Thomas Bouillon

Pharmacodynamic interaction between propofol and remifentanil regarding hypnosis, tolerance of laryngoscopy, bispectral index, and electroencephalographic approximate entropy.

Background: The purpose of this investigation was to describe the pharmacodynamic interaction between propofol and remifentanil for probability of no response to shaking and shouting, probability of no response to laryngoscopy, Bispectral Index (BIS), and electroencephalographic approximate entropy (AE). Methods: Twenty healthy volunteers received either propofol or remifentanil alone and then concurrently with a fixed concentration of remifentanil or propofol, respectively, via a target-controlled infusion. Responses to shaking and shouting and to laryngoscopy were assessed multiple times after allowing for plasma effect site equilibration. The raw electroencephalogram and BIS were recorded throughout the study, and AE was calculated off-line. Response surfaces were fit to the clinical response data using logistic regression or hierarchical response models. Response surfaces were also estimated for BIS and AE. Surfaces were visualized using three-dimensional rotations. Model parameters were estimated with NONMEM. Results: Remifentanil alone had no appreciable effect on response to shaking and shouting or response to laryngoscopy. Propofol could ablate both responses. Modest remifentanil concentrations dramatically reduced the concentrations of propofol required to ablate both responses. The hierarchical response surface described the data better than empirical logistic regression. BIS and AE are more sensitive to propofol than to remifentanil. Conclusions: Remifentanil alone is ineffective at ablating response to stimuli but demonstrates potent synergy with propofol. BIS and AE values corresponding to 95% probability of ablating response are influenced by the combination of propofol and remifentanil to achieve this endpoint, with higher propofol concentrations producing lower values for BIS and AE.

Electromyographic activity falsely elevates the bispectral index.

THE bispectral index (BIS, Aspect Medical Systems, Framingham, MA) is a complex electroencephalographic (EEG) parameter that integrates several disparate descriptors of the EEG into a single variable and correlates behavioral assessments of sedation and hypnosis. We report two cases in which the bispectral index failed to measure depth of anesthesia but instead was a measure of electromyographic (EMG) activity. In the first case bispectral index paradoxically increased after increasing propofol concentration, correlating with increasing EMG activity. In the second case the administration of a nondepolarizing muscle relaxant decreased the bispectral index value at constant anesthetic drug concentrations.

Correlation of approximate entropy, bispectral index, and spectral edge frequency 95 (SEF95) with clinical signs of "anesthetic depth" during coadministration of propofol and remifentanil.

Background Several studies relating electroencephalogram parameter values to clinical endpoints using a single (mostly hypnotic) drug at relatively low levels of central nervous system depression (sedation) have been published. However, the usefulness of a parameter derived from the electroencephalogram for clinical anesthesia largely depends on its ability to predict the response to stimuli of different intensity or painfulness under a combination of a hypnotic and an (opioid) analgesic. This study was designed to evaluate the predictive performance of spectral edge frequency 95 (SEF95), BIS, and approximate entropy for the response to increasingly intense stimuli under different concentrations of both propofol and remifentanil in the therapeutic range. Methods Ten healthy male and ten healthy female volunteers were studied during coadministration of propofol and remifentanil. After having maintained a specific target concentration for 10 min, the depth of sedation–anesthesia was assessed using the responsiveness component of the Observers Assessment of Alertness/Sedation (OAA/S) rating scale, which was modified by adding insertion of a laryngeal mask and laryngoscopy. The electroencephalogram derived parameters approximate entropy, bispectral index, and SEF95 were recorded just before sedation level was assessed. Results The prediction probability values for approximate entropy were slightly, but not significantly, better than those for bispectral index, SEF95, and the combination of drug concentrations. A much lower prediction ability was observed for tolerance of airway manipulation than for hypnotic endpoints. Conclusion Approximate entropy revealed informations on hypnotic and analgesic endpoints using coadministration of propofol and remifentanil comparable to bispectral index, SEF95, and the combination of drug concentrations.

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

BackgroundApproximate 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. MethodsEleven 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. ResultsHigher 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. ConclusionElectroencephalogram 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.

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

BackgroundThe 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. MethodsElectroencephalographic 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. ResultsThe 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). ConclusionsThe Shannon entropy seems to be a useful electroencephalographic measure of anesthetic drug effect.

A new closed-loop control system for isoflurane using bispectral index outperforms manual control

Background: Automatic control of depth of hypnosis using the Bispectral Index (BIS) can help to reduce phases of inadequate control. Automated BIS control with propofol or isoflurane administration via an infusion system has recently been described, a comparable study with isoflurane administration via a vaporizer had not been conducted yet. Our hypothesis was that our new model based closed-loop control system can safely be applied clinically and maintains the BIS within a defined target range better than manual control. Methods: Twenty-three patients, American Society of Anesthesiologists risk class I–III, scheduled for decompressive spinal surgery were randomized into groups with either closed-loop or manual control of BIS using isoflurane. An alfentanil target-controlled infusion was adjusted according to standard clinical practice. The BIS target was set to 50 during the operation. The necessity of human intervention in the control system and events of inadequate sedation (BIS <40 or BIS >60) were counted. The number of phases of inadequate control, defined as BIS ≥65 for more than 3 min, were recorded. The performance of the controller was assessed by several indicators (mean absolute deviation and median absolute performance error) and measured during the skin incision phase, the subsequent low flow phase, and the wound closure phase. Recovery profiles of both groups were compared. Results: No human intervention was necessary in the closed-loop control group. The occurrence of inadequate BIS was quantified with the mean and median values of the area under the curve and amounted to 0.360 and 0.088 for the manual control group and 0.049 and 0.017 for the closed-loop control group, respectively. In the manual control group nine phases of inadequate control were recorded, compared with one in the closed-loop control group, 10.3% to 0.5% of all observed anesthesia time. During all phases the averages of the performance parameters (mean absolute deviation and median absolute performance error) were more than 30% smaller in closed-loop control than in manual control (P < 0.05 between groups). Conclusions: Closed-loop control with BIS using isoflurane can safely be applied clinically and performs significantly better than manual control, even in phases with abrupt changes of stimulation that cannot be foreseen by the control system.

A model of the ventilatory depressant potency of remifentanil in the non-steady state.

Background The C50 of remifentanil for ventilatory depression has been previously determined using inspired carbon dioxide and stimulated ventilation, which may not describe the clinically relevant situation in which ventilatory depression occurs in the absence of inspired carbon dioxide. The authors applied indirect effect modeling to non–steady state Paco2 data in the absence of inspired carbon dioxide during and after administration of remifentanil. Methods Ten volunteers underwent determination of carbon dioxide responsiveness using a rebreathing design, and a model was fit to the end-expiratory carbon dioxide and minute ventilation. Afterwards, the volunteers received remifentanil in a stepwise ascending pattern using a computer-controlled infusion pump until significant ventilatory depression occurred (end-tidal carbon dioxide [Peco2] > 65 mmHg and/or imminent apnea). Thereafter, the concentration was reduced to 1 ng/ml. Remifentanil pharmacokinetics and Paco2 were determined from frequent arterial blood samples. An indirect response model was used to describe the Paco2 time course as a function of remifentanil concentration. Results The time course of hypercarbia after administration of remifentanil was well described by the following pharmacodynamic parameters: F (gain of the carbon dioxide response), 4.30; ke0 carbon dioxide, 0.92 min−1; baseline Paco2, 42.4 mmHg; baseline minute ventilation, 7.06 l/min; kel,CO2, 0.08 min−1; C50 for ventilatory depression, 0.92 ng/ml; Hill coefficient, 1.25. Conclusion Remifentanil is a potent ventilatory depressant. Simulations demonstrated that remifentanil concentrations well tolerated in the steady state will cause a clinically significant hypoventilation following bolus administration, confirming the acute risk of bolus administration of fast-acting opioids in spontaneously breathing patients.

Comparative Pharmacodynamic Modeling of the Electroencephalography-slowing Effect of Isoflurane, Sevoflurane, and Desflurane

BACKGROUND The most common measure to compare potencies of volatile anesthetics is minimum alveolar concentration (MAC), although this value describes only a single point on a quantal concentration-response curve and most likely reflects more the effects on the spinal cord rather than on the brain. To obtain more complete concentration-response curves for the cerebral effects of isoflurane, sevoflurane, and desflurane, the authors used the spectral edge frequency at the 95th percentile of the power spectrum (SEF95) as a measure of cerebral effect. METHODS Thirty-nine patients were randomized to isoflurane, sevoflurane, or desflurane groups. After induction with propofol, intubation, and a waiting period, end-tidal anesthetic concentrations were randomly varied between 0.6 and 1.3 MAC, and the EEG was recorded continuously. Population pharmacodynamic modeling was performed using the software package NONMEM. RESULTS The population mean EC50 values of the final model for SEF95 suppression were 0.66+/-0.08 (+/- SE of estimate) vol% for isoflurane, 1.18+/-0.10 vol% for sevoflurane, and 3.48+/-0.66 vol% for desflurane. The slopes of the concentration-response curves were not significantly different; the common value was lambda = 0.86+/-0.06. The Ke0 value was significantly higher for desflurane (0.61+/-0.11 min(-1)), whereas separate values for isoflurane and sevoflurane yielded no better fit than the common value of 0.29+/-0.04 min(-1). When concentration data were converted into fractions of the respective MAC values, no significant difference of the C50 values for the three anesthetic agents was found. CONCLUSIONS This study demonstrated that (1) the concentration-response curves for spectral edge frequency slowing have the same slope, and (2) the ratio C50(SEF95)/MAC is the same for all three anesthetic agents. The authors conclude that MAC and MAC multiples, for the three volatile anesthetics studied, are valid representations of the concentration-response curve for anesthetic suppression of SEF95.

Non–steady State Analysis of the Pharmacokinetic Interaction between Propofol and Remifentanil

Background The pharmacokinetics of both propofol and remifentanil have been described extensively. Although they are commonly administered together for clinical anesthesia, their pharmacokinetic interaction has not been investigated so far. The purpose of the current investigation was to elucidate the nature and extent of pharmacokinetic interactions between propofol and remifentanil. Methods Twenty healthy volunteers aged 20–43 yr initially received either propofol or remifentanil alone in a stepwise incremental and decremental fashion via a target controlled infusion. Thereafter, the respective second drug was infused to a fixed target concentration in the clinical range (0–4 &mgr;g/ml and 0–4 ng/ml for propofol and remifentanil, respectively) and the stepwise incremental pattern repeated. Frequent blood samples were drawn for up to 6 h for propofol and 40 min for remifentanil after the end of administration and assayed for the respective drug concentrations with gas chromatography–mass spectrometry. The time courses of the measured concentrations were fitted to standard compartmental models. Calculations were performed with NONMEM. After having established the individual population models for both drugs and an exploratory analysis for hypothesis generation, pharmacokinetic interaction was identified by including an interaction term into the population model and comparing the value of the objective function in the presence and absence of the respective term. Results The concentration–time courses of propofol and remifentanil were described best by a three- and two-compartment model, respectively. In the concentration range examined, remifentanil does not alter propofol pharmacokinetics. Coadministration of propofol decreases the central volume of distribution and distributional clearance of remifentanil by 41% and elimination clearance by 15%. This effect was not concentration-dependent in the examined concentration range of propofol. Conclusions Coadministration of propofol decreases the bolus dose of remifentanil needed to achieve a certain plasma–effect compartment concentration but does not alter the respective maintenance infusion rates and recovery times to a clinically significant degree.

Pharmacokinetic-Pharmacodynamic Modeling of the Respiratory Depressant Effect of Alfentanil

BACKGROUND Although respiratory depression is the most well-known and dangerous side effect of opioids, no pharmacokinetic-pharmacodynamic model exists for its quantitative analysis. The development of such a model was the aim of this study. METHODS After institutional approval approval and informed consent were obtained, 14 men (American Society of Anesthesiologists physical status I or II; median age, 42 yr [range, 20-71 yr]; median weight, 82.5 kg [range, 68-108 kg]) were studied before they underwent major urologic surgery. An intravenous infusion of alfentanil (2.3 microg x kg(-1) x min(-1)) was started while the patients were breathing oxygen-enriched air (fraction of inspired oxygen [FIO2 = 0.5) over a tightly fitting continuous positive airway pressure mask. The infusion was discontinued when a cumulative dose of 70 microg/kg had been administered, the end-expiratory partial pressure of carbon dioxide (PE(CO2) exceeded 65 mmHg, or apneic periods lasting more than 60 s occurred During and after the infusion, frequent arterial blood samples were drawn and analyzed for the concentration of alfentanil and the arterial carbon dioxide pressure (PaCO2). A mamillary two-compartment model was fitted to the pharmacokinetic data. The PaCO2 data were described by an indirect response model The model accounted for the respiratory stimulation resulting from increasing PaCO2. The model parameters were estimated using NONMEM. Simulations were performed to define the respiratory response at steady state to different alfentanil concentrations. RESULTS The indirect response model adequately described the time course of the PaCO2. The following pharmacodynamic parameters were estimated (population means and interindividual variability): EC50, 60.3 microg/l (32%); the elimination rate constant of carbon dioxide (Kel), 0.088 min(-1) (44%); and the gain in the carbon dioxide response, 4(28%) (fixed according to literature values). Simulations revealed the pronounced role of PaCO2 in maintaining alveolar ventilation in the presence of opioid. CONCLUSIONS The model described the data for the entire opioid-PaCo2 response surface examined. Indirect response models appear to be a promising tool for the quantitative evaluation of drug-induced respiratory depression.