Fexofenadine, a Putative In Vivo P-glycoprotein Probe, Fails to Predict Clearance of the Substrate Tacrolimus in Renal Recipients.

Whether the combined use of probe drugs for CYP3A4 and P-glycoprotein can clarify the relative contribution of these proteins to pharmacokinetic variability of a dual substrate like tacrolimus has never been assessed. Seventy renal recipients underwent simultaneous 8-h pharmacokinetic profiles for tacrolimus, the CYP3A4 probe midazolam, and the putative P-glycoprotein probe fexofenadine. Patients were genotyped for polymorphisms in CYP3A5, CYP3A4, ABCB1, ABCC2 and SLCO2B1, -1B1, and 1B3. Carriers of the ABCB1 2677G>A polymorphism displayed lower fexofenadine Cmax (-66%; P = 0.012) and a trend toward higher clearance (+157%; P = 0.078). Predictors of tacrolimus clearance were CYP3A5 genotype, midazolam clearance, hematocrit, weight, and age (R2 = 0.61). Fexofenadine pharmacokinetic parameters were not predictive of tacrolimus clearance. In conclusion, fexofenadine pharmacokinetics varied considerably between renal recipients but most of this variability remained unexplained, with only minor effects of genetic polymorphisms. Fexofenadine cannot be used to assess in vivo CYP3A4-P-glycoprotein interplay in tacrolimus-treated renal recipients.

Probability to tolerate laryngoscopy and noxious stimulation response index as general indicators of the anaesthetic potency of sevoflurane, propofol, and remifentanil.

BACKGROUND: The probability to tolerate laryngoscopy (PTOL) and its derivative, the noxious stimulation response index (NSRI), have been proposed as measures of potency of a propofol-remifentanil drug combination. This study aims at developing a triple drug interaction model to estimate the combined potency of sevoflurane, propofol, and remifentanil in terms of PTOL. We compare the predictive performance of PTOL and the NSRI with various anaesthetic depth monitors. METHODS: Data from three previous studies (n=120) were pooled and reanalysed. Movement response after laryngoscopy was observed with different combinations of propofol-remifentanil, sevoflurane-propofol, and sevoflurane-remifentanil. A triple interaction model to estimate PTOL was developed. The NSRI was derived from PTOL. The ability of PTOL and the NSRI to predict observed tolerance of laryngoscopy (TOL) was compared with the following other measures: (i) effect-site concentrations of sevoflurane, propofol, and remifentanil (CeSEVO, CePROP, and CeREMI); (ii) bispectral index; (iii) two measures of spectral entropy; (iv) composite variability index; and (v) surgical pleth index. RESULTS: Sevoflurane and propofol interact additively, whereas remifentanil interacts in a strongly synergistic manner. The effect-site concentrations of sevoflurane and propofol at a PTOL of 50% (Ce50; se) were 2.59 (0.13) vol % and 7.58 (0.49) µg ml(-1). A CeREMI of 1.36 (0.15) ng ml(-1) reduced the Ce50 of sevoflurane and propofol by 50%. The common slope factor was 5.22 (0.52). The PTOL and NSRI predict the movement response to laryngoscopy best. CONCLUSIONS: The triple interaction model estimates the potency of any combination of sevoflurane, propofol, and remifentanil expressed as either PTOL or NSRI.

Compartmental pharmacokinetics of nefopam during mild hypothermia.

BACKGROUND: Nefopam is a non-opioid, non-steroidal, centrally acting analgesic which has an opioid-sparing effect. It also reduces the threshold (triggering core temperature) for shivering without causing sedation or respiratory depression. The drug is therefore useful as both an analgesic and to facilitate induction of therapeutic hypothermia. However, compartmental pharmacokinetics during hypothermia are lacking for nefopam. METHODS: We conducted a prospective, randomized, blinded study in eight volunteers. On two different occasions, one of two nefopam concentrations was administered and more than 30 arterial blood samples were gathered during 12 h. Plasma concentrations were determined using gas chromatography/mass spectrometry to investigate the pharmacokinetics of nefopam with non-linear mixed-effect modelling. RESULTS: A two-compartment mammillary model with moderate inter-individual variability and inter-occasional variability independent of covariates was found to best describe the data [mean (SE): V(1)=24.13 (2.8) litre; V(2)=183.34 (13.5) litre; Cl(el)=0.54 (0.07) litre min(-1); Cl(dist)=2.84 (0.42) litre min(-1)]. CONCLUSIONS: The compartmental data set describing a two-compartment model was determined and could be implemented to drive automated pumps. Thus, work load could be distributed to a pump establishing and maintaining any desired plasma concentration deemed necessary for a treatment with therapeutical hypothermia.

Population pharmacokinetics of sevoflurane in conjunction with the AnaConDa: toward target-controlled infusion of volatiles into the breathing system.

BACKGROUND: The Anesthetic Conserving Device (AnaConDa) uncouples delivery of a volatile anesthetic (VA) from fresh gas flow (FGF) using a continuous infusion of liquid volatile into a modified heat-moisture exchanger capable of adsorbing VA during expiration and releasing adsorbed VA during inspiration. It combines the simplicity and responsiveness of high FGF with low agent expenditures. We performed in vitro characterization of the device before developing a population pharmacokinetic model for sevoflurane administration with the AnaConDa, and retrospectively testing its performance (internal validation). MATERIALS AND METHODS: Eighteen females and 20 males, aged 31-87, BMI 20-38, were included. The end-tidal concentrations were varied and recorded together with the VA infusion rates into the device, ventilation and demographic data. The concentration-time course of sevoflurane was described using linear differential equations, and the most suitable structural model and typical parameter values were identified. The individual pharmacokinetic parameters were obtained and tested for covariate relationships. Prediction errors were calculated. RESULTS: In vitro studies assessed the contribution of the device to the pharmacokinetic model. In vivo, the sevoflurane concentration-time courses on the patient side of the AnaConDa were adequately described with a two-compartment model. The population median absolute prediction error was 27% (interquartile range 13-45%). CONCLUSION: The predictive performance of the two-compartment model was similar to that of models accepted for TCI administration of intravenous anesthetics, supporting open-loop administration of sevoflurane with the AnaConDa. Further studies will focus on prospective testing and external validation of the model implemented in a target-controlled infusion device.

Hypnotic and opioid anesthetic drug interactions on the CNS, focus on response surface modeling.

This chapter will present the conceptual and applied approaches to capture the interaction of anesthetic hypnotic drugs with opioid drugs, as used in the clinical anesthetic state. The graphic and mathematical approaches used to capture hypnotic/opiate anesthetic drug interactions will be presented. This chapter is not a review article about interaction modeling, but focuses on specific drug interactions within a quite narrow field, anesthesia.

[Pharmacokinetic-pharmacodynamic models for inhaled anaesthetics]. / Pharmakokinetische/pharmakodynamische Modelle für Inhalationsanästhetika.

Pharmacokinetic models can be differentiated into two groups: physiological-based models and empirical models. Traditionally the pharmacokinetics of volatile anaesthetics are described using physiological-based models together with the respective tissue-blood distribution coefficients. The compartments of the empirical model have no anatomical equivalents and are merely the product of the mathematical procedure for parameter estimation. The end expiratory concentration of volatile anaesthetics is approximately equal to the arterial concentration and, therefore, the description of the transition between plasma and effect site for volatile anaesthetics plays a central role. The most important parameter here is the k(e0) value which is a time constant and describes the time delay for the transition from the central compartment to the calculated effect compartment. The k(e0) values for sevoflurane and isoflurane are the same but the concentration balance between the end-tidal concentration and the effect compartment occurs twice as quickly with desflurane. In clinical practice volatile anaesthetics are normally combined with N(2)O and/or opioids. This results in an additive interaction between volatile anaesthetics and N(2)O but a synergistic interaction of volatile anaesthetics with opioids. However, there are relatively few investigations on the interactions between the clinically widely used combination of volatile anaesthetics, N(2)O and opioids.

Ondansetron does not reduce the shivering threshold in healthy volunteers.

BACKGROUND: Ondansetron, a serotonin-3 receptor antagonist, reduces postoperative shivering. Drugs that reduce shivering usually impair central thermoregulatory control, and may thus be useful for preventing shivering during induction of therapeutic hypothermia. We determined, therefore, whether ondansetron reduces the major autonomic thermoregulatory response thresholds (triggering core temperatures) in humans. METHODS: Control (placebo) and ondansetron infusions at the target plasma concentration of 250 ng ml(-1) were studied in healthy volunteers on two different days. Each day, skin and core temperatures were increased to provoke sweating; then reduced to elicit peripheral vasoconstriction and shivering. We determined the core-temperature sweating, vasoconstriction and shivering thresholds after compensating for changes in mean-skin temperature. Data were analysed using t-tests and presented as means (sds); P<0.05 was taken as significant. RESULTS: Ondensetron plasma concentrations were 278 (57), 234 (55) and 243 (58) ng ml(-1) at the sweating, vasoconstriction and shivering thresholds, respectively; these corresponded to approximately 50 mg of ondansetron which is approximately 10 times the dose used for postoperative nausea and vomiting. Ondansetron did not change the sweating (control 37.4 (0.4) degrees C, ondansetron 37.6 (0.3) degrees C, P=0.16), vasoconstriction (37.0 (0.5) degrees C vs 37.1 (0.3) degrees C; P=0.70), or shivering threshold (36.3 (0.5) degrees C vs 36.3 (0.6) degrees C; P=0.76). No sedation was observed on either study day. CONCLUSIONS: /b>. Ondansetron appears to have little potential for facilitating induction of therapeutic hypothermia.

[Effect compartment equilibration and time-to-peak effect. Importance of a pharmacokinetic-pharmacodynamic principle for the daily clinical practice]. / Wirkortäquilibration, Anschlagzeit, "time to peak effect". Bedeutung pharmakokinetisch-dynamischer Prinzipien für die tägliche klinische Praxis.

Contrary to the situation in "classical" clinical pharmacology, non-steady state phenomena play a fundamental role for clinical pharmacology in anesthesia. Their understanding is of tantamount importance for the safe and efficient application of drugs relevant to anesthesia. Concepts like optimised target-controlled infusion (TCI), effect compartment targeting and the small margin of error tolerable during maintained spontaneous ventilation, force the anesthesiologist to acquire a firm understanding of the difference between the concentration time course at the effect side vs. time course of the plasma concentration. The underlying concepts, their application for the rational use of muscle relaxants, propofol with TCI systems, volatile anaesthetics and opioids will be discussed.

The pharmacokinetics of piritramide after prolonged administration to intensive care patients.

BACKGROUND AND OBJECTIVE: The purpose of the present study was to determine the pharmacokinetics of the micro-agonist opioid pirinitramide (piritramide) after prolonged administration. METHODS: Nine patients requiring intensive care therapy and artificial ventilation for several days received piritramide with a median infusion rate of 5 mg h(-1) (range 4.8-10 mg h(-1)) for a median period of 69.9 h (range 49-89 h) for analgesia and sedation. After the end of the infusion, frequent arterial blood samples were withdrawn for 96 h and assayed for piritramide using a gas chromatographic method. Standard compartmental models were fitted to the individual concentration-time courses to characterize the elimination of piritramide after prolonged administration. RESULTS: The concentration-time course after the end of the infusion was adequately described with a three-compartment model in eight patients and a two-compartment model in one patient (standard two-stage geometric mean and 16-84% quantile: volumes of distribution V1 = 47.9 (26.8-85.8)L, V2 = 402 (241-672)L, V3 = 332 (124-885)L; clearances Cl1 = 66.5 (53.2-83.0)Lh(-1), Cl2 = 215 (125-369)Lh(-1), Cl3 = 18.4 (9.2-36.8) Lh(-1)). Both the steady-state volume of distribution (782 L) and the terminal elimination half-life (17.4 h) were larger than predicted from single bolus pharmacokinetic studies (412.5 L and 10.4 h, respectively), the context-sensitive half-time after more than 72 h of administration was 32% shorter than predicted (285 vs. 420 min). CONCLUSIONS: Despite increasing terminal elimination half-life and volume of distribution at steady state (increasing drug load for a given plasma concentration), the context-sensitive half-time of piritramide after 3 days of administration is lower than predicted from bolus kinetics, making the drug a suitable candidate for intensive care unit analgesia.

Comparison of the concentration-dependent effect of sevoflurane on the spinal H-reflex and the EEG in humans.

BACKGROUND: It has been shown that spinal reflexes such as the H-reflex predict motor responses to painful stimuli better than cortical parameters derived from the EEG. The precise concentration-dependence of H-reflex suppression by anaesthetics, however, is not known. Here we investigated this concentration-response relationship and the equilibration between the alveolar and the effect compartment for sevoflurane. METHODS: In 26 patients, the H-reflex was recorded at a frequency of 0.1 Hz while anaesthesia was induced and maintained with sevoflurane at increasing and decreasing concentrations. Population pharmacodynamic modelling was performed using the NONMEM software package, yielding population mean parameters as well as indicators of interindividual variability. RESULTS: Suppression of H-reflex amplitude occurred at lower concentrations (mean EC(50) 1.04 +/- 0.10 vol%, SE of NONMEM estimate) than the effect on either BIS or SEF(95) of the EEG (mean EC(50) 1.55 +/- 0.08 and 1.72 +/- 0.18 vol%, respectively), and exhibited a higher interindividual variability. The concentration-response function for the H-reflex was also steeper (mean ë 2.83 +/- 0.25). In addition, the equilibration between alveolar and effect compartment was slower for the H-reflex (mean k(e0) 0.15 +/- 0.01 min(-1)) than for BIS or SEF(95) (mean k(e0) 0.22 +/- 0.02 and 0.41 +/- 0.05 min(-1)). CONCLUSION: The differences in EC(50) and slope of the concentration-response relationships for H-reflex suppression and the EEG parameters point to different underlying mechanisms. In addition, the differences in time constant for equilibration between alveolar and effect compartment confirm the notion that immobility is caused at a different anatomic site than suppression of the EEG.

Model-based control of mechanical ventilation: design and clinical validation.

BACKGROUND: We developed a model-based control system using end-tidal carbon dioxide fraction (FE'(CO(2))) to adjust a ventilator during clinical anaesthesia. METHODS: We studied 16 ASA I-II patients (mean age 38 (range 20-59) yr; weight 67 (54-87) kg) during i.v. anaesthesia for elective surgery. After periods of normal ventilation the patients were either hyper- or hypoventilated to assess precision and dynamic behaviour of the control system. These data were compared with a previous group where a fuzzy-logic controller had been used. Responses to different clinical events (invalid carbon dioxide measurement, limb tourniquet release, tube cuff leak, exhaustion of carbon dioxide absorbent, simulation of pulmonary embolism) were also noted. RESULTS: The model-based controller correctly maintained the setpoint. No significant difference was found for the static performance between the two controllers. The dynamic response of the model-based controller was more rapid (P<0.05). The mean rise time after a setpoint increase of 1 vol% was 313 (sd 90) s and 142 (17) s for fuzzy-logic and model-based control, respectively, and after a 1 vol% decrease was 355 (127) s and 177 (36) s, respectively. The new model-based controller had a consistent response to clinical artefacts. CONCLUSION: A model-based FE'(CO(2)) controller can be used in a clinical setting. It reacts appropriately to artefacts, and has a better dynamic response to setpoint changes than a previously described fuzzy-logic controller.

Piritramide and alfentanil display similar respiratory depressant potency.

BACKGROUND: The question whether some opioids exert less respiratory depression than others has not been answered conclusively. We applied pharmacokinetic/pharmacodynamic (PKPD) modeling to obtain an estimate of the C50 for the depression of CO2 elimination as a measure of the respiratory depressant potency of alfentanil and piritramide, two opioids with vastly different pharmacokinetics and apparent respiratory depressant action. METHODS: Twenty-three patients received either alfentanil (2.3 microg x kg(-1) x min-1, 14 patients, as published previously) or piritramide (17.9 microg x kg(-1) x min(-1), nine patients) until significant respiratory depression occurred. Opioid pharmacokinetics and the arterial PCO2 (PaCO2) were determined from frequent arterial blood samples. An indirect response model accounting for the respiratory stimulation due to increasing PaCO2 was used to describe the PaCO2 data. RESULTS: The following pharmacodynamic parameters were estimated with NONMEM [population means and interindividual variability (CV)]: k(elCO2) (elimination rate constant of CO2) 0.144 (-) min(-1), F (gain of the CO2 response) 4.0 (fixed according to literature values) (28%), C50 (both drugs) 61.3 microg l-1 (41%), k(eo alfentanil) 0.654 (-) min(-1) and k(eo piritramide) 0.023 (-) min(-1). Assigning separate C50 values for alfentanil and piritramide did not improve the fit compared with a model with the same C50. CONCLUSION: Since the C50 values did not differ, both drugs are equally potent respiratory depressants. The apparently lower respiratory depressant effect of piritramide when compared with alfentanil is caused by slower equilibration between the plasma and the effect site. Generalizing our results and based on simulations we conclude that slowly equilibrating opioids like piritramide are intrinsically safer with regard to respiratory depression than rapidly equilibrating opioids like alfentanil.

Opioid-induced respiratory depression is associated with increased tidal volume variability.

BACKGROUND AND OBJECTIVE: mu-agonistic opioids cause concentration-dependent hypoventilation and increased irregularity of breathing. The aim was to quantify opioid-induced irregularity of breathing and to investigate its time-course during and after an opioid infusion, and its ability to predict the severity of respiratory depression. METHODS: Twenty-three patients breathing spontaneously via a continuous positive airway pressure (CPAP) mask received an intravenous (i.v.) infusion of alfentanil (2.3 microg kg(-1) min(-1), 14 patients) or pirinitramide (piritramide) (17.9 microg kg(-1) min(-1), nine patients) until either a cumulative dose of 70 microg kg(-1) for alfentanil or 500 microg kg(-1) for pirinitramide had been achieved or the infusion had to be stopped for safety reasons. Tidal volumes (VT) and minute ventilation were measured with an anaesthesia workstation. For every 20 breaths, the quartile coefficient was calculated (Qeff20V(T)). RESULTS: Both the decrease of minute volume and the increase of Qeff20V(T) during and after opioid infusion were highly significant (P < 0.001, ANOVA). Patients in which the alfentanil infusion had to be terminated prematurely had lower minute volumes (P = 0.002, t-test) and higher Qeff20V(T) (P = 0.034, t-test) than those who received the complete dose. Changes in the regularity of breathing measured as Qeff20V(T) parallel those of minute ventilation during and after opioid infusion. CONCLUSIONS: Opioids cause a more complicated disturbance of the control of respiration than a mere resetting to higher PCO2. Furthermore, Qeff20V(T) appears to predict the severity of opioid-induced respiratory depression.

Application of semilinear canonical correlation to the measurement of the electroencephalographic effects of volatile anaesthetics.

BACKGROUND AND OBJECTIVE: The common parameters of the electroencephalogram quantify a shift of its power spectrum towards lower frequencies with increasing anaesthetic drug concentrations (e.g. spectral-edge frequency 95). These ad hoc parameters are not optimized for the content of information with regard to drug effect. Using semilinear canonical correlation, different frequency ranges (bins) of the power spectrum can be weighted for sensitivity to changes of drug concentration by multiplying their power with iteratively determined coefficients, yielding a new (canonical univariate) electroencephalographic parameter. METHODS: Electroencephalographic data obtained during application of volatile anaesthetics were used: isoflurane (n = 6), desflurane (7), sevoflurane (7), desflurane during surgical stimulation (12). Volatile anaesthetic end-tidal concentrations varied between 0.5 and 1.6 minimum alveolar concentration (MAC). The canonical univariate parameter and spectral-edge frequency 95 were determined and their correlation with the volatile anaesthetic effect compartment concentration, obtained by simultaneous pharmacokinetic-pharmacodynamic modelling, were compared. RESULTS: The canonical univariate parameter with individually optimized coefficients, but not with mean coefficients, was superior to the spectral-edge frequency 95 as a measure of anaesthetic drug effect. No significant differences of the coefficients were found between the three volatile anaesthetics or between the data with or without surgical stimulus. The coefficients for volatile anaesthetics were similar to the coefficients for opioids, but different from coefficients for propofol and midazolam. CONCLUSIONS: The canonical univariate parameter calculated with individually optimized coefficients, but not with mean coefficients, correlates more accurately and consistently with the effect site concentrations of volatile anaesthetics than with spectral-edge frequency 95.

Onset of propofol-induced burst suppression may be correctly detected as deepening of anaesthesia by approximate entropy but not by bispectral index.

The bispectral index (BIS) is a complex EEG variable that combines several disparate descriptors of the EEG into a single value. Approximate entropy is a novel EEG measure that quantifies the regularity of a data time series such as EEG. We report two patients in which the EEG effect of propofol was quantified very similarly by BIS and approximate entropy. However, at the beginning of burst suppression of the EEG, BIS did not indicate an increased anaesthetic drug effect, while approximate entropy did.

Pharmacodynamic interaction of nitrous oxide with sevoflurane, desflurane, isoflurane and enflurane in surgical patients: measurements by effects on EEG median power frequency.

BACKGROUND AND OBJECTIVE: This study investigates the interaction of sevoflurane and nitrous oxide on EEG median power frequency of 2.5 Hz during surgery. METHODS: Sevoflurane concentrations required for electroencephalographic median power frequency between 2 and 3 Hz were measured in 25 patients during gynaecological laparotomies. Nitrous oxide was randomly administered at 0, 20, 40, 60 and 75 vol%, subsequently two different concentrations in each patient. The data were analysed using isobolographic analysis together with previously published data on nitrous oxide-isoflurane, -enflurane, or -desflurane interaction. RESULTS: The interaction is described by the equation: C volatile anaesthetic/C0 volatile anaesthetic + C N2O/C0 N2O=1 (C is the concentrations for a drug combination to achieve the desired effect; C0 is the concentration for single drug use). The parameters are C0 isoflurane=1.11 vol% (95% CI 1.03-1.19), C0 enflurane=1.64 (1.52-1.77), C0 desflurane=5.31 (4.92-5.73), C0 sevoflurane=2.12 (1.96-2.29), C0 N2O=174 (153-202). These parameters decrease by 6% (2.5-10) for every 10 years of patients' age > 40 years. CONCLUSIONS: The interaction is compatible with additivity. The potency of nitrous oxide to substitute the volatile anaesthetics is less than anticipated from previously reported MAC values.

Shannon entropy applied to the measurement of the electroencephalographic effects of desflurane.

BACKGROUND: The Shannon entropy is a standard measure for the order state of sequences. It quantifies the degree of skew of the distribution of values. Increasing hypnotic drug concentrations increase electroencephalographic amplitude. The probability density function of the amplitude values broadens and flattens, thereby changing from a skew distribution towards equal distribution. We investigated the dose-response relation of the Shannon entropy of the electroencephalographic amplitude values during desflurane monoanesthesia in comparison with previously used electroencephalographic parameters. METHODS: Electroencephalographic records previously obtained in 12 female patients during gynecologic laparotomies were reanalyzed. Between opening and closure of the peritoneum, desflurane vapor settings were varied between 0.5 and 1.6 minimum alveolar concentration. Electroencephalographic Shannon entropy, approximate entropy, median electroencephalographic frequency, SEF 95, total power, log total power, and Bispectral Index were determined, and their correlations with the desflurane effect compartment concentration, obtained by simultaneous pharmacokinetic-pharmacodynamic modeling, were compared. RESULTS: The electroencephalographic Shannon entropy increased continuously over the observed concentration range of desflurane. The correlation of the Shannon entropy (R2 = 0.84+/-0.08, mean +/- SD) with the desflurane effect compartment concentrations is similar to approximate entropy (R2 = 0.85+/-0.12), SEF 95 (R2 = 0.85+/-0.10), and Bispectral Index (R2 = 0.82+/-0.13) and is more statistically significant than median frequency (R2 = 0.72+/-0.17), total power (R2 = 0.67+/-0.18), and log total power (R2 = 0.80+/-0.09). CONCLUSIONS: The Shannon entropy seems to be a useful electroencephalographic measure of anesthetic drug effect.

Surgical stimulation shifts EEG concentration-response relationship of desflurane.

BACKGROUND: Anesthesiologists routinely increase the delivered anesthetic concentration before surgical stimulation in anticipation of increased anesthetic requirement to achieve certain goals (e.g., amnesia, unconsciousness, and immobility). Electroencephalographic monitoring is one method of determining indirectly anesthetic effect on the brain. The present study investigated the effect of surgical stimuli on the concentration-response relation of desflurane-induced electroencephalographic changes. METHODS: The electroencephalographic activity was recorded from 24 female patients who received only desflurane after a single induction dose of propofol. Twelve patients served as a control group before surgical stimulation. The other 12 patients, all undergoing lower abdominal surgery, were investigated between opening and closure of the peritoneum. Desflurane vaporizer settings were randomly increased and decreased between 0.5 and 1.6 minimum alveolar concentration as long as anesthesia was considered adequate. Spectral edge frequency 95, median power frequency, and Bispectral Index were calculated. Desflurane effect-site concentrations and the concentration-effect curves for spectral edge frequency 95, median power frequency, and Bispectral Index were determined by simultaneous pharmacokinetic and pharmacodynamic modeling. RESULTS: Surgical stimulation shifted the desflurane concentration-electroencephalographic effect curves for spectral edge frequency 95, median power frequency, and Bispectral Index toward higher desflurane concentrations. In the unstimulated group, 2.2 +/- 0.74 vol% desflurane were necessary to achieve a Bispectral Index of 50, whereas during surgery, 6.8 +/- 0.98 vol% (mean +/- SE) were required. CONCLUSIONS: During surgery, higher concentrations of the volatile anesthetic are required to achieve a desired level of cortical electrical activity and, presumably, anesthesia.

Propofol and remifentanil pharmacodynamic interaction during orthopedic surgical procedures as measured by effects on bispectral index.

STUDY OBJECTIVE: To identify and quantify the interaction between propofol and remifentanil during surgical procedures with a bispectral index (BIS) of 50 that was chosen as a continuous surrogate measure for "adequate depth" of anesthesia. DESIGN: Prospective, open-label study. SETTING: Department of orthopedics of a university hospital. PATIENTS: 20 patients undergoing orthopedic surgery. INTERVENTIONS: Anesthesia was induced and maintained with propofol and remifentanil, both administered by target-controlled infusion (TCI). Initial target concentrations of propofol (1.5-8 microg/mL) and remifentanil (2-15 ng/mL) were chosen and alternated in order to maintain the BIS between 45 and 55. If constant target concentrations had been maintained for 20 minutes and the BIS did not depart from the desired range, blood samples were taken to determine propofol concentrations, and the BIS value was recorded. Isobolographic interaction models were fitted to the infusion rates of remifentanil and propofol, predicted target concentrations of both drugs, and measured propofol concentrations versus predicted remifentanil concentrations. MAIN RESULTS: The isobole for the interaction of propofol and remifentanil in the concentration range investigated (propofol 1.5-8 microg/mL and remifentanil 1-30 ng/mL) is a concave up hyperbola ((0.15. C(prop))(3.13). C(rem) = 1) with C(prop) = propofol plasma concentration [microg/mL] and C(rem) = remifentanil blood concentration [ng/mL]). Use of predicted (=TCI target) concentrations or the respective infusion rates did not alter the general shape of the interaction isobole. CONCLUSIONS: The interaction between propofol and remifentanil for maintenance of a BIS value between 45 and 55 during surgery is synergistic. This finding applies regardless of whether measured concentrations (for propofol), predicted concentrations of the infusion device, or infusion rates are used as model input. Notably, the interaction isobole of the (clinically readily available) infusion rates provides a useful dosing recommendation for the coadministration of propofol and remifentanil during maintenance of anesthesia.

Electroencephalogram approximate entropy correctly classifies the occurrence of burst suppression pattern as increasing anesthetic drug effect.

BACKGROUND: Approximate entropy, a measure of signal complexity and regularity, quantifies electroencephalogram changes during anesthesia. With increasing doses of anesthetics, burst-suppression patterns occur. Because of the high-frequency bursts, spectrally based parameters such as median electroencephalogram frequency and spectral edge frequency 95 do not decrease, incorrectly suggesting lightening of anesthesia. The authors investigated whether the approximate entropy algorithm correctly classifies the occurrence of burst suppression as deepening of anesthesia. METHODS: Eleven female patients scheduled for elective major surgery were studied. After propofol induction, anesthesia was maintained with isoflurane only. Before surgery, the end-tidal isoflurane concentration was varied between 0.6 and 1.3 minimum alveolar concentration. The raw electroencephalogram was continuously recorded and sampled at 128 Hz. Approximate entropy, electroencephalogram median frequency, spectral edge frequency 95, burst-suppression ratio, and burst-compensated spectral edge frequency 95 were calculated offline from 8-s epochs. The relation between burst-suppression ratio and approximate entropy, electroencephalogram median frequency, spectral edge frequency 95, and burst-compensated spectral edge frequency 95 was analyzed using Pearson correlation coefficient. RESULTS: Higher isoflurane concentrations were associated with higher burst-suppression ratios. Electroencephalogram median frequency (r = 0.34) and spectral edge frequency 95 (r = 0.29) increased, approximate entropy (r = -0.94) and burst-compensated spectral edge frequency 95 (r = -0.88) decreased with increasing burst-suppression ratio. CONCLUSION: Electroencephalogram approximate entropy, but not electroencephalogram median frequency or spectral edge frequency 95 without burst compensation, correctly classifies the occurrence of burst-suppression pattern as increasing anesthetic drug effect.