Free
Correspondence  |   August 2018
Pharmacokinetic Pharmacodynamic Perspective on the Detection of Signs of Neural Inertia in Humans
Author Notes
  • University of Groningen, University Medical Center Groningen, Groningen, The Netherlands, and Ghent University, Ghent, Belgium (P.J.C.). j.colin@umcg.nl
  • (Accepted for publication May 7, 2018.)
    (Accepted for publication May 7, 2018.)×
Article Information
Correspondence
Correspondence   |   August 2018
Pharmacokinetic Pharmacodynamic Perspective on the Detection of Signs of Neural Inertia in Humans
Anesthesiology 8 2018, Vol.129, 373-375. doi:10.1097/ALN.0000000000002287
Anesthesiology 8 2018, Vol.129, 373-375. doi:10.1097/ALN.0000000000002287
To the Editor:
We read with great interest the paper, “Investigation of Slow-wave Activity Saturation during Surgical Anesthesia Reveals a Signature of Neural Inertia in Humans” by Warnaby et al.1  The authors claim to have found experimental evidence for neural inertia in humans on the basis of a difference in the modeled slow-wave activity between induction and emergence from propofol anesthesia. As the authors state, until recently, neural inertia has only been observed in animals,2  and evidence was lacking on the importance of this phenomenon in humans.
In parallel to Warnaby et al., our group recently conducted a clinical study to investigate this phenomenon in healthy volunteers.3  Our analysis suggested, among other things, that the ability to detect signs of neural inertia depends on the design of the study. Inspired by the work of Warnaby et al., we would like to show how the drug titration scheme may influence the detection of neural inertia and could lead to false positive results.
In studies with anesthetic agents, effect-site target-controlled infusion is frequently used to control delivery of the drug. Effect-site target-controlled infusion systems calculate the optimal infusion regimen required to achieve the target effect-site concentration as fast as possible. These systems depend heavily on population pharmacokinetic models and their associated estimate for the rate-constant for equilibration between the plasma and effect-site concentrations. Clinical trial design is usually optimized with respect to this rate-constant for equilibration, such that pharmacodynamic endpoints are measured only after the predicted effect-site concentrations have reached a steady-state. The rate-constant for equilibration of 0.260 min–1 integrated into the Diprifusor system (AstraZeneca Ltd., United Kingdom) suggests a rapid effect-site equilibration. Presumably based on this knowledge, Warnaby et al. chose to change the target effect-site every 2 min during the induction phase of the study. For the emergence phase, the authors simply stopped the propofol infusion.
However, reported rate-constants for equilibration in the literature vary substantially. For example, for propofol-induced changes in Bispectral Index (Covidien, USA), reported rate-constants for equilibration range between 0.17 min–14  and 0.79 min–1.5  In our opinion, this uncertainty should be taken into account when designing a study; failing to do so may lead to false conclusions.
To substantiate our claim, we simulated the propofol infusion scheme used by Warnaby et al. (details with respect to the propofol infusion are found in the supplementary materials from an earlier paper from the same group6 ). Hereto, the Marsh model7  and the associated rate-constant for equilibration of 0.260 min–1 were used to calculate predicted arterial and effect-site concentrations. Predicted effect-site concentrations (Ce) were used to calculate a hypothetical drug effect according to equation 1 with a gamma (γ) and a concentration producing half-maximum effect (C50) which were 2 and 1.5 µg/ml, respectively.
Subsequently, the model in equation 1 was fitted to the simulated data for the induction and emergence phase separately to estimate the γ and C50. This process was repeated with different values for the rate-constant for equilibration. Besides the study design described by Warnaby et al., we also evaluated the drug infusion scheme that was used in our study.3 
The results of the simulations are shown in figure 1. This figure clearly shows that the C50s for induction and emergence depend on the rate-constant for equilibration. More specifically, if the wrong rate-constant for equilibration is used, the estimated C50 for induction increases, whereas that for emergence decreases. For example, in Warnaby et al., a 30% difference between estimated induction and emergence C50 is expected when the rate-constant for equilibration is 0.160 min–1, but none if it is 0.260 min–1. Thus, neural inertia is an apparent artefact of the experiment. In addition, some trial designs may be less sensitive to the rate-constant for equilibration used. For example, in our study design, this situation would only result in a 4% difference between the predicted C50s. This would likely lead to no difference between induction and emergence C50, which, in this case, is the correct conclusion.
Fig. 1.
The estimated concentration producing half-maximum effect (C50) for the induction (solid lines) and emergence phase (dashed lines) according to the rate-constant for equilibration (ke0) that was used to generate the hypothetical drug effect. The different colors show the dependence of the C50 on the ke0 for the trial design by Warnaby et al. (blue lines) and the design that was used in our study on neural inertia (red lines).
The estimated concentration producing half-maximum effect (C50) for the induction (solid lines) and emergence phase (dashed lines) according to the rate-constant for equilibration (ke0) that was used to generate the hypothetical drug effect. The different colors show the dependence of the C50 on the ke0 for the trial design by Warnaby et al. (blue lines) and the design that was used in our study on neural inertia (red lines).
Fig. 1.
The estimated concentration producing half-maximum effect (C50) for the induction (solid lines) and emergence phase (dashed lines) according to the rate-constant for equilibration (ke0) that was used to generate the hypothetical drug effect. The different colors show the dependence of the C50 on the ke0 for the trial design by Warnaby et al. (blue lines) and the design that was used in our study on neural inertia (red lines).
×
Our simulations show that data indicating the existence of neural inertia (higher estimated C50 for induction vs. emergence) may occur because of poor trial design. Given the range of rate-constants for equilibration reported in the literature, it seems pivotal to take the uncertainty associated with the rate-constant for equilibration into account when designing a study. Failing to do so will lead to false positive results. A more precise definition of neural inertia, and methodologic framework for studying this in clinical practice, is necessary to conclude whether neural inertia exists in humans and is of clinical importance.
Research Support
The Department of Anesthesiology, University Medical Center Groningen, Groningen, The Netherlands, received sponsorship from Masimo (Irvine, California) for the execution of this trial, and the additional modeling work was funded by departmental and institutional funding.
Competing Interests
Dr. Struys’s research group/department received grants and funding from The Medicines Company (Parsippany, New Jersey), Masimo (Irvine, California), Fresenius (Bad Homburg, Germany), Acacia Design (Maastricht, The Netherlands), and Medtronic (Dublin, Ireland), and honoraria from The Medicines Company, Masimo, Fresenius, Baxter (Deerfield, Illinois), Medtronic, and Demed Medical (Temse, Belgium). Dr. Struys serves as director and editorial board member of the British Journal of Anesthesia and as senior editor for Anesthesia & Analgesia. The remaining authors declare no competing interests.
Pieter J. Colin, Pharm.D., Ph.D., Merel H. Kuizenga, M.D., Hugo E. M. Vereecke, M.D., Ph.D., Michel M. R. F. Struys, M.D., Ph.D. University of Groningen, University Medical Center Groningen, Groningen, The Netherlands, and Ghent University, Ghent, Belgium (P.J.C.). j.colin@umcg.nl
References
Warnaby, CE, Sleigh, JW, Hight, D, Jbabdi, S, Tracey, I Investigation of slow-wave activity saturation during surgical anesthesia reveals a signature of neural inertia in humans. Anesthesiology 2017; 127:645–57 [Article] [PubMed]
Friedman, EB, Sun, Y, Moore, JT, Hung, HT, Meng, QC, Perera, P, Joiner, WJ, Thomas, SA, Eckenhoff, RG, Sehgal, A, Kelz, MB A conserved behavioral state barrier impedes transitions between anesthetic-induced unconsciousness and wakefulness: evidence for neural inertia. PLoS One 2010; 5:e11903 [Article] [PubMed]
Kuizenga, MH, Colin, PJ, Reyntjens, KMEM, Touw, DJ, Nalbat, H, Knotnerus, FH, Vereecke, HEM, Struys, MMRF Test of neural inertia in humans during general anaesthesia. Br J Anaesth 2018; 120:525–36 [Article] [PubMed]
Doufas, AG, Bakhshandeh, M, Bjorksten, AR, Shafer, SL, Sessler, DI Induction speed is not a determinant of propofol pharmacodynamics. Anesthesiology 2004; 101:1112–21 [Article] [PubMed]
Coppens, MJ, Eleveld, DJ, Proost, JH, Marks, LA, Van Bocxlaer, JF, Vereecke, H, Absalom, AR, Struys, MM An evaluation of using population pharmacokinetic models to estimate pharmacodynamic parameters for propofol and bispectral index in children. Anesthesiology 2011; 115:83–93 [Article] [PubMed]
Mhuircheartaigh, RN, Warnaby, C, Rogers, R, Jbabdi, S, Tracey, ISlow-wave activity saturation and thalamocortical isolation during propofol anesthesia in humans. Sci Transl Med 2013; 5(208), DOI: 10.1126/scitranslmed.3006007
Marsh, B, White, M, Morton, N, Kenny, GN Pharmacokinetic model driven infusion of propofol in children. Br J Anaesth 1991; 67:41–8 [Article] [PubMed]
Fig. 1.
The estimated concentration producing half-maximum effect (C50) for the induction (solid lines) and emergence phase (dashed lines) according to the rate-constant for equilibration (ke0) that was used to generate the hypothetical drug effect. The different colors show the dependence of the C50 on the ke0 for the trial design by Warnaby et al. (blue lines) and the design that was used in our study on neural inertia (red lines).
The estimated concentration producing half-maximum effect (C50) for the induction (solid lines) and emergence phase (dashed lines) according to the rate-constant for equilibration (ke0) that was used to generate the hypothetical drug effect. The different colors show the dependence of the C50 on the ke0 for the trial design by Warnaby et al. (blue lines) and the design that was used in our study on neural inertia (red lines).
Fig. 1.
The estimated concentration producing half-maximum effect (C50) for the induction (solid lines) and emergence phase (dashed lines) according to the rate-constant for equilibration (ke0) that was used to generate the hypothetical drug effect. The different colors show the dependence of the C50 on the ke0 for the trial design by Warnaby et al. (blue lines) and the design that was used in our study on neural inertia (red lines).
×