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Introduction: We previously reported models that characterized the synergistic interaction between remifentanil and sevoflurane in blunting responses to verbal and painful stimuli. This preliminary study evaluated the ability of these models to predict a return of responsiveness during emergence from anesthesia and a response to tibial pressure when patients required analgesics in the recovery room. We hypothesized that model predictions would be consistent with observed responses. We also hypothesized that under non-steady-state conditions, accounting for the lag time between sevoflurane effect-site concentration (Ce) and end-tidal (ET) concentration would improve predictions., Methods: Twenty patients received a sevoflurane, remifentanil, and fentanyl anesthetic. Two model predictions of responsiveness were recorded at emergence: an ET-based and a Ce-based prediction. Similarly, 2 predictions of a response to noxious stimuli were recorded when patients first required analgesics in the recovery room. Model predictions were compared with observations with graphical and temporal analyses., Results: While patients were anesthetized, model predictions indicated a high likelihood that patients would be unresponsive (> or = 99%). However, after termination of the anesthetic, models exhibited a wide range of predictions at emergence (1%-97%). Although wide, the Ce-based predictions of responsiveness were better distributed over a percentage ranking of observations than the ET-based predictions. For the ET-based model, 45% of the patients awoke within 2 min of the 50% model predicted probability of unresponsiveness and 65% awoke within 4 min. For the Ce-based model, 45% of the patients awoke within 1 min of the 50% model predicted probability of unresponsiveness and 85% awoke within 3.2 min. Predictions of a response to a painful stimulus in the recovery room were similar for the Ce- and ET-based models., Discussion: Results confirmed, in part, our study hypothesis; accounting for the lag time between Ce and ET sevoflurane concentrations improved model predictions of responsiveness but had no effect on predicting a response to a noxious stimulus in the recovery room. These models may be useful in predicting events of clinical interest but large-scale evaluations with numerous patients are needed to better characterize model performance.

Background: Part task training (PTT) focuses on dividing complex tasks into components followed by intensive concentrated training on individual components. Variable priority training (VPT) focuses on optimal distribution of attention when performing multiple tasks simultaneously with the goal of flexible allocation of attention. This study explored how principles of PTT and VPT adapted to anesthesia training would improve first-year anesthesiology residents' management of simulated adverse airway and respiratory events. The authors hypothesized that participants with PTT and VPT would perform better than those with standard training., Methods: Twenty-two first-year anesthesia residents were randomly divided into two groups and trained over 12 months. The control group received standard didactic and simulation-based training. The experimental group received similar training but with emphasis on PTT and VPT techniques. Participant ability to manage seven adverse airway and respiratory events were assessed before and after the training period. Performance was measured by the number of correct tasks, making a correct diagnosis, assessment of perceived workload, and an assessment of scenario comprehension., Results: Participants in both groups exhibited significant improvement in all metrics after a year of training. Participants in the experimental group were able to complete more tasks and answered more comprehension questions correctly. There was no difference in perceived workload or the number of correct diagnoses between groups., Conclusion: This study in part confirmed the study hypotheses. The results suggest that VPT and PTT are promising adjuncts to didactic and simulation-based training for management of adverse airway and respiratory events.

Introduction: In this study, we explored how a set of remifentanil-propofol response surface interaction models developed from data collected in volunteers would predict responses to events in patients undergoing elective surgery. Our hypotheses were that these models would predict a patient population's loss and return of responsiveness and the presence or absence of a response to laryngoscopy and the response to pain after surgery., Methods: Twenty-one patients were enrolled. Anesthesia consisted of remifentanil and propofol infusions and fentanyl boluses. Loss and return of responsiveness, responses to laryngoscopy, and responses to postoperative pain were assessed in each patient. Model predictions were compared with observed responses., Results: The loss of responsiveness model predicted that patients would become unresponsive 2.4 +/- 2.6 min earlier than observed. At the time of laryngoscopy, the laryngoscopy model predicted an 89% probability of no response to laryngoscopy and 81% did not respond. During emergence, the loss of responsiveness model predicted return of responsiveness 0.6 +/- 5.1 min before responsiveness was observed. The mean probability of no response to pressure algometry was 23% +/- 35% when patients required fentanyl for pain control., Discussion: This preliminary assessment of a series of remifentanil-propofol interaction models demonstrated that these models predicted responses to selected pertinent events during elective surgery. However, significant model error was evident during rapid changes in predicted effect-site propofol-remifentanil concentration pairs.

Background: Hypercapnia with hyperventilation shortens the time between turning off the vaporizer (1 MAC) and when patients open their eyes after isoflurane anesthesia by 62%., Methods: In the present study we tested whether a proportional shortening occurs with sevoflurane and desflurane., Results: Consistent with a proportional shortening, we found that hypercapnia with hyperventilation decreased recovery times by 52% for sevoflurane and 64% for desflurane (when compared with normal ventilation with normocapnia)., Conclusion: Concurrent hyperventilation to rapidly remove the anesthetic from the lungs and rebreathing to induce hypercapnia can significantly shorten recovery times and produce the same proportionate decrease for anesthetics that differ in solubility.

Background: To shorten emergence time after a procedure using volatile anesthesia, 78% of anesthesiologists recently surveyed used hyperventilation to rapidly clear the anesthetic from the lungs. Hyperventilation has not been universally adapted into clinical practice because it also decreases the Paco2, which decreases cerebral bloodflow and depresses respiratory drive. Adding deadspace to the patient's airway may be a simple and safe method of maintaining a normal or slightly increased Paco2 during hyperventilation., Methods: We evaluated the differences in emergence time in 20 surgical patients undergoing 1 MAC of isoflurane under mild hypocapnia (ETco2 approximately 28 mmHg) and mild hypercapnia (ETco2 approximately 55 mmHg). The minute ventilation in half the patients was doubled during emergence, and hypercapnia was maintained by insertion of additional airway deadspace to keep the ETco2 close to 55 mmHg during hyperventilation. A charcoal canister adsorbed the volatile anesthetic from the deadspace. Fresh gas flows were increased to 10 L/min during emergence in all patients., Results: The time between turning off the vaporizer and the time when the patients opened their eyes and mouths, the time of tracheal extubation, and the time for normalized bispectral index to increase to 0.95 were faster whenever hypercapnic hyperventilation was maintained using rebreathing and anesthetic adsorption (P < 0.001). The time to tracheal extubation was shortened by an average of 59%., Conclusions: The emergence time after isoflurane anesthesia can be shortened significantly by using hyperventilation to rapidly clear the anesthetic from the lungs and CO2 rebreathing to induce hypercapnia during hyperventilation. The device should be considered when it is important to provide a rapid emergence, especially after surgical procedures where a high concentration of the volatile anesthetic was maintained right up to the end of the procedure, or where surgery ends abruptly and without warning.

Unlabelled: We studied the influence of hemorrhagic shock on the pharmacology of etomidate in swine. Sixteen swine were randomly assigned to control and shock groups. The shock group was bled to a mean arterial blood pressure of 50 mm Hg and held there until 30 mL/kg blood was removed. Etomidate 300 micro g x kg(-1) x min(-1) was infused for 10 min to both groups. Fifteen arterial samples were collected until 180 min after the infusion began to determine drug concentration. Pharmacokinetic variables for each group were estimated by using a three-compartment model. The bispectral index scale was used as a measure of drug effect. The pharmacodynamics were characterized by using a sigmoid inhibitory maximal effect model. The raw data revealed a 25% increase in the plasma etomidate concentration at the end of the 10-min infusion which resolved after termination of the infusion in the shock group. The pharmacokinetic analysis revealed subtle changes in the variable estimates between groups. The etomidate infusion produced a similar Bispectral Index Scale change in both groups. These results demonstrated that, unlike the influence of hemorrhagic shock on other sedative hypnotics and opioids, moderate hemorrhagic shock produced minimal changes in the pharmacokinetics and no change in the pharmacodynamics of etomidate., Implications: Hemorrhagic shock produced minimal changes in the pharmacokinetics and no change in the pharmacodynamics of etomidate in swine. These results suggest that, unlike other sedative hypnotics and opioids, minimal adjustment in the dose of etomidate is required to achieve the same drug effect during hemorrhagic shock.