An evaluation of remifentanil-sevoflurane response surface models in patients emerging from anesthesia: model improvement using effect-site sevoflurane concentrations

The Effect of Ramosetron on Remifentanil in Preventing Emergence Cough from Sevoflurane Anesthesia in Female Patients

BACKGROUND

Remifentanil reduces cough during extubation. Ramosetron, a 5-HT3 receptor antagonist, is a potent antiemetic. Regarding the antitussive property of 5-HT receptor agonists, ramosetron can mediate the cough reflex, as increasing the remifentanil requirement. The aim of this study was to evaluate the effect of ramosetron on the optimal effect-site concentration (Ce) of remifentanil for preventing emergence cough from sevoflurane anesthesia in female patients.

METHODS

Forty-seven female patients undergoing laparoscopic cholecystectomy randomly received either ramosetron 0.3 mg (n = 23) or the same volume of normal saline (n = 24) intravenously at the end of surgery. The remifentanil Ce using target controlled infusion in 50% of patients (EC50) and 95% of patients (EC95) were assessed using Dixon's up-and-down or isotonic regression method with a boot¬strapping approach.

RESULTS

Using Dixon's up-and-down method, the EC50 of remifentanil in the control group (1.33 ± 0.38 ng/mL) was comparable to that of ramosetron group (1.50 ± 0.69 ng/mL) (P = 0.615). Using isotonic regression analysis, the EC50 (83% confidence interval) did not differ between the two groups (1.17 [0.86-1.43] ng/mL and 1.13 [0.68-1.56] ng/mL in control and ramosetron groups). However, the EC95 (95% confidence interval) was significantly lower in the control group than in the ramosetron group (1.90 [1.45-1.96] ng/mL and 2.92 [2.35-2.97] ng/mL).

CONCLUSION

Remifentanil Ce for preventing emergence cough was higher in the ramosetron group than the control group. It may indicate the lowering effect of ramosetron on antitussive activity of remifentanil.

A pharmacokinetic-pharmacodynamic real-time display may change anesthesiologists' behavior

We have developed a real-time graphical display that presents anesthetic pharmacology data (drug effect site concentrations (Ce) and probability of anesthetic effects including hypnosis, loss of response to tracheal intubation), improving a previous prototype. We hypothesized that the use of the display alters (1) clinical behavior of anesthesiologists (i.e., Ce of isoflurane and fentanyl at the end of anesthesia), (2) fentanyl dose during the first 30 min of recovery in the post anesthesia care unit (PACU), and that the response of clinicians to the display in terms of workload and utility is favorable. The display was evaluated in a two-group, non-randomized prospective observational study of 30 patients undergoing general anesthesia using isoflurane and fentanyl. The isoflurane-predicted Ce was lower in the display group (without-display: 0.64% ± 0.06%; with-display: 0.42 ± 0.04%; t_23.9 = 3.17, P = 0.004 < adjusted alpha 0.05/2). The difference in fentanyl-predicted Ce did not achieve statistical significance (without-display: 1.5 ± 0.1 ng/ml; with-display: 2.0 ± 0.2 ng/ml; t_25.5 = 2.26, P = 0.03 > adjusted alpha 0.05/2) (means ± standard error). A joint test of isoflurane and fentanyl Ce with respect to the display condition rejected the null hypothesis of no differences (Hotelling T2, P = 0.01), supporting our primary hypothesis. The total fentanyl per patient during the first 30 min in the PACU with the display was 75.0 ± 62.7 µg and that without the display was 83.0 ± 74.7 µg. There was no significant difference between the groups (means ± standard deviation, P = 0.75). There were no differences in perceived workload. Use of the display does not appear to be cognitively burdensome and may change the anesthesiologist's dosing regimen.

Enhanced recovery after surgery: Prediction for early extubation in video-assisted thoracic surgery using a response surface model in anesthesia

BACKGROUND/PURPOSE

Enhanced recovery after surgery (ERAS) is a growing tendency in modern perioperative period management, but no protocol has been established for a strategy that optimally facilitates rapid recovery from anesthesia. We hypothesized that applying a total intravenous anesthesia (TIVA) method to the response surface model (RSM) would allow prediction of the emergence and endotracheal tube extubation in cases undergoing video-assisted thoracotomy surgery (VATS).

METHODS

Thirty patients who were scheduled to undergo VATs under TIVA were enrolled. Pharmacokinetic profiles were calculated using a Tivatrainer. Emergence from anesthesia was observed and the exact time point of the regained response (RR) was recorded. The effect of concentration was analyzed and applied to a response surface model.

RESULTS

The cumulative prediction curve of the RR was closer to the 50% probability as set by the OAA/S ≥ 4 than by the OAA/S ≥ 2 model. The median, averages, and standard deviations of the time differences were 14.5, 22.05 ± 19.23 min for the OAA/S ≥2 model and 10.4, 14.26 ± 10.40 min for the OAA/S ≥ 4 model.

CONCLUSION

The OAA/S ≥ 4 model could identify the target concentration in propofol-remifentanil pairs that predicted the time of emergence from VATS in 10 min. Our results indicate that RSM can be used to derive an ERAS protocol for VATS under TIVA. Further studies should investigate application of RSM to predict ERAS for various types of procedures.

Paradox of age: older patients receive higher age-adjusted minimum alveolar concentration fractions of volatile anaesthetics yet display higher bispectral index values

BACKGROUND

Minimum alveolar concentration (MAC) and MAC-awake decrease with age. We hypothesised that, in clinical practice, (i) end-tidal MAC fraction in older patients would decline by less than the predicted age-dependent MAC decrease (i.e. older patients would receive relatively excessive anaesthetic concentrations), and (ii) bispectral index (BIS) values would therefore be lower in older patients.

METHODS

We examined the relationship between end-tidal MAC fraction, BIS values, and age in 4699 patients > 30 yr in age at a single centre using unadjusted local regression (locally estimated scatterplot smoothing), Spearman's correlation, stratification, and robust univariable and multivariable linear regression.

RESULTS

The end-tidal MAC fraction in older patients declined by 3.01% per decade (95% confidence interval [CI]: 2.56-3.45; P<0.001), less than the 6.47% MAC decrease per decade that we found in a meta-regression analysis of published studies of age-dependent changes in MAC (P<0.001), and less than the age-dependent decrease in MAC-awake. The BIS values correlated positively with age (ρ=0.15; 95% CI: 0.12-0.17; P<0.001), and inversely with the age-adjusted end-tidal MAC (aaMAC) fraction (ρ= -0.13; 95% CI: -0.16, -0.11; P<0.001).

CONCLUSIONS

The age-dependent decline in end-tidal MAC fraction delivered in clinical practice at our institution was less than the age-dependent percentage decrease in MAC and MAC-awake determined from published studies. Despite receiving higher aaMAC fractions, older patients paradoxically showed higher BIS values. This most likely suggests that the BIS algorithm is inaccurate in older adults.

Pharmacokinetic and pharmacodynamic interactions in anaesthesia. A review of current knowledge and how it can be used to optimize anaesthetic drug administration

This review describes the basics of pharmacokinetic and pharmacodynamic drug interactions and methodological points of particular interest when designing drug interaction studies. It also provides an overview of the available literature concerning interactions, with emphasis on graphic representation of interactions using isoboles and response surface models. It gives examples on how to transform this knowledge into clinically and educationally applicable (bedside) tools.

Disposition of Remifentanil in Obesity

Background

The influence of obesity on the pharmacokinetic (PK) behavior of remifentanil is incompletely understood. The aim of the current investigation was to develop a new population PK model for remifentanil that would adequately characterize the influence of body weight (among other covariates, e.g., age) on the disposition of remifentanil in the general adult population. We hypothesized that age and various indices of body mass would be important covariates in the new model.

Methods

Nine previously published data sets containing 4,455 blood concentration measurements from 229 subjects were merged. A new PK model was built using nonlinear mixed-effects modeling. Satisfactory model performance was assessed graphically and numerically; an internal, boot-strapping validation procedure was performed to determine the CIs of the model.

Results

Body weight, fat-free body mass, and age (but not body mass index) exhibited significant covariate effects on certain three-compartment model parameters. Visual and numerical assessments of model performance were satisfactory. The bootstrap procedure showed satisfactory CIs on all of the model parameters.

Conclusions

A new model estimated from a large, diverse data set provides the PK foundation for remifentanil dosing calculations in adult obese and elderly patients. It is suitable for use in target-controlled infusion systems and pharmacologic simulation.

A desflurane and fentanyl dosing regimen for wake-up testing during scoliosis surgery: Implications for the time-course of emergence from anesthesia

BACKGROUND/PURPOSE

The Stagnara wake-up test assesses neurological deficits during scoliosis surgery, and response surface interaction models for opioids and inhaled agents predicts anesthetic drug effects. We hypothesized that there is an optimal desflurane-fentanyl dosing regimen that can provide a faster and more predictable wake-up time, while also ensuring adequate analgesia during wake-up testing.

METHODS

Twenty-three American Society of Anesthesiologists Class I-II scoliosis patients who received desflurane-fentanyl anesthetic regimens were enrolled in this posthoc study, and their intraoperative drug administration data were collected retrospectively. Desflurane and fentanyl effect site concentrations were calculated using pharmacokinetic models, and converted to equivalent remifentanil-sevoflurane concentrations.

RESULTS

Results were fitted into Greco models for predicting the probability of an Observers Assessment of Alertness/Sedation score of <2. At time of wake-up, the models correctly predicted the probability that patients would respond to voice prompts and prodding was approximately 50%. The probability of pain intensity was distributed between 50% and 95%, indicating a low degree of pain at emergence. When comparing subgroups defined by calculated effect-site fentanyl concentrations, the wake-up time in the intermediate concentration group was significantly shorter than that in the high concentration group (p = 0.024).

CONCLUSION

This study provides evidence that desflurane-fentanyl-based anesthesia is conducive to rapid emergence followed by an immediate neurological evaluation. Intermediate fentanyl effect-site concentrations (1-2 ng/mL) at time of wake-up were associated with good balance between rapid emergence and adequate analgesia. Furthermore, we believe that generalizing response surface models to a variety of inhalation agent-opioid combinations using simple relative potency relationships is possible and practical.

Incomplete Spontaneous Recovery from Airway Obstruction During Inhaled Anesthesia Induction: A Computational Simulation

BACKGROUND

Inhaled induction with spontaneous respiration is a technique used for difficult airways. One of the proposed advantages is if airway patency is lost, the anesthetic agent will spontaneously redistribute until anesthetic depth is reduced and airway patency can be recovered. There are little and conflicting clinical or experimental data regarding the kinetics of this anesthetic technique. We used computer simulation to investigate this situation.

METHODS

We used GasMan, a computer simulation of inhaled anesthetic kinetics. For each simulation, alveolar ventilation was initiated with a set anesthetic induction concentration. When the vessel-rich group level reached the simulation specified airway obstruction threshold, alveolar ventilation was set at 0 to simulate complete airway obstruction. The time until the vessel-rich group anesthetic level decreased below the airway obstruction threshold was designated time to spontaneous recovery. We varied the parameters for each simulation, exploring the use of sevoflurane and halothane, airway obstruction threshold from 0.5 to 2 minimum alveolar concentration (MAC), anesthetic induction concentration 2 to 4 MAC sevoflurane and 4 to 6 MAC halothane, cardiac output 2.5 to 10 L/min, functional residual capacity 1.5 to 3.5 L, and relative vessel-rich group perfusion 67% to 85%.

RESULTS

In each simulation, there were 3 general phases: anesthetic wash-in, obstruction and overshoot, and then slow redistribution. During the first 2 phases, there was a large gradient between the alveolar and vessel-rich group. Alveolar do not reflect vessel-rich group anesthetic levels until the late third phase. Time to spontaneous recovery varied between 35 and 749 seconds for sevoflurane and 13 and 222 seconds for halothane depending on the simulation parameters. Halothane had a faster time to spontaneous recovery because of the lower alveolar gradient and less overshoot of the vessel-rich group, not faster redistribution. Higher airway obstruction thresholds, decreased anesthetic induction, and higher cardiac output reduced time to spontaneous recovery. To a lesser effect, decreased functional residual capacity and the decreased relative vessel-rich groups' perfusion also reduced the time to spontaneous recovery.

CONCLUSIONS

Spontaneous recovery after complete airway obstruction during inhaled induction is plausible, but the recovery time is highly variable and depends on the clinical and physiologic situation. These results emphasize that induction is a non-steady-state situation, thus effect-site anesthetic levels should be modeled in future research, not alveolar concentration. Finally, this study provides an example of using computer simulation to explore situations that are difficult to investigate clinically.

Pharmacokinetic-pharmacodynamic modelling in anaesthesia

Anaesthesiologists adjust drug dosing, administration system and kind of drug to the characteristics of the patient. They then observe the expected response and adjust dosing to the specific requirements according to the difference between observed response, expected response and the context of the surgery and the patient. The approach above can be achieved because on one hand quantification technology has made significant advances allowing the anaesthesiologist to measure almost any effect by using noninvasive, continuous measuring systems. On the other the knowledge on the relations between dosing, concentration, biophase dynamics and effect as well as detection of variability sources has been achieved as being the benchmark specialty for pharmacokinetic-pharmacodynamic (PKPD) modelling. The aim of the review is to revisit the most common PKPD models applied in the field of anaesthesia (i.e. effect compartmental, turnover, drug-receptor binding and drug interaction models) through representative examples. The effect compartmental model has been widely used in this field and there are multiple applications and examples. The use of turnover models has been limited mainly to describe respiratory effects. Similarly, cases in which the dissociation process of the drug-receptor complex is slow compared with other processes relevant to the time course of the anaesthetic effect are not frequent in anaesthesia, where in addition to a rapid onset, a fast offset of the response is required. With respect to the characterization of PD drug interactions different response surface models are discussed. Relevant applications that have changed the way modern anaesthesia is practiced are also provided.

An exploration of remifentanil-propofol combinations that lead to a loss of response to esophageal instrumentation, a loss of responsiveness, and/or onset of intolerable ventilatory depression

BACKGROUND

Remifentanil and propofol are increasingly used for short-duration procedures in spontaneously breathing patients. In this setting, it is preferable to block the response to moderate stimuli while avoiding loss of responsiveness (LOR) and intolerable ventilatory depression (IVD). In this study, we explored selected effects of combinations of remifentanil-propofol effect-site concentrations (Ces) that lead to a loss of response to esophageal instrumentation (EI), LOR, and/or onset of IVD. A secondary aim was to use these observations to create response surface models for each effect measure. We hypothesized that (1) in a large percentage of volunteers, selected remifentanil and propofol Ces would allow EI but avoid LOR and IVD, and (2) the drug interaction for these effects would be synergistic.

METHODS

Twenty-four volunteers received escalating target-controlled remifentanil and propofol infusions over ranges of 0 to 6.4 ng · mL(-1) and 0 to 4.3 μg · mL(-1), respectively. At each set of target concentrations, responses to insertion of a blunt end bougie into the midesophagus (40 cm), level of responsiveness, and respiratory rate were recorded. From these data, response surface models of loss of response to EI and IVD were built and characterized as synergistic, additive, or antagonistic. A previously published model of LOR was used.

RESULTS

Of the possible 384 assessments, volunteers were unresponsive to EI at 105 predicted remifentanil-propofol Ces; in 30 of these, volunteers had no IVD; in 30, volunteers had no LOR; and in 9, volunteers had no IVD or LOR. Many other assessments over the same concentration ranges, however, did have LOR and/or IVD. The combinations that allowed EI and avoided IVD and/or LOR primarily clustered around remifentanil-propofol Ces ranging from 0.8 to 1.6 ng · mL(-1) and 1.5 to 2.7 μg · mL(-1), respectively, and to a lesser extent approximately 3.0 to 4.0 ng · mL(-1) and 0.0 to 1.1 μg · mL(-1), respectively. Models of loss of response to EI and IVD both demonstrated a synergistic interaction between remifentanil and propofol.

CONCLUSION

Selected remifentanil-propofol concentration pairs, especially higher propofol-lower remifentanil concentration pairs, can block the response to EI while avoiding IVD in spontaneously breathing volunteers. It is, however, difficult to block the response to EI and avoid both LOR and IVD. It may be necessary to accept some discomfort and blunt rather than block the response to EI to consistently avoid LOR and IVD.

Response surface model predictions of emergence and response to pain in the recovery room: An evaluation of patients emerging from an isoflurane and fentanyl anesthetic

INTRODUCTION

Sevoflurane-remifentanil interaction models that predict responsiveness and response to painful stimuli have been evaluated in patients undergoing elective surgery. Preliminary evaluations of model predictions were found to be consistent with observations in patients anesthetized with sevoflurane, remifentanil, and fentanyl. This study explored the feasibility of adapting the predictions of sevoflurane-remifentanil interaction models to an isoflurane-fentanyl anesthetic. We hypothesized that model predictions adapted for isoflurane and fentanyl are consistent with observed patient responses and are similar to the predictions observed in our previous work with sevoflurane-remifentanil/fentanyl anesthetics.

METHODS

Twenty-five patients scheduled for elective surgery received a fentanyl-isoflurane anesthetic. Model predictions of unresponsiveness were recorded at emergence, and predictions of a response to noxious stimulus were recorded when patients first required analgesics in the recovery room. Model predictions were compared with observations with graphical and temporal analyses. Results were also compared with our previous predictions after the administration of a sevoflurane-remifentanil/fentanyl anesthetic.

RESULTS

Although patients were anesthetized, model predictions indicated a high likelihood that patients would be unresponsive (> or = 99%). After the termination of the anesthetic, model predictions of responsiveness well described the actual fraction of patients observed to be responsive during emergence. Half of the patients woke within 2 min of the 50% model-predicted probability of unresponsiveness; 70% woke within 4 min. Similarly, predictions of a response to a noxious stimulus were consistent with the number of patients who required fentanyl in the recovery room. Model predictions after the administration of an isoflurane-fentanyl anesthetic were similar to model predictions after a sevoflurane-remifentanil/fentanyl anesthetic.

DISCUSSION

The results confirmed our study hypothesis; model predictions for unresponsiveness and no response to painful stimuli, adapted to isoflurane-fentanyl were consistent with observations. These results were similar to our previous study comparing model predictions and patient observations after a sevoflurane-remifentanil/fentanyl anesthetic.

Drug interaction: focusing on response surface models

Anesthesiologists have been aware of the importance of optimal drug combination long ago and performed many investigations about the combined use of anesthetic agents. There are 3 classes of drug interaction: additive, synergistic, and antagonistic. These definitions of drug interaction suggest that a zero interaction model should exist to be used as a reference in classifying the interaction of drug combinations. The Loewe additivity has been used as a universal reference model for classifying drug interaction. Most anesthetic drugs follow the sigmoid E(max) model (Hill equation); this model will be used for modeling response surface. Among lots of models for drug interaction in the anesthetic area, the Greco model, Machado model, Plummer model, Carter model, Minto model, Fidler model, and Kong model are adequate to be applied to the data of anesthetic drug interaction. A model with a single interaction parameter does not accept an inconsistency in the classes of drug interactions. To solve this problem, some researchers proposed parametric models which have a polynomial interaction function to capture synergy, additivity, and antagonism scattered all over the surface of drug combinations. Inference about truth must be based on an optimal approximating model. Akaike information criterion (AIC) is the most popular approach to choosing the best model among the aforementioned models. Whatever the good qualities of a chosen model, it is uncertain whether the chosen model is the best model. A more robust inference can be extracted from averaging several models that are considered relevant.