Hyperventilation delays clinical induction of desflurane

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1 Anesth Pain Med 2010; 5: 216~221 Research Article Hyperventilation delays clinical induction of desflurane Department of Anesthesiology and Pain Medicine, Dongguk University Ilsan Hospital, Ilsan, *St. Maria s Hospital, Uijeongbu, Catholic University, Uijeongbu, Korea Younsuk Lee, Junyong In, Kyoung Ok Kim, Dong-Il Yun, Jeoung Hyuk Lee*, Hun Cho, Jun Gwon Choi, Seunghyun Chung, and Eun-Jung Jang Background: Ventilation is a major determinant of the alveolar concentration of inhaled anesthetics. Hyperventilation accelerates the equilibration of anesthetic in the lungs, but decelerates it in the brain. We evaluated this phenomenon for desflurane. Methods: Twenty healthy subjects were enrolled after IRB approval. End-tidal concentrations of desflurane (P.DESF) were recorded during 10 minutes of mask induction with 8% desflurane. P.DESF was modeled with time and end-tidal concentrations of CO 2 (P.ETCO 2) using a two-exponential pharmacokinetic equation. Bispectral index (BIS) values were also measured to find out the component reflecting the cerebral concentration of desflurane. Results: During induction, the rise of P.DESF could be separated into two components: early and late rises. Individual BIS values showed a higher correlation with the late component of P.DESF (P = 0.000). P.ETCO 2 had two different effects on the rise of P.DESF. Conclusions: Hyperventilation hastened the early rise and delayed the late rise of P.DESF (P = 0.00, P = 0.00). Hyperventilation should be avoided to obtain rapid anesthesia induction with desflurane. (Anesth Pain Med 2010; 5: ) Key Words: Desflurane, Inhalation anesthesia, Nonlinear model, Pharmacokinetics, Ventilation. INTRODUCTION During induction of anesthesia, ventilation is a major factor that governs the pulmonary inhaled anesthetic concentration. Ventilation introduces anesthetics into the lungs whereas uptake removes them. The relationship between input and removal determines the alveolar concentration of inhaled anesthetics. While hyperventilation increases the alveolar concentration and resultant low arterial CO 2 concentration also reduces blood Received: April 16, Revised: May 8, Accepted: June 8, Corresponding author: Younsuk Lee, M.D., Department of Anesthesiology and Pain Medicine, Dongguk University Ilsan Hospital, Siksa-dong, Ilsandong-gu, Goyang , Korea. Tel: , Fax: , ylee@dongguk.ac.kr flow to the brain and can delay the rise of brain anesthetic concentration. On anesthesia induction, net effect of hyperventilation has been reported for classical anesthetics, but not for modern anesthetics [1]. The balance between these opposite effects differs among anesthetics of different solubilities [2]. In highly soluble anesthetics, the considerable rise in alveolar anesthetic concentration induced by hyperventilation cannot be offset by the reduced cerebral blood flow. But, in less soluble anesthetics, the effect of a modest increase in alveolar concentration is more than offset by the reduction of cerebral blood flow [1]. In desflurane of our interest, the effect of hyperventilation on the speed of anesthesia induction has not been calculated nor observed before. To prove the effect of ventilation on the rise of alveolar concentration of desflurane, we postulated nonlinear statistical models that predicted the rise of end-tidal concentration of desflurane during induction, which would replace the alveolar concentration. With our model, we separated the rise of end-tidal concentration of desflurane into two components, which would make it easier to interpret the ventilation effect on the rise of desflurane concentration. MATERIALS AND METHODS Twenty ASA PS class I-II subjects undergoing scheduled surgery were enrolled after obtaining approval in institutional ethics board for clinical research (Table 1). Owing to lack of related study, sample size requirement was estimated indirectly with the variability of cerebral blood flow by the variability of arterial carbon dioxide published in Kety and Schmidt [3]. When varied between 43 and 52 mmhg, cerebral blood flow varied between 53 and 93 ml/100 gm/min, whose correlation coefficient was We wished to detect an effect size of r = 0.61 at alpha = 0.05, and to estimate the sample 216

2 Younsuk Lee, et al:hyperventilation and desflurane induction 217 Table 1. Subjects Characteristics N 20 Age (yr) 35 ± 10 Gender (F/M) 13/7 Body weight (kg) 62 ± 12 Height (cm) 164 ± 8 Mean arterial pressure (mmhg) 91 ± 10 Heart rate (beat/min) 72 ± 17 Values are mean ± SD except of N and gender. Mean arterial pressure and heart rate were measured before anesthesia induction. N: sample size. DATA ANALYSIS Individual changes in P DESF curves and the average curve were fitted to a series of exponential models limited to single and two-exponential models. Exponential curves were fitted as the following equations: First, by single exponential fit, size requirement in a power of According to the Cohen s [4] sample size table (n to detect r by t-test), the minimum sample size was estimated at 15. Although we posited that the variability of the speed of uptake of desflurane must inherit the variability of cerebral blood flow, the minimum sample size was considered as 20 assuming some inflation of variability of the speed of uptake of desflurane. Subjects were informed and consented. No premedicant was given. Anesthesia machine (S/5 Avance Carestation R, Datex- Ohmeda, Helsinki, Finland) and semi-closed circuit were prefilled with 8.0% of desflurane. End-tidal concentration of desflurane (P DESF) and CO 2 ( ) were measured with a detachable airway module in anesthesia machine. Only one airway module was used for all subjects to minimize the inter-device bias. A BIS sensor was attached to the subject in conjunction with a BIS XP monitor (BIS TM Monitor, Model A-2000 TM, Aspect Medical Systems, Inc., Newton, MA, USA). Anesthesia was induced with 1.5 mg/kg of propofol. After confirmation of adequate mask ventilation with bag-valve device, muscle relaxation was provided with 0.1 mg/kg of vecuronium. Desflurane-prefilled anesthesia circuit was connected to the mask, and tight seal between the mask and the face of the subject was secured with two hands of an experienced anesthesiologist unaware of the purpose of this study. Dial concentration of 8.0% desflurane was retained throughout the study procedure. Volume-controlled mechanical ventilation was applied with 9 ml/kg of tidal volume and 10 breaths/min of respiratory rate. Oxygen flow was set at 6 L/min. T0 was defined by the connection of the anesthesia circuit. Total eleven measurements were taken at 0.0, 0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 4.0, 5.0, 7.5, and 10.0 minutes. Measurements included P DESF and. Pulse oximetry was kept at %, and mean arterial pressure between mmhg. where A is asymptote and lrc was log rate constant. Second, curves were fitted also by two-exponential fit, (Equation 1) where A 1 and A 2 were asymptotes for the early and late component respectively, and lrc 1 and lrc 2 were log rate constants, respectively. Absolute condition was lrc 1 > lrc 2 in the equation. The two-exponential fit represents the threecompartment pharmacokinetic model, which contains central, early (having high rate constant), and late (having low rate constant) compartment. The asymptotes reflect the final concentrations of each component. In dynamic modeling of our use, because the volume of distribution could not be estimated, it was eligible to interpret the relative values of the asymptotes, whose summation was P DESF rather than the absolute values. We have, in a loose sense, accepted a term component instead of compartment. Between two models, the better one was chosen, which was defined by the principles of parsimony. Three different fitted values were generated using the (Equation 1), which were individually fitted P DESF, fitted, and. To find out which component corresponded to concentration in brain tissue, the BIS (bispectral index) values were linearly regressed by three variables; they included the individually observed P DESF, early component values, and late component values. Third, to elucidate the ventilation-effect, the values of were combined linearly with the parameters of the individually fitted curves. The -combination was accepted if the combination yielded either a statistically significant difference or a low Akaike s information criteria (AIC). Intra-class correlation (ρ) was estimated with variance components of the random effects of the model parameters.

3 218 Anesth Pain Med Vol. 5, No. 3, 2010 Table 2. Summary of Parameters in Pharmacokinetic Models Single-exponential model Two-exponential model not including -effect Parameters Estimates P Parameters Estimates P A (5.905, 6.195) 0.00 A (3.776, 4.076) 0.00 lrc (0.206, 0.393) 0.00 lrc (1.082, 1.456) 0.00 A (2.725, 3.140) 0.00 lrc ( 1.046, 1.464) 0.00 AIC 249 AIC 99 Estimates are means (95% confidence intervals). P = 0.00 of analysis of variances between two models. In single-exponential model, A = asymptote, and lrc = log rate constant. In two-exponential model, A 1: asymptote in early component, lrc 1: log rate constant in early component, A 2: asymptote in late component, and lrc 2: log rate constant in late component. P DESF: end-tidal concentration of desflurane (%), AIC: Akaike s information criteria., where the was a summation of standard deviation for all variance components between-subject, and the, a standard deviation within-subject, a.k.a. residuals. The model parameters were presented as means (95% confidence intervals). The 95% confidence intervals were estimated with mean estimates ± standard error t Residuals for population were presented as means ± standard deviations. Normality assumptions were tested using Shapiro- Wilks test for the residuals and random effects of the model parameters. R: A Language and Environment for Statistical Computing (Version , R Development Core Team. R Foundation for Statistical Computing, Vienna, Austria) was used for statistical analyses. An nlme package (Linear and Nonlinear Mixed Effects Models. Version Developed by Jose Pinheiro, Douglas Bates, Saikat DebRoy, Deepayan Sarkar, and the R Core team), was used as well. Statistical difference was accepted when P < 0.05, or low AIC. Fig. 1. Individual and average curves for rise of the concentrations of early (P early) and late (P late) components. Individual (dotted) and average (thick dotted) curves for P early show smaller variations between individuals, while individual (thin solid) and average (thick solid) curves for late rise of P late show larger variations between individuals. P early: fitted concentrations of desflurane (%) in early component, P late: fitted concentrations of desflurane (%) in late component. RESULTS During mask induction, P DESF increased to 6.7 ± 0.3% and ranged from 6.1 to 7.3%. The values of were averaged at 37 ± 3 mmhg and ranged from 23 to 45 mmhg. Temporal changes in P DESF was well fitted to two-exponential pharmacokinetic model. By comparing with single-exponential one, the two-exponential model showed a better fit (P = 0.00) (Table 2). Individual BIS values were correlated better with the individually fitted late component values (AIC = 815, P = 0.00, R 2 = 0.21) than with the early component values (AIC = 834, P = 0.00, R 2 = 0.12) or with the observed P DESF (AIC = 820, P = 0.00, R 2 = 0.19). Individual variations of P DESF in the early component looked smaller than in the late component (Fig. 1). By rough exploration, all parameters seemed to be linearly dependent on. Inferential statistics were not yet applied because these values are the average values within individual (Fig. 2). With

4 Younsuk Lee, et al:hyperventilation and desflurane induction 219 Fig. 2. Correlations between random effects of individual model parameters and. Increased decreases all of the random effects except of A 2. In (Equation 1), A 1 and A 2 are asymptotes for the early and late component respectively, and lrc 1 and lrc 2 are log rate constants, respectively. : end-tidal concentration of CO 2 (mmhg). Table 3. Summary of Parameters of the Final Model including - effect Two-exponential model including -effect Parameters Estimates P A (4.282, 4.768) 0.00 A ( 0.142, 0.089) 0.00 lrc (0.921, 1.162) 0.00 lrc ( 0.051, 0.013) 0.00 A (2.290, 2.844) 0.00 A (0.081, 0.195) 0.00 lrc ( 1.806, 1.524) 0.00 AIC 218 Estimates are means (95% confidence intervals). A 1: asymptote in early component, lrc 1: log rate constant in early component, A 2: asymptote in late component, and lrc 2: log rate constant in late component. P DESF: end-tidal concentration of desflurane (%), : end-tidal concentration of CO 2 (mmhg), AIC: Akaike s information criteria. Variable time is in minute.

5 220 Anesth Pain Med Vol. 5, No. 3, 2010 Fig. 3. Contour plot of population prediction for P DESF with the changes in time and. Predicted values of P DESF are presented over the contour lines obtained from the final model (Table 3). Increased ventilation accelerates the rise of P DESF earlier, and later decelerates it. P DESF = end-tidal concentration of desflurane (%), = end-tidal concentration of CO 2 (mmhg). assumption that the variations of P EDSF depended on the variations of, the values were combined linearly to the parameters one by one. -effect on lrc 2 was excluded in the final model because its selection yielded statistical insignificance (P = 0.79) and a higher AIC ( 216 from 218). For easy interpretation of the final model, the values were centered at 37 mmhg that was the average value in the range of our study (Table 3). Therefore, decrease in raised both asymptote and rate constant of the early component, which should accelerate the time to equilibrate the desflurane concentration in the early component. As expected from the rough exploration (Fig. 2), there was a conflicting -effect on A 2, which can oppose the acceleration-effect on the rise of P DESF. Population prediction with arbitrary values (25 45 mmhg) illustrated the overall -effect (Fig. 3). While hyperventilation accelerates the early rise of P DESF until the P DESF reaches at over 6%, hyperventilation also decelerates the late rise of P DESF (Fig. 3). Contour curve for P DESF tells that the -effect on the late component becomes dominant over acceleration of the early component, and thereby hyperventilation can make the late increase of P DESF slower. In = 37 mmhg, the final average model can be expressed as,. Residuals for population were small ( ± 0.348), and Fig. 4. Residuals for population (%). The residuals are distributed normally (P = 0.08) and independently to the fitted P DESF. P DESF = end-tidal concentration of desflurane (%). distributed normally (P = 0.08) and independently to the fitted P DESF (Fig. 4). Random effects of the model parameters were small and distributed normally (P = 0.95, 0.62, 0.99, and 0.10 for A 1, lrc 1, A 2, and lrc 2). Intra-class correlation (ρ) was estimated at (= 1.380/1.447). DISCUSSION Our results will interest readers in two aspects. One is that during induction the two-exponential non-steady state pharmacokinetic modeling can separate the increase in P DESF of desflurane into the two components. The other is that the ventilation-effect in desflurane induction is fairly compatible to the classical concept that hyperventilation can decelerate the increase in the alveolar concentration of poorly soluble anesthetics during induction [1,5]. It has been confirmed mathematically for nitrous oxide and cyclopropane, but neither for modern anesthetics such as desflurane, nor in clinical condition. In our model, the model parameters could be comparable hardly with the well-founded pharmacokinetic indices of desflurane. But, we can draw following conjectures. The rate constant was in the early component, which would represent the washin of desflurane in the lungs. Basically, rate constant to saturate lungs is proportional to ventilation and inversely proportional to lung volume that can be calculated with / FRC ( = alveolar ventilation, FRC = functional residual capacity), in normal adults, which is accepted as [6]. The reason why our estimate of k 1 was higher than normal value is that our default in the final

6 Younsuk Lee, et al:hyperventilation and desflurane induction 221 equation was assumed to be 37 mmhg. Our was which was lower than rate constant for blood or for tissues of vessel-rich group including the brain [7,8]. Although desflurane is a potent cerebral vasodilator, direct or indirect measures of cerebral blood flow was reported to respond well to ventilation even in MAC of desflurane in dog and human [9,10]. So, decreased cerebral blood flow was supposed in the final equation, and the equilibration of desflurane in the brain should be delayed. BIS values were well correlated to the curve of the late component. They were the clues for our conjecture that the late component corresponded to the desflurane concentration in brain. Hyperventilation also has the same impact on recovery from inhalation anesthesia. It was partly supported by the study of Sakata et al. [11]. They reported that hypercapnia coincident with hyperventilation promoted rapid awakening from desflurane anesthesia. Limitations of our approach also should be recognized. We applied a constant ventilation per body weight, but the observed showed the large variations inter-individually. might hold a time gap to reflect the given ventilation, as well. It was inevitable that would underestimate the amount of ventilation in earlier stage of the measurements. We failed to find out a better way to solve these problems. In the present design, as the values were merely observable measurements, any other discrete statistical test based on grouping could be inapplicable except the nonlinear modeling of our use. We expect that other study design to allocate different minute ventilations for groups will discriminate the effect of ventilation more clearly. Another limitation was that, in spite of the statistical significance (P = 0.00), the regression coefficient was too low (R 2 = 0.21) to fit the late component to the BIS values. It was probably because propofol also influenced the BIS, and a nonlinear curve will explain the BIS values with anesthetic concentration [12]. Use of propofol was obligatory for a good acceptance to positive pressure ventilation. Even though the BIS values were nonlinearly fitted to the desflurane concentration in the late component better than linearly, for simplicity, we excluded further analysis on BIS. The ventilation-effect on the rise of end-tidal concentration of desflurane was conceptualized in clinical condition. We found that the two-exponential model can separate the ventilation-effect into the early and late components during desflurane induction, of which the BIS values are correlated better with the late component. Hyperventilation hastens the rise of end-tidal desflurane concentration earlier, but later delays it. The late component corresponds to the brain concentration and our results indicate that hyperventilation delays the desflurane induction. REFERENCES 1. Munson ES, Bowers DL. Effects of hyperventilation on the rate of cerebral anesthetic equilibration. Calculations using a mathematical model. Anesthesiology 1967; 28: Yamamura H, Wakasugi B, Okuma Y, Maki K. The Effects of Ventilation on the Absorption and Elimination of Inhalation Anaesthetics. Anaesthesia 1963; 18: Kety SS, Schmidt CF. The effects of altered arterial tensions of carbon dioxide and oxygen on cerebral blood flow and cerebral oxygen consumption of normal young men. J Clin Invest 1948; 27: Cohen J. Statistical power analysis for the behavioral sciencies. 2nd ed. Hillsdale, Lawrence Erlbaum Associates. 1988, p Eger EI 2nd. Anesthetic uptake and action. Baltimore, Waverly Press, Inc. 1974, pp Eger EI 2nd, Shafer SL. Tutorial: context-sensitive decrement times for inhaled anesthetics. Anesth Analg 2005; 101: Yasuda N, Lockhart SH, Eger EI 2nd, Weiskopf RB, Johnson BH, Freire BA, et al. Kinetics of desflurane, isoflurane, and halothane in humans. Anesthesiology 1991; 74: Bailey JM. Context-sensitive half-times and other decrement times of inhaled anesthetics. Anesth Analg 1997; 85: Lutz LJ, Milde JH, Milde LN. The response of the canine cerebral circulation to hyperventilation during anesthesia with desflurane. Anesthesiology 1991; 74: Lee Y, Lee JH, Yoon DI, Kim KO, Chung S, In J, et al. Hypocapnia attenuates, and nitrous oxide disturbs the cerebral oximetric response to the rapid introduction of desflurane. J Korean Med Sci 2009; 24: Sakata DJ, Gopalakrishnan NA, Orr JA, White JL, Westenskow DR. Rapid recovery from sevoflurane and desflurane with hypercapnia and hyperventilation. Anesth Analg 2007; 105: Struys MM, Vereecke H, Moerman A, Jensen EW, Verhaeghen D, De Neve N, et al. Ability of the bispectral index, autoregressive modelling with exogenous input-derived auditory evoked potentials, and predicted propofol concentrations to measure patient responsiveness during anesthesia with propofol and remifentanil. Anesthesiology 2003; 99: