Simulation of residual sedation effect of remimazolam: pharmacokinetic–pharmacodynamic simulation can be an additional standard anesthesia monitoring method

Monitoring the sedation level during general anesthesia is important to avoid intraoperative awareness and recall or overdose of anesthetics. For that purpose, along with the traditional observation of autonomic responses, using processed electroencephalogram monitors, including bispectral index monitors, has become the standard recently. However, this method can only estimate the depth of anesthesia during measurements. Particularly, in the case of overdose, even if the sedation level seems adequate or slightly deep, potential drug accumulation can cause delayed recovery from anesthesia; therefore, predicting the potential anesthetic effects by estimating the effect-site concentration of anesthetics and drug effect using pharmacokinetic–pharmacodynamic (PK–PD) simulations is necessary. Anesthesia practitioners use many standalone applications (e.g., TIVA trainer, EuroSIVA, Netherlands) and anesthesia information management systems with similar functionality.

Patient and equipment monitoring is used to titrate the administration of anesthetics to detect physiological perturbations, allow interventions before the patient experiences harmful effects, and detect and rectify equipment malfunction [1]. Additionally, the term “monitoring” is defined as the observation of a patient by a physician and analysis of the quality of sedation or anesthesia over a period [2]. Given the intent of the aforementioned definition, although the standard monitoring procedure during anesthesia (e.g., continuous evaluation of the patient’s oxygenation, ventilation, circulation, and temperature) [3] excludes it, PK–PD simulations can be an additional monitoring method.

Recently, in the Journal of Anesthesia, Morimoto et al. [4] have conducted a randomized controlled trial to evaluate the utility of SmartPilot View (SPV) (Draeger, Lübeck, Germany), a PK–PD simulator. SPV automatically records the administrations of anesthetics from the anesthesia workstation and shows the estimated effect-site concentrations and PD interaction between sedative and analgesic drugs as isobolograms. The authors have compared the recovery time in SPV-guided general anesthesia with that in usual practice in patients with desflurane general anesthesia. SPV-guided anesthesia enabled faster recovery of orientation (451 ± 100 s in the control group and 316 ± 57 s in the SPV group). Several similar clinical studies have used PK–PD simulation systems [5,6,7,8]. As these studies have examined the effects of reduced anesthetic use and shortened recovery time as outcomes, the use of PK–PD simulation systems could prevent delayed recovery due to drug accumulation from the clinical viewpoint.

Recently, anesthetics were expected to have characteristics that make their effects easily adjustable, as desflurane does for inhalation anesthetics. In intravenous anesthetics, this attribute is increasingly achieved using the soft drug approach, in which novel active compounds are specifically designed to be susceptible to rapid biotransformation to inactive metabolites [9]. For example, nonspecific esterases distributed throughout the body rapidly metabolize remifentanil. Carboxylesterases rapidly metabolize Remimazolam in the liver. These features would reduce the risk of accumulation. Then, the question arises whether the importance of PK–PD simulation will diminish as such drugs are used increasingly. As shown by Morimoto et al. above, the difference in recovery time between the groups using desflurane and remifentanil was statistically significant but not extremely large clinically.

Remimazolam, launched in 2020 [10], is a short-acting benzodiazepine anesthetic; however, according to data from phase IIb/III trials, it takes longer time to extubation than propofol, which is the present standard drug for total intravenous anesthesia [11]. Japanese anesthesiologists who are accustomed to rapid awakening after using propofol target-controlled infusion or desflurane may prefer administering flumazenil, a specific antagonist of benzodiazepines, rather than waiting for spontaneous complete recovery of consciousness after the end of remimazolam administration. Regarding the use of flumazenil, Yamamoto et al. have reported a case of re-sleeping after the reversal of remimazolam in the Journal of Anesthesia [12,13,14]. A 62-year-old female patient (152.4 cm, 57.9 kg) became drowsy again in the ward 45 min after antagonizing remimazolam with flumazenil, despite following the instructions in the package insert (i.e., 12 mg/kg/h as induction, followed by 1 mg/kg/h for maintenance). The authors have emphasized that the sedative effect of remimazolam may reappear as the blood concentration of flumazenil decreases, as the package insert states that the duration of action of remimazolam is similar to that of flumazenil.

I want to consider this phenomenon using PK–PD simulations. The context-sensitive half-time (i.e., the time required for plasma drug concentrations to decrease by 50% after discontinuation of continuous administration), which is often mentioned as a measure of quick recovery from anesthesia, is simulated using Schüttler’s parameter set for remimazolam [15] (Fig. 1, curve a). Even after 180 min of continuous administration, the plasma concentration of remimazolam is halved in only 4.9 min, which may seemingly result in a quick awakening; however, the effect-site concentration, not the plasma concentration, better reflects the clinical effects of intravenous anesthetics. The context-sensitive decrement time (CSDT) representing the time required for effect-site concentrations to decrease was also simulated (Fig. 1, curves b and c). The 50% CSDT is 11 min, but the 80% CSDT is as long as 44 min. In other words, 44 min after the end of continuous administration of remimazolam, its effect-site concentration is expected to decrease by ~ 80%.

Fig. 1
figure1

Context-sensitive half-time and context-sensitive decrement time. The vertical axis represents the time required to reach the desired remimazolam concentrations (a blood concentration halved; b effect-site concentration decreased by 50%; c effect-site concentration decreased by 80%). The horizontal axis represents the infusion duration of remimazolam.

Alternatively, since there are no detailed PK–PD data on the loss of the effect of flumazenil administered as an antagonist of remimazolam, previous data using other drugs will be referred to in this editorial. According to the guidelines by the Japan Society of Anesthesiologists, the half-life of flumazenil is short, and the duration of the effect after a single dose is 15–140 min [16]. Zhi et al. [17] have conducted a simulation using PK-PD parameters from a study in which flumazenil was administered during the steady-state of midazolam plasma concentration. They have revealed that immediately after the administration of 0.6-mg flumazenil, the patient’s consciousness recovers to a level near completely alert, but after ~ 35 min, it again falls below the level of awake. Considering the aforementioned information, it can be roughly assumed that most of the effects of flumazenil can disappear in 44 min. Now, at the end of 180-min remimazolam administration, flumazenil is administered, and 44 min after its effect wears off, the remimazolam effect-site concentration decreases from 0.8 to 0.2 µg/mL (Fig. 2). However, at this time, PD simulation using the Schüttler model reveals the probability of the patient’s Modified Observer’s Assessment of Alertness and Sedation Score being ≤ 1 (i.e., equal or deeper than the level where a subject responds only after painful trapezius squeeze) remains 1% (Fig. 3). Additionally, aging causes changes in PK and PD of remimazolam [18, 19], and the residual effects of remimazolam may be greater than that predicted by the Schüttler model constructed using data from younger volunteers. Thus, the effects of remimazolam could remain after the antagonistic effect of flumazenil disappears because flumazenil’s action is only antagonistic inhibition. Furthermore, Chen et al. have shown that either flumazenil or normal saline administrations did not differ in the concentration-time curves of remimazolam [20] (i.e., remimazolam does not disappear from the blood by reversal).

Fig. 2
figure2

Time courses of remimazolam effect-site concentrations (black curve, corresponding to the left Y-axis) and probability of patient’s modified observer’s assessment of alertness and sedation (MOAA/S) score being ≤ 1 (i.e., equal or deeper than the level where a subject responds only after painful trapezius squeeze) (gray curve, corresponding to the right Y-axis). a Flumazenil administration, b loss of flumazenil effect

Fig. 3
figure3

The probability of a patient’s modified observer’s assessment of alertness and sedation (MOAA/S) score being ≤ 1 (i.e., equal or deeper than the level where a subject responds only after painful trapezius squeeze). The inset graph shows the probability at effect-site remimazolam concentrations in the lower range

These considerations may be challenging by simply comparing pharmacokinetic parameter values, such as half-life, listed in the drug package insert. Meanwhile, PK–PD simulations, as shown in this editorial, can help predict the future anesthetic effects even of soft drugs, such as remimazolam. Presently, several PK or PK–PD models have been published for remimazolam [15, 18, 19, 21]; however, only a few models have a structure simple enough to be easily implemented in current simulators and to predict drug effects. Thus, more PK–PD clinical studies according to current clinical practice, such as flumazenil administration after remimazolam administration, are needed to increase the number of available PK–PD models; thus, the utility of PK–PD simulation is further recognized to become an additional standard monitoring procedure.

References

  1. 1.

    Iohom G (2021) Monitoring during anesthesia. https://www.uptodate.com/contents/monitoring-during-anesthesia. Accessed 6 Jun 2021

  2. 2.

    Manohar M, Gupta B, Gupta L. Closed-loop monitoring by anesthesiologists-a comprehensive approach to patient monitoring during anesthesia. Korean J Anesthesiol. 2018;71:417–8.

    Article  Google Scholar 

  3. 3.

    Committee on Standards and Practice Parameters (2020) Standards for basic anesthetic monitoring. https://www.asahq.org/standards-andguidelines/standards-for-basic-anesthetic-monitoring. Accessed 6 Jun 2021

  4. 4.

    Morimoto Y, Shiramoto H, Yoshimura M. The usefulness of smart pilot view for fast recovery from desflurane general anesthesia. J Anesth. 2021;35:239–45.

    Article  Google Scholar 

  5. 5.

    Cirillo V, Zito Marinosci G, De Robertis E, Iacono C, Romano GM, Desantis O, Piazza O, Servillo G, Tufano R. Navigator® and SmartPilot® view are helpful in guiding anesthesia and reducing anesthetic drug dosing. Minerva Anestesiol. 2015;81:1163–9.

    CAS  PubMed  Google Scholar 

  6. 6.

    Leblanc D, Conte M, Masson G, Richard F, Jeanneteau A, Bouhours G, Chretien JM, Rony L, Rineau E, Lasocki S. SmartPilot® view-guided anaesthesia improves postoperative outcomes in hip fracture surgery: a randomized blinded controlled study. Br J Anaesth. 2017;119:1022–9.

    CAS  Article  Google Scholar 

  7. 7.

    Mai S, Ami S, Takayuki K. Complementary use of effect site-target controlled infusion and SmartPilot view for anesthetic management in semi-awake craniotomy near BIS 85. J Neurosurg Anesthesiol. 2018;30:78–9.

    Article  Google Scholar 

  8. 8.

    Obara S, Syroid N, Ogura T, Pace NL, Johnson KB, Albert R, Agutter J, Stuart AR, Egan TD. A pharmacokinetic-pharmacodynamic real-time display may change anesthesiologists’ behavior. J Clin Monit Comput. 2021;35:547–56.

    Article  Google Scholar 

  9. 9.

    Birgenheier NM, Stuart AR, Egan TD. Soft drugs in anesthesia: remifentanil as prototype to modern anesthetic drug development. Curr Opin Anaesthesiol. 2020;33:499–505.

    Article  Google Scholar 

  10. 10.

    Masui K. Remimazolam besilate, a benzodiazepine, has been approved for general anesthesia!! J Anesth. 2020;34:479–82.

    Article  Google Scholar 

  11. 11.

    Doi M, Morita K, Takeda J, Sakamoto A, Yamakage M, Suzuki T. Efficacy and safety of remimazolam versus propofol for general anesthesia: a multicenter, single-blind, randomized, parallel-group, phase IIb/III trial. J Anesth. 2020;34:543–53.

    Article  Google Scholar 

  12. 12.

    Yamamoto T, Kurabe M, Kamiya Y. Re-sleeping after reversal of remimazolam by flumazenil. J Anesth. 2021;35:322.

    Article  Google Scholar 

  13. 13.

    Godai K. What are mechanisms of re-sedation caused by remimazolam? J Anesth. 2021;35:466.

    Article  Google Scholar 

  14. 14.

    Yamamoto T, Kurabe M, Kamiya Y. A mechanism of re-sedation caused by remimazolam. J Anesth. 2021;35:467–8.

    Article  Google Scholar 

  15. 15.

    Schüttler J, Eisenried A, Lerch M, Fechner J, Jeleazcov C, Ihmsen H. Pharmacokinetics and pharmacodynamics of remimazolam (CNS 7056) after continuous infusion in healthy male volunteers: part I. pharmacokinetics and clinical pharmacodynamics. Anesthesiology. 2020;132:636–51.

    Article  Google Scholar 

  16. 16.

    Japanese Society of Anesthesiologists (2021) Guidelines for the usage of anesthetic drugs and associated drugs; 3rd edn (in Japanese). https://anesth.or.jp/files/pdf/hypnosis_sedative_20190905.pdf. Accessed 6 Jun 2021

  17. 17.

    Zhi J, Massarella JW, Melia AT, Teller SB, Schmitt-Muskus J, Crews T, Oldfield N, Erb RJ, Leese PT, Patel IH. The pharmacokinetic-pharmacodynamic (digit symbol substitution test) relationship of flumazenil in a midazolam steady-state model in healthy volunteers. Clin Pharmacol Ther. 1994;56:530–6.

    CAS  Article  Google Scholar 

  18. 18.

    Zhou J, Curd L, Lohmer LL, Ossig J, Schippers F, Stoehr T, Schmith V. Population pharmacokinetics of remimazolam in procedural sedation with nonhomogeneously mixed arterial and venous concentrations. Clin Transl Sci. 2021;14:326–34.

    CAS  Article  Google Scholar 

  19. 19.

    Zhou J, Curd L, Lohmer LRL, Delpratt N, Ossig J, Schippers F, Stoehr T, Schmith VD. A population pharmacodynamic markov mixed-effects model for determining remimazolam-induced sedation when co-administered with fentanyl in procedural sedation. Clin Transl Sci. 2021. https://doi.org/10.1111/cts.13023.

    Article  PubMed  Google Scholar 

  20. 20.

    Chen X, Sang N, Song K, Zhong W, Wang H, Jiang J, Huang Y, Hu P. Psychomotor recovery following remimazolam-induced sedation and the effectiveness of flumazenil as an antidote. Clin Ther. 2020;42:614–24.

    CAS  Article  Google Scholar 

  21. 21.

    Doi M. Remimazolam. JJSCA. 2014;34:860–6 (Japanese manuscript with English abstract).

    Article  Google Scholar 

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Correspondence to Shinju Obara.

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Obara, S. Simulation of residual sedation effect of remimazolam: pharmacokinetic–pharmacodynamic simulation can be an additional standard anesthesia monitoring method. J Anesth (2021). https://doi.org/10.1007/s00540-021-02963-3

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Keywords

  • Remimazolam
  • Pharmacokinetics
  • Pharamacodynamics
  • Simulation
  • Flumazenil