical practice because proper direct comparisons have not been done. Indeed, it is likely that some combination of the various indices will end up being the most useful. The various indices are only modestly correlated with each other and hence provide somewhat independent and multidimensional views of the state of the patient. It is certainly very clear that the body’s response to noxious stimuli is often very specific and surprisingly structured. The response is more complex and varied than a simple blanket mass activation of the autonomic system. Cardiovascular and EEG arousals are often at variance, and even within the cardiovascular system, it is not uncommon to see digital vasoconstriction (in the surgical pleth index) without tachycardia.
Every practicing anesthesiologist knows that the addition of opioids will reduce the dose of propofol that is required for the patient to tolerate noxious stimuli, such as tracheal intubation or surgical incision. However, what is the best dose combination of hypnotic and analgesic? Should we give a lot of hypnotic and just a little opioid, or vice versa? There is huge variation in practice among anesthesiologists. The heart of the problem lies in determining the correct quantitative understanding of the complex relationship between “pure” hypnotic drugs and their interaction with opioids. Sahinovic et al.1 attempt to address this question by studying 4 clinically relevant concentrations of analgesic drug (remifentanil) with 3 clinical levels of hypnosis (corresponding to heavy sedation, clinical anesthesia, and deep anesthesia) and thus can make some statements about the interactions. They found that at a heavy sedation level of propofol, the CVI increased in all patients, irrespective of the dose of remifentanil. At the other extreme, during deep anesthesia, the increasing concentrations of remifentanil had minimal effect on movement or CVI. However, with medium levels of anesthesia, there is a “sweet spot” of maximal synergism between propofol and remifentanil. Even modest concentrations of remifentanil (2 ng/mL) were enough to decrease the movement and eliminate the increase in CVI. The results of opioid effects in reducing somatic movement are similar to those from a number of previous articles.11 What are the neuropharmacological mechanisms underlying these observations?
The usual model that has been suggested to explain the synergy between opioids and propofol is that the opioids shift the propofol dose-response curve to the left and steepen it.12 This view suggests that the opioids somehow “block” nociceptive input to the cortex, and hence, the patient can be kept unresponsive with a lower concentration of propofol than would be the case if there were no opioids. This is seemingly supported by views that propofol may act “top-down” to specifically obtund cortical responses before subcortical effects,13 while opioids act predominantly “bottom-up.”14,15 While this interpretation seems to explain some clinical and scientific observations, it is problematic. In the absence of any γ-aminobutyric acid (GABA)-ergic drug, opioids do not cut the mustard. Unless used in enormous doses, remifentanil on its own is ineffective in blocking somatic responses to a proper surgical stimulus.12 We need to turn the argument on its head. Propofol is not a classical analgesic drug but can be an antinociceptive drug, and it does interact with brainstem opioid systems.16,17 The top-down modulation of remifentanil analgesia is not new; both placebo and nocebo responses are known to modulate remifentanil analgesia in awake healthy volunteers.18 Whether propofol interacts with the neural circuitry of reward, placebo, and/or nocebo responses to augment remifentanil analgesia requires further investigation. For example, perhaps propofol-induced fracturing of hippocampal connectivity19 may block nocebo-like modulation18 of remifentanil antinociception. In contrast, positive modulation of remifentanil antinociception may be associated with the activation of dopaminergic neurons in the ventral tegmental area20 or altered connectivity of the anterior cingulate cortex with brainstem center.21,22 This area is fertile for further investigation.
The study by Sahinovic et al.1 shows that, at somewhere slightly above the concentration required for loss of response to verbal command, propofol is suddenly able to vastly amplify the antinociceptive effects of remifentanil. Thus, instead of describing the effects of remifentanil to increase the potency of propofol, perhaps it would be more accurate to say that the propofol is increasing the potency of the remifentanil. This is not just casuistry but points to new experiments. Exactly how does propofol amplify remifentanil? Are there special receptors or circuits involved? Could we achieve this degree of intense analgesia (i.e., the ability to ignore a surgical incision) without the concomitant loss of consciousness, as suggested by data from the isolated forearm technique?23
Name: Jamie W. Sleigh, MD.
Contribution: This author helped write the manuscript.
Attestation: Jamie W. Sleigh approved the final manuscript.
Name: Robert D. Sanders, MB ChB, PhD.
Contribution: This author helped write the manuscript.
Attestation: Robert D. Sanders approved the final manuscript.
This manuscript was handled by: Tony Gin, MD, FRCA, FANZCA.
1. Sahinovic MM, Eleveld DJ, Kalmar AF, Heeremans EH, De Smet T, Seshagiri CV, Absalom AR, Vereecke HEM, Struys MMRF. Accuracy of the Composite Variability Index as a measure of the balance between nociception and antinociception during anesthesia. Anesth Analg. 2014;119:288–301
2. Mathews DM, Clark L, Johansen J, Matute E, Seshagiri CV. Increases in electroencephalogram and electromyogram variability are associated with an increased incidence of intraoperative somatic response. Anesth Analg. 2012;114:759–70
3. Ledowski T, Tiong WS, Lee C, Wong B, Fiori T, Parker N. Analgesia nociception index: evaluation as a new parameter for acute postoperative pain. Br J Anaesth. 2013;111:627–9
4. Bergmann I, Göhner A, Crozier TA, Hesjedal B, Wiese CH, Popov AF, Bauer M, Hinz JM. Surgical pleth index-guided remifentanil administration reduces remifentanil and propofol consumption and shortens recovery times in outpatient anaesthesia. Br J Anaesth. 2013;110:622–8
5. Aho AJ, Yli-Hankala A, Lyytikäinen LP, Jäntti V. Facial muscle activity, Response Entropy, and State Entropy indices during noxious stimuli in propofol-nitrous oxide or propofol-nitrous oxide-remifentanil anaesthesia without neuromuscular block. Br J Anaesth. 2009;102:227–33
6. Liley DT, Sinclair NC, Lipping T, Heyse B, Vereecke HE, Struys MM. Propofol and remifentanil differentially modulate frontal electroencephalographic activity. Anesthesiology. 2010;113:292–304
7. Luginbühl M, Schumacher PM, Vuilleumier P, Vereecke H, Heyse B, Bouillon TW, Struys MM. Noxious stimulation response index: a novel anesthetic state index based on hypnotic-opioid interaction. Anesthesiology. 2010;112:872–80
8. Boselli E, Bouvet L, Bégou G, Dabouz R, Davidson J, Deloste JY, Rahali N, Zadam A, Allaouchiche B. Prediction of immediate postoperative pain using the analgesia/nociception index: a prospective observational study. Br J Anaesth. 2014;112:715–21
9. Chen X, Thee C, Gruenewald M, Ilies C, Höcker J, Hanss R, Steinfath M, Bein B. Correlation of surgical pleth index with stress hormones during propofol-remifentanil anaesthesia. Scientific World Journal. 2012;2012:879158
10. Ledowski T, Averhoff L, Tiong WS, Lee C. Analgesia Nociception Index (ANI) to predict intraoperative haemodynamic changes: results of a pilot investigation. Acta Anaesthesiol Scand. 2014;58:74–9
11. Ellerkmann RK, Grass A, Hoeft A, Soehle M. The response of the composite variability index to a standardized noxious stimulus during propofol-remifentanil anesthesia. Anesth Analg. 2013;116:580–8
12. Bouillon TW, Bruhn J, Radulescu L, Andresen C, Shafer TJ, Cohane C, Shafer SL. Pharmacodynamic interaction between propofol and remifentanil regarding hypnosis, tolerance of laryngoscopy, bispectral index, and electroencephalographic approximate entropy. Anesthesiology. 2004;100:1353–72
13. Monti MM, Lutkenhoff ES, Rubinov M, Boveroux P, Vanhaudenhuyse A, Gosseries O, Bruno MA, Noirhomme Q, Boly M, Laureys S. Dynamic change of global and local information processing in propofol-induced loss and recovery of consciousness. PLoS Comput Biol. 2013;9:e1003271
14. Wagner KJ, Sprenger T, Kochs EF, Tölle TR, Valet M, Willoch F. Imaging human cerebral pain modulation by dose-dependent opioid analgesia: a positron emission tomography activation study using remifentanil. Anesthesiology. 2007;106:548–56
15. Wanigasekera V, Lee MC, Rogers R, Kong Y, Leknes S, Andersson J, Tracey I. Baseline reward circuitry activity and trait reward responsiveness predict expression of opioid analgesia in healthy subjects. Proc Natl Acad Sci U S A. 2012;109:17705–10
16. Lee JJ, Hahm ET, Min BI, Han SH, Cho JJ, Cho YW. Roles of protein kinase A and C in the opioid potentiation of the GABAA response in rat periaqueductal gray neuron. Neuropharmacology. 2003;44:573–83
17. Xiao C, Zhou C, Atlas G, Delphin E, Ye JH. Labetalol facilitates GABAergic transmission to rat periaqueductal gray neurons via antagonizing beta1-adrenergic receptors—a possible mechanism underlying labetalol-induced analgesia. Brain Res. 2008;1198:34–43
18. Bingel U, Wanigasekera V, Wiech K, Ni Mhuircheartaigh R, Lee MC, Ploner M, Tracey I. The effect of treatment expectation on drug efficacy: imaging the analgesic benefit of the opioid remifentanil. Sci Transl Med. 2011;3:70ra14
19. Liu X, Pillay S, Li R, Vizuete JA, Pechman KR, Schmainda KM, Hudetz AG. Multiphasic modification of intrinsic functional connectivity of the rat brain during increasing levels of propofol. Neuroimage. 2013;83:581–92
20. Li KY, Xiao C, Xiong M, Delphin E, Ye JH. Nanomolar propofol stimulates glutamate transmission to dopamine neurons: a possible mechanism of abuse potential? J Pharmacol Exp Ther. 2008;325:165–74
21. Långsjö JW, Alkire MT, Kaskinoro K, Hayama H, Maksimow A, Kaisti KK, Aalto S, Aantaa R, Jääskeläinen SK, Revonsuo A, Scheinin H. Returning from oblivion: imaging the neural core of consciousness. J Neurosci. 2012;32:4935–43
22. Gili T, Saxena N, Diukova A, Murphy K, Hall JE, Wise RG. The thalamus and brainstem act as key hubs in alterations of human brain network connectivity induced by mild propofol sedation. J Neurosci. 2013;33:4024–31
23. Sanders RD, Tononi G, Laureys S, Sleigh JW. Unresponsiveness ≠ unconsciousness. Anesthesiology. 2012;116:946–59