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

Comparison of patient-controlled analgesia and sedation (PCAS) with remifentanil and propofol versus total intravenous anesthesia (TIVA) with midazolam, fentanyl, and propofol for colonoscopy

BACKGROUND

Colonoscopy is a commonly performed gastroenterological procedure in patients associated with anxiety and pain. Various approaches have been used to provide sedation and analgesia during colonoscopy, including patient-controlled analgesia and sedation (PCAS). This study aims to evaluate the feasibility and efficiency of PCAS administered with propofol and remifentanil for colonoscopy.

METHODS

This randomized controlled trial was performed in an authorized and approved endoscopy center. A total of 80 outpatients were recruited for the colonoscopy studies. Patients were randomly allocated into PCAS and total intravenous anesthesia (TIVA) groups. In the PCAS group, the dose of 0.1 ml/kg/min of the mixture was injected after an initial bolus of 3 ml mixture (1 ml containing 3 mg of propofol and 10 μg of remifentanil). Each 1 ml of bolus was delivered with a lockout time of 1 min. In the TIVA group, patients were administered fentanyl 1 μg/kg, midazolam 0.02 mg/kg, and propofol (dosage titrated). Cardiorespiratory parameters and auditory evoked response index were continuously monitored during the procedure. The recovery from anesthesia was assessed using the Aldrete scale and the Observer's Assessment of Alertness/Sedation Scale. The Visual Analogue Scale was used to assess the satisfaction of patients and endoscopists.

RESULTS

No statistical differences were observed in the Visual Analogue Scale scores of the patients (9.58 vs 9.50) and the endoscopist (9.43 vs 9.30). A significant decline in the mean arterial blood pressure, heart rate, and auditory evoked response index parameters was recorded in the TIVA group (P < 0.05). The recovery time was significantly shorter in the PCAS group than in the TIVA group (P = 0.00).

CONCLUSION

The combination of remifentanil and propofol could provide sufficient analgesia, better hemodynamic stability, lighter sedation, and faster recovery in the PCAS group of patients compared with the TIVA group.

Logistic Regression Is Non-Inferior to the Response Surface Model in Patient Response Prediction of Video-Assisted Thoracoscopic Surgery

Response surface models (RSMs) are a new trend in modern anesthesia. RSMs have demonstrated significant applicability in the field of anesthesia. However, the comparative analysis between RSMs and logistic regression (LR) in different surgeries remains relatively limited in the current literature. We hypothesized that using a total intravenous anesthesia (TIVA) technique with the response surface model (RSM) and logistic regression (LR) would predict the emergence from anesthesia in patients undergoing video-assisted thoracotomy surgery (VATS). This study aimed to prove that LR, like the RSM, can be used to improve patient safety and achieve enhanced recovery after surgery (ERAS). This was a prospective, observational study with data reanalysis. Twenty-nine patients (American Society of Anesthesiologists (ASA) class II and III) who underwent VATS for elective pulmonary or mediastinal surgery under TIVA were enrolled. We monitored the emergence from anesthesia, and the precise time point of regained response (RR) was noted. The influence of varying concentrations was examined and incorporated into both the RSM and LR. The receiver operating characteristic (ROC) curve area for Greco and LR models was 0.979 (confidence interval: 0.987 to 0.990) and 0.989 (confidence interval: 0.989 to 0.990), respectively. The two models had no significant differences in predicting the probability of regaining response. In conclusion, the LR model was effective and can be applied to patients undergoing VATS or other procedures of similar modalities. Furthermore, the RSM is significantly more sophisticated and has an accuracy similar to that of the LR model; however, the LR model is more accessible. Therefore, the LR model is a simpler tool for predicting arousal in patients undergoing VATS under TIVA with Remifentanil and Propofol.

Antinociceptive Agents as General Anesthetic Adjuncts: Supra-additive and Infra-additive Interactions

The hypothesis "General anesthesia consists of producing both loss of consciousness and the inhibition of noxious stimuli reaching the brain and causing arousal" was used as a basis for the review of published data on general anesthetic interactions with antinociceptive agents: opioids, α 2 adrenergic agonists, and systemic sodium channel blockers. This review is focused on a specific type of anesthetic interaction-the transformation of antinociceptive agents into general anesthetic adjuncts. The primary aim is to answer 2 questions. First, how does an antinociceptive agent transform the effect of an anesthetic in providing a certain component of anesthesia-hypnosis, immobility, or hemodynamic response to noxious stimulation? Second, does a combination of an anesthetic with an adjunct result in a simple summation of their respective effects or in a supra-additive or infra-additive interaction? The Medline database was searched for data describing the interactions of antinociceptive agents and general anesthetics. The following classes of antinociceptive agents were considered: opioids, α 2 adrenergic agonists, and systemic sodium channel blockers. Drugs used in combination with antinociceptive agents were general anesthetics and benzodiazepines. The following terms related to drug interactions were used: anesthetic interactions, synergy, antagonism, isobolographic analysis, response surface analysis, and fractional analysis. The interactions of antinociceptive agents with general anesthetics result in a decrease of general anesthetic requirements, which differ for each of the components of general anesthesia: hypnosis, immobility, and hemodynamic response to noxious stimulation. Most studies of the nature of anesthetic interactions are related to opioid-general anesthetic combinations, and their conclusions usually confirm supra-additivity.

Effects of remifentanil on brain responses to noxious stimuli during deep propofol sedation

BACKGROUND

The safety of anaesthesia has improved as a result of better control of anaesthetic depth. However, conventional monitoring does not inform on the nature of nociceptive processes during unconsciousness. A means of inferring the quality of potentially painful experiences could derive from analysis of brain activity using neuroimaging. We have evaluated the dose effects of remifentanil on brain response to noxious stimuli during deep sedation and spontaneous breathing.

METHODS

Optimal data were obtained in 26 healthy subjects. Pressure stimulation that proved to be moderately painful before the experiment was applied to the thumbnail. Functional MRI was acquired in 4-min periods at low (0.5 ng ml^-1), medium (1 ng ml^-1), and high (1.5 ng ml^-1) target plasma concentrations of remifentanil at a stable background infusion of propofol adjusted to induce a state of light unconsciousness.

RESULTS

At low remifentanil doses, we observed partial activation in brain areas processing sensory-discriminative and emotional-affective aspects of pain. At medium doses, relevant changes were identified in structures highly sensitive to general brain arousal, including the brainstem, cerebellum, thalamus, auditory and visual cortices, and the frontal lobe. At high doses, no significant activation was observed.

CONCLUSIONS

The response to moderately intense focal pressure in pain-related brain networks is effectively eliminated with safe remifentanil doses. However, the safety margin in deep sedation-analgesia would be narrowed in minimising not only nociceptive responses, but also arousal-related biological stress.

Pharmacodynamic modeling of moderate sedation and rationale for dosing using midazolam, propofol and alfentanil

PURPOSE

Regulations have broadened to allow moderate sedation administration for gastrointestinal endoscopy by non-anesthesia personnel. The line between moderate and deep sedation is ambiguous. Deep sedation offers patient comfort as well as greater safety concerns. Unintended deep sedation can occur if drug interactions are overlooked. We present a pharmacodynamic model for moderate sedation using midazolam, alfentanil and propofol. The model is suitable for training and devising rationales for appropriate dosing.

METHODS

The study consists of two parts: modeling and validation. In modeling, patients scheduled for esophagogastroduodenoscopy (EGD) or colonoscopy sedation are enrolled. The modified observer's assessment of alertness/sedation (MOAA/S) score < 4 is defined as loss of response to represent moderate sedation. Two patient groups receiving bronchoscopy or endoscopic retrograde cholangiopancreatography (ERCP) are used for validation. Model performance is assessed by receiver operating characteristic (ROC) curves and area under the curve (AUC). Simulations are performed to demonstrate how the model is used to rationally determine drug regimen for moderate sedation.

RESULTS

Interaction between propofol and alfentanil is stronger than the other pairwise combinations. Additional synergy is observed with three drugs. ROC AUC is 0.83 for the modeling group, and 0.96 and 0.93 for ERCP and bronchoscopy groups respectively. Model simulation suggests that 1 mg midazolam, 250 µg alfentanil and propofol maximally benefits from drug interactions and suitable for moderate sedation.

CONCLUSION

We demonstrate the accurate prediction of a three-drug response surface model for moderate sedation and simulation suggests a rational dosing strategy for moderate sedation with midazolam, alfentanil and propofol.

Comparison Effects of Propofol-Dexmedetomidine versus Propofol-Remifentanil for Endoscopic Ultrasonography: A Prospective Randomized Comparative Trial

Objective. To compare the effects of propofol-dexmedetomidine versus propofol-remifentanil for endoscopic ultrasonography (EUS). Design, Setting, and Participants. A single-center, randomized trial from August 20, 2020 to August 20, 2021, in patients undergoing EUS. Interventions. Propofol-dexmedetomidine (PD) versus propofol-remifentanil (PR). Outcome Measures. The primary outcome was the endoscopist satisfaction level. The secondary outcomes included patient satisfaction, the incidence of adverse events, induction time, and time to achieve postanesthesia discharge score (PADS) ≥9. Methods. Total of 200 patients were enrolled and randomized into PD and PR groups. A bolus dose of 0.5 μg/kg dexmedetomidine was injected intravenously for 5 min. Subsequently, a continuous infusion of 0.5 μg/kg/h for the PD group. Remifentanil was continuously infused at 1.5 μg/kg/h for the PR group. A bolus dose of 1 mg/kg propofol was administered to both groups and then continuously infused. Results. The endoscopist satisfaction level was higher in the PR group than in the PD group ( $P=0.009$ ). Patient satisfaction was not significantly different between the groups ( $P=0.738$ ). No patients required mask ventilation or tracheal intubation in both groups. All patients were relatively hemodynamically stable. The incidence of body movements during the procedure in the PD group was higher than in the PR group ( $P=0.035$ ). The induction time and time taken to achieve PADS ≥9 in the PD group were longer than in the PR group ( $P<0.05$ ). Conclusions. PR sedation can increase the satisfaction level of the endoscopist by providing faster induction time and lower body movement and that of the patient by achieving faster PADS than PD sedation. Trial registration number: http://www.chictr.org.cn (ChiCTR2000034987).

Simulation-Based Gastrointestinal Endoscopy Sedations: A Novel Validation to Multidrug Pharmacodynamic Modeling

Pharmacodynamic models have described the interactions between anesthetics. Applying the models to clinical practice is still problematic due to inherent limitations: 1. modeling conditions are different from practice. 2. One model can only describe one endpoint. To tackle these, we propose a new method of model validation for recovery and intraprocedural sedation adequacy with a three-drug pharmacodynamic model using six published clinical studies that contain midazolam, opioid, and propofol. Mean drug dose, intraprocedural sedation level, procedure, and recovery time are extracted from each study. Simulated drug regimens are designed to best approximate study conditions. A published deep sedation model is used for simulation. Model-predicted recovery time and intraprocedural sedation scores are compared with the original clinical study outcomes. The model successfully predicted recovery times in eight out of nine regimens. Lower doses of midazolam are associated with faster recovery. Model prediction of intraprocedural sedation level was compatible with the clinical studies in five out of seven regimens. The three-drug pharmacodynamic model describes the course of gastrointestinal endoscopy sedations from clinical studies well. Model predictions are consistent with the results from clinical studies. The approach implies that large scale validation can be performed repeatedly.

Adding Low-Dose Propofol to Limit Anxiety during Target-Controlled Infusion of Remifentanil for Gastrointestinal Endoscopy: Respiratory Issues and Safety Recommendations

Backgroundand Objectives: Remifentanil-based sedation is one of many protocols proposed for endoscopy procedures in spontaneous ventilation, alone or in combination with propofol. However, the effect of these small doses of propofol on the efficacy and safety of remifentanil target-controlled infusion (TCI) deserves to be examined in this context. The objective of this study was to assess the adverse respiratory and cardiovascular effects of small boluses of propofol combined with remifentanil, in comparison with remifentanil alone, and balanced with the quality of sedation and recovery. Materials andMethods: This was an observational bicenter study, representing a subgroup of a larger study describing remifentanil-based procedural sedation. In center 1, patients scheduled for gastrointestinal (GI) endoscopy had remifentanil TCI alone. In center 2, patients had a 10 mg propofol bolus before TCI and other boluses were allowed during the procedure. Remifentanil TCI was started at a target of 2 ng/mL then adapted by 0.5 ng/mL steps according to patient response to endoscopy stimulations. Results: Center 1 included 29 patients, while center 2 included 60 patients. No difference was found in the patients’ characteristics, incidence of success, average remifentanil consumption, or cardiovascular variables. Light sedation was achieved when propofol was added. The incidence of respiratory events, such as bradypnea, desaturation < 90%, and apnea requiring rescue maneuvers, were significantly higher with propofol. Conclusions: Adding propofol boluses to a remifentanil TCI for GI endoscopy ensures light sedation that may be necessary for anxiolysis but increases respiratory events, even after administration of small-dose boluses. Its safety is acceptable if the procedure is performed in an equipped environment with sedation providers trained to manage respiratory events and drugs titrated to minimal doses.

Efficacy and safety of remifentanil for endoscopic ultrasound-guided tissue acquisition: a single center retrospective study

BACKGROUND

Remifentanil is a rapid onset and rapid recovery opioid. The combination of remifentanil and propofol for deep sedation decreases the incidents of movement, cough, and hiccup. We evaluated the efficacy and safety of remifentanil during endoscopic ultrasound-guided tissue acquisition.

METHODS

We retrospectively reviewed patients in whom endoscopic ultrasound-guided tissue acquisition was performed for solid mass lesions of the upper gastrointestinal tract and adjacent organs. All patients were premedicated with midazolam (2 mg), and target-controlled infusion of propofol, opioid, and Bispectral Index (BIS) monitoring were administered as necessary to maintain moderate-to-deep sedation. The opioids used were a bolus of alfentanil or remifentanil infusion. The discharge time, consumption of propofol and opioid, adverse events, diagnostic accuracy, and sensitivity and specificity for malignancy, were compared.

RESULTS

Tissue acquisition was achieved in 123 patients (alfentanil group, n = 64; remifentanil group, n = 59). The discharge time of the remifentanil group (16.5 ± 3.2 min) was significantly shorter than that of the alfentanil group (19.0 ± 4.9 min, P = 0.001). The consumption of propofol, adverse events, diagnostic accuracy, sensitivity, and specificity for malignancy in the alfentanil group were not significantly different from those in the remifentanil group.

CONCLUSIONS

Use of alfentanil or remifentanil for target-controlled infusion of propofol-BIS monitoring can provide good sedative and diagnostic quality for endoscopic ultrasound-guided tissue acquisition. However, remifentanil resulted in faster recovery than alfentanil.

Response surface model comparison and combinations for remifentanil and propofol in describing response to esophageal instrumentation and adverse respiratory events

BACKGROUND

The primary aim of this essay was to explore the best fitting model in remifentanil-propofol combined administrations during esophageal instrumentation (EI) from five distinct response surface models. The secondary aim was to combine the models to give appropriate effect-site drug concentrations (Ces) range with maximal comfort and safety.

METHODS

The Greco, reduced Greco, Minto, Scaled C50 Hierarchy and Fixed C50 Hierarchy models were constructed to fit four drug effects: loss of response to esophageal instrumentation (LREI), loss of response to esophageal instrumentation revised (LREIR), intolerable ventilatory depression (IVD) and respiratory compromise (RC). Models were tested by chi-square statistical test and evaluated with Akaike Information Criterion (AIC). Model prediction performance were measured by successful prediction rate (SPR) and three prediction errors.

RESULTS

The reduced Greco model was the best fitting model for LREI and RC, and the Minto model was the best fitting model for LREIR and IVD. The SPRs of reduced Greco model for LREI and RC were 81.76% and 79.81%. The SPRs of Minto model for LREIR and IVD were 80.32% and 80.12%. Overlay of the reduced Greco model for LREI and Minto model for IVD offered visual aid for guidance in drug administration.

CONCLUSIONS

Using proper response surface model to fit different drug effects will describe the interactions between anesthetic drugs better. Combining response surface models to select the more reliable effect-site drug concentrations range can be used to guide clinical drug administration with greater safety and provide an improvement of anesthesia precision.

Thermodynamic Interpretation of a Machine-Learning-Based Response Surface Model and Its Application to Pharmacodynamic Synergy between Propofol and Opioids

Propofol and fentanyl are commonly used agents for the induction of anesthesia, and are often associated with hemodynamic disturbances. Understanding pharmacodynamic impacts is vital for parasympathetic and sympathetic tones during the anesthesia induction period. Inspired by the thermodynamic interaction between drug concentrations and effects, we established a machine-learning-based response surface model (MLRSM) to address this predicament. Then, we investigated and modeled the biomedical phenomena in the autonomic nervous system. Our study prospectively enrolled 60 patients, and the participants were assigned to two groups randomly and equally. Group 1 received propofol first, followed by fentanyl, and the drug sequence followed an inverse procedure in Group 2. Then, we extracted and analyzed the spectrograms of electrocardiography (ECG) and pulse photoplethysmography (PPG) signals after induction of propofol and fentanyl. Eventually, we utilized the proposed MLRSM to evaluate the relationship between anesthetics and the integrity/balance of sympathetic and parasympathetic activity by employing the power of high-frequency (HF) and low-frequency (LF) bands and PPG amplitude (PPGA). It is worth emphasizing that the proposed MLRSM exhibits a similar mathematical form to the conventional Greco model, but with better computational performance. Furthermore, the MLRSM has a theoretical foundation and flexibility for arbitrary numbers of drug combinations. The modeling results are consistent with the previous literature. We employed the bootstrap algorithm to inspect the results’ consistency and measure the various statistical fluctuations. Then, the comparison between the modeling and the bootstrapping results was used to validate the statistical stability and the feasibility of the proposed MLRSM.

A Response Surface Analysis of the Combination of Dexmedetomidine and Sufentanil for Attenuating the Haemodynamic Response to Endotracheal Intubation

Purpose

Dexmedetomidine combined with opioids has been extensively used to blunt cardiovascular responses to endotracheal intubation. To determine their interaction, we aimed to develop a response surface model between dexmedetomidine and sufentanil.

Methods

One hundred and twenty patients undergoing scheduled gynaecological surgery were recruited. According to a simulation of slice design, patients received different dose pairs of dexmedetomidine (0 to 1.1 μg/kg) and sufentanil (.1 to .5 μg/kg). The mean arterial blood pressure and heart rate of patients were recorded just before endotracheal intubation, immediately after intubation, and during the first 3 min after intubation. The primary outcomes were haemodynamic changes. The full dose–response relationship between dexmedetomidine and sufentanil was analysed using a logit model.

Results

This response surface model revealed that the interaction between dexmedetomidine and sufentanil was additive. The dose pairs that could effectively attenuate the haemodynamic response to endotracheal intubation primarily ranged from .3 to .4 μg/kg and .5 to 1.1 μg/kg for sufentanil and dexmedetomidine, respectively.

Conclusion

When used propofol as the main hypnotic drug during anaesthesia induction, dexmedetomidine could effectively reduce the requirement of sufentanil in an additive manner. However, it is not an effective drug for ablating the cardiovascular response to endotracheal intubation when used alone. The clinical trial registry. The trial registry name: Chinese Clinical Trial Registry. Registration number: ChiCTR1800015273. URL: http://www.chictr.org.cn

Induction and maintenance of procedural sedation in adults: focus on remimazolam injection

Introduction: Procedural sedation (PS) is a humane way to help patients get through painful medical procedures by the administration of sedative drugs combined with analgesics. However, each of the currently used medications has certain shortcomings, urging the search for a new drug. Remimazolam, a novel benzodiazepine, is an ultra-short-acting hypnotic agent invented out of the 'soft drug' development.Areas covered: This presented review provides an overview of the drugs used in clinical practice for the induction and maintenance of procedural sedation in adults, focusing on the newly investigated benzodiazepine remimazolam. Literature search was conducted using the MEDLINE and ClinicalTrial.gov databases from January 2007 to December 2020.Expert opinion: Based on the reported clinical trials so far, remimazolam has demonstrated its effectiveness and safety with promising properties including rapid onset, short duration of action, predictable and consistent recovery profile, metabolism almost unaffected by liver or renal function, with non or minimal cardiorespiratory depression, and availability with a reversal drug. With marketing approval received recently, remimazolam is expected to have a place in the practice for procedural sedation in the near future if its efficacy and safety are further confirmed by more clinical trials and post-market analyses.

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.

Opioid and propofol pharmacodynamics modeling during brain mapping in awake craniotomy

BACKGROUND

Awake craniotomy (AC) is performed to identify cerebral language center. The challenge of anesthesia is to maintain a calm, comfortable, and cooperative patient during the mapping phase. Response surface models (RSMs) are multidrug modeling algorithms. In this pharmacodynamic study, we investigate the first use of RSM with bispectral index (BIS) to predict patient's response to name calling (RNC) and wakefulness (complete neurological tests) during AC.

METHODS

The study is performed in two phases. We prospectively enrolled 40 patients who received video-assisted thoracoscopic surgery (VATS) using propofol and fentanyl as the modeling group. Effect-site concentrations (Ce) and BIS values were recorded and a RSM is built from the data set. We verified the RSM retrospectively in AC patients, designated as the validation group. Corresponding BIS values were analyzed for RNC and wakefulness.

RESULTS

A total of 155 data sets of propofol Ce, fentanyl Ce, and BIS pairs were available for modeling. The range of propofol and fentanyl Ce were 0 to 9.95 μg/mL and 0 to 3.69 ng/mL, respectively. Observed BIS ranged from 21 to 98. The model identified an additive interaction between propofol and an opioid. RNC at BIS 64 is predicted by the model and 70 is required for wakefulness.

CONCLUSION

RSM built from VATS patients is verified with a separate group of AC patient. The BIS target advised for RSM-predicted wakefulness is 70. The model illustrates the timeline to wakefulness during AC under propofol and an opioid. It has implications in guiding, dosing, and estimation of time to wakefulness with propofol and an opioid.

Optimizing intraoperative administration of propofol, remifentanil, and fentanyl through pharmacokinetic and pharmacodynamic simulations to increase the postoperative duration of analgesia

Titrating an intraoperative anesthetic to achieve the postoperative goals of rapid emergence and prolonged analgesia can be difficult because of inter-patient variability and the need to provide intraoperative sedation and analgesia. Modeling pharmacokinetics and pharmacodynamics of anesthetic administrations estimates drug concentrations and predicted responses to stimuli during anesthesia. With utility of these PK/PD models we created an algorithm to optimize the intraoperative dosing regimen. We hypothesized the optimization algorithm would find a dosing regimen that would increase the postoperative duration of analgesia, not increase the time to emergence, and meet the intraoperative requirements of sedation and analgesia. To evaluate these hypotheses we performed a simulation study on previously collected anesthesia data. We developed an algorithm to recommend different intraoperative dosing regimens for improved post-operative results. To test the post-operative results of the algorithm we tested it on previously collected anesthesia data. An anesthetic dataset of 21 patients was obtained from a previous study from an anesthetic database at the University of Utah. Using the anesthetic records from these surgeries we modeled 21 patients using the same patient demographics and anesthetic requirements as the dataset. The anesthetic was simulated for each of the 21 patients with three different dosing regimens. The three dosing regimens are: from the anesthesiologist as recorded in the dataset (control group), from the algorithm in the clinical scenario one (test group), and from the algorithm in the clinical scenario two (test group). We created two clinical scenarios for the optimization algorithm to perform; one with normal general anesthesia constraints and goals, and a second condition where a delayed time to emergence is allowed to further maximize the duration of analgesia. The algorithm was evaluated by comparing the post-operative results of the control group to each of the test groups. Comparing results between the clinical scenario 1 dosing to the actual dosing showed a median increase in the duration of analgesia by 6 min and the time to emergence by 0.3 min. This was achieved by decreasing the intraoperative remifentanil infusion rate, increased the fentanyl dosing regimen, and not changing the propofol infusion rate. Comparing results between the clinical scenario 2 dosing to the actual dosing showed a median increase in the duration of analgesia by 26 min and emergence by 1.5 min. To dosing regimen from clinical scenario 2 greatly increased the fentanyl dosing regimen and greatly decreased the remifentanil infusion rate with no change to the propofol infusion rate. The results from this preliminary analysis of the optimization algorithm appear to imply that it can operate as intended. However a clinical study is warranted to determine to what extent the optimization algorithm determined optimal dosing regimens can maximize the postoperative duration of analgesia without delaying the time to emergence in a clinical setting.

Previously published drug interaction models predict loss of response for transoesophageal echocardiography sedation well but not response to oesophageal instrumentation

Response surface models (RSMs) were used to predict effects of multiple drugs interactions. Our study was aimed to validate accuracy of the previous published volunteer models during transoesophageal echocardiography (TEE). This is a cross-sectional study with 20 patients scheduled for transesophageal echocardiography in Taipei Veterans General Hospital, Taiwan. Effect-site concentration pairs of alfentanil and propofol were recorded and converted to equivalent remifentanil and propofol effect-site concentrations. Observer’s Assessment of Alertness/Sedation (OAA/S) scores were assessed every 2 minutes. Using these data, previous published models of loss of response (LOR), intolerable ventilatory depression (IVD), and loss of response to esophageal instrumentation (LREI) were then estimated. Accuracy of prediction is assessed by calculating the difference between the true response and the model-predicted probability. Clinical events such as interruption of TEE were recorded. The average procedure time was 11 minutes. Accuracy for prediction of LOR and LREI is 63.6% and 38.5%, respectively. There were four patients experienced desaturation for less than 1 minute, which were not predicted by IVD model, and one interruption of TEE due to involuntary movement. The previous published drug-interaction RSMs predict LOR well but not LREI for TEE sedation. Further studies using response surface methodology are needed to improve quality for TEE sedation and clinical implementation.

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.

The Myth of Rescue Reversal in "Can't Intubate, Can't Ventilate" Scenarios

BACKGROUND

An unanticipated difficult airway during induction of anesthesia can be a vexing problem. In the setting of can't intubate, can't ventilate (CICV), rapid recovery of spontaneous ventilation is a reasonable goal. The urgency of restoring ventilation is a function of how quickly a patient's hemoglobin oxygen saturation decreases versus how much time is required for the effects of induction drugs to dissipate, namely the duration of unresponsiveness, ventilatory depression, and neuromuscular blockade. It has been suggested that prompt reversal of rocuronium-induced neuromuscular blockade with sugammadex will allow respiratory activity to recover before significant arterial desaturation. Using pharmacologic simulation, we compared the duration of unresponsiveness, ventilatory depression, and neuromuscular blockade in normal, obese, and morbidly obese body sizes in this life-threatening CICV scenario. We hypothesized that although neuromuscular function could be rapidly restored with sugammadex, significant arterial desaturation will occur before the recovery from unresponsiveness and/or central ventilatory depression in obese and morbidly obese body sizes.

METHODS

We used published models to simulate the duration of unresponsiveness and ventilatory depression using a common induction technique with predicted rates of oxygen desaturation in various size patients and explored to what degree rapid reversal of rocuronium-induced neuromuscular blockade with sugammadex might improve the return of spontaneous ventilation in CICV situations.

RESULTS

Our simulations showed that the duration of neuromuscular blockade was longer with 1.0 mg/kg succinylcholine than with 1.2 mg/kg rocuronium followed 3 minutes later by 16 mg/kg sugammadex (10.0 vs 4.5 minutes). Once rocuronium neuromuscular blockade was completely reversed with sugammadex, the duration of hemoglobin oxygen saturation >90%, loss of responsiveness, and intolerable ventilatory depression (a respiratory rate of ≤4 breaths/min) were dependent on the body habitus and duration of oxygen administration. There is a high probability of intolerable ventilatory depression that extends well beyond the time when oxygen saturation decreases <90%, especially in obese and morbidly obese patients. If ventilatory rescue is inadequate, oxygen desaturation will persist in the latter groups, despite full reversal of neuromuscular blockade. Depending on body habitus, the duration of intolerable ventilatory depression after sugammadex reversal may be as long as 15 minutes in 5% of individuals.

CONCLUSIONS

The clinical management of CICV should focus primarily on restoration of airway patency, oxygenation, and ventilation consistent with the American Society of Anesthesiologist's practice guidelines for management of the difficult airway. Pharmacologic intervention cannot be relied upon to rescue patients in a CICV crisis.

A previously published propofol-remifentanil response surface model does not predict patient response well in video-assisted thoracic surgery

Modern anesthesia usually employs a hypnotic and an analgesic to produce synergistic sedation and analgesia. Two remifentanil-propofol interaction response surface models were used to predict sedation using Observer's Assessment of Alertness/Sedation (OAA/S) scores; one predicts an OAA/S <2 and the other <4. We hypothesized that both models would predict regained responsiveness (RR) after video-assisted thoracic surgery (VATS) to reduce total anesthesia time and make early extubation clinically relevant. We included 30 patients undergoing VATS received total intravenous anesthesia (TIVA) combined with thoracic epidural anesthesia (TEA). Pharmacokinetic profiles were calculated using Tivatrainer. Model predictions were compared with observations to evaluate the accuracy and precision of emergence model predictions. The mean (standard deviation) differences between when a patient responded to their name and the time when the model predicted a 50% probability of patient response were 30.80 ± 17.77 and 13.71 ± 11.35 minutes for the OAA/S <2 model and <4 model, respectively. Both models had a limited ability to predict patient response in our patients. Both models identified target concentration pairs predicting time of RR in volunteers and some elective surgeries, but another model of epidural and intravenous anesthetic combinations may be needed to predict time of RR after VATS under TIVA with TEA.

Pregabalin Has Analgesic, Ventilatory, and Cognitive Effects in Combination with Remifentanil

Background

Pregabalin is widely used perioperatively. The authors explored the effects of pregabalin, remifentanil, and their combination on experimental pain, ventilatory, and cognitive function.

Methods

In a randomized, double-blinded crossover study, 12 volunteers received (1) pregabalin + placebo, (2) placebo + remifentanil, (3) pregabalin + remifentanil, and (4) placebo + placebo. Pregabalin 150 mg/placebo was administered twice orally. After baseline, remifentanil/placebo was given as effect-site target-controlled infusion (TCI): 0.6, 1.2, and 2.4 ng/ml. Pain during cold pressor test was scored on visual analog scale (0 to 100 mm). Ventilation was measured by spirometry and cognition tested with Color-Word Interference and Rapid Information Processing tests.

Results

Pain intensity after placebo was (mean) 72 mm (95% CI, 62 to 83). Pregabalin reduced pain score by −10 mm (−14 to −7, P &lt; 0.001). Remifentanil had dose-dependent analgesic effect, reducing pain score by −47 mm (−54 to −39, P &lt; 0.001) on highest TCI level, whereas pregabalin + remifentanil exerted additive effect, reducing pain score by −57 mm (−64 to −50, P &lt; 0.001). Respiratory depression was potentiated by adding pregabalin to remifentanil; end-tidal carbon dioxide was 39.3 mmHg (37.2 to 41.3) with placebo, increased 1.8 mmHg (−0.9 to 4.6, P = 0.4) with pregabalin, 10.1 mmHg (4.9 to 15.4, P &lt; 0.001) with remifentanil, and 16.4 mmHg (11.3 to 21.5, P &lt; 0.001) with pregabalin + remifentanil on highest TCI level. The combination pregabalin + remifentanil, but not either drug alone, adversely affected all cognitive tests.

Conclusions

The combination of pregabalin and remifentanil had additive analgesic effects, pregabalin potentiated remifentanil ventilatory depression, and the combination adversely affected cognition. These results question the clinical benefit of the combination compared with higher doses of opioids.

Pharmacodynamic interaction models in pediatric anesthesia

Pharmacokinetic (PK) and pharmacodynamic (PD) models are important tools for summarizing drug dose, concentration, and effect relationships. Co-administration of drugs may alter PK and PD relationships. Traditional methods of evaluating PD interactions include using isoboles, shifts in dose-response curves, or interaction indices based on parameters of potency derived from separate monotherapy and combination therapy analyses. These methods provide an estimation of the magnitude of effect for dose or concentration combinations, but they do not inform us on the time course of that effect, or its associated variability. A better way to investigate PD interactions is to use modeling, and to take advantage of the benefits of population analyses. A population analysis is a statistical method in which a model describing the typical (or population) response, and the variability between individuals within that population, is developed. Models for monotherapy, derived using a population approach, can be combined and extended to incorporate PD interactions between two or more drugs. The purpose of this article was to provide a general road map for understanding and interpreting PD interaction models, including the 'response surface' models. Several types of response surface models exist, and here we review these with examples taken from the literature. We also consider current and future applications for this type of analysis for clinical anesthesia and pediatrics.

Response surface models in the field of anesthesia: A crash course

Drug interaction is fundamental in performing anesthesia. A response surface model (RSM) is a very useful tool for investigating drug interactions. The methodology appeared many decades ago, but did not receive attention in the field of anesthesia until the 1990s. Drug investigations typically start with pharmacokinetics, but it is the effects on the body clinical anesthesiologists really care about. Typically, drug interactions are divided into additive, synergistic, or infra-additive. Traditional isobolographic analysis or concentration-effect curve shifts are limited to a single endpoint. Response surface holds the complete package of isobolograms and concentration effect curves in one equation for a given endpoint, e.g., loss of response to laryngoscopy. As a pharmacodynamic tool, RSM helps anesthesiologists guide their drug therapy by navigating the surface. We reviewed the most commonly used models: (1) the Greco model; (2) Reduced Greco model; (3) Minto model; and (4) the Hierarchy models. Each one has its unique concept and strengths. These models served as groundwork for researchers to modify the formula to fit their drug of interest. RSM usually work with two drugs, but three-drug models can be constructed at the expense of greatly increasing the complexity. A wide range of clinical applications are made possible with the help of pharmacokinetic simulation. Pharmacokinetic-pharmcodynamic modeling using the RSMs gives anesthesiologists the versatility to work with precision and safe drug interactions. Currently, RSMs have been used for predicting patient responses, estimating wake up time, pinpointing the optimal drug concentration, guide therapy with respect to patient's well-being, and aid in procedures that require rapid patient arousal such as awake craniotomy or Stagnara wake-up test. There is no other model that is universally better than the others. Researches are encouraged to find the best fitting model for different occasions with an objective measure.

Sedation-analgesia with propofol and remifentanil: concentrations required to avoid gag reflex in upper gastrointestinal endoscopy

BACKGROUND

The purpose of this study was to identify optimal target propofol and remifentanil concentrations to avoid a gag reflex in response to insertion of an upper gastrointestinal endoscope.

METHODS

Patients presenting for endoscopy received target-controlled infusions (TCI) of both propofol and remifentanil for sedation-analgesia. Patients were randomized to 4 groups of fixed target effect-site concentrations: remifentanil 1 ng•mL (REMI 1) or 2 ng•mL (REMI 2) and propofol 2 μg•mL (PROP 2) or 3 μg•mL (PROP 3). For each group, the other drug (propofol for the REMI groups and vice versa) was increased or decreased using the "up-down" method based on the presence or absence of a gag response in the previous patient. A modified isotonic regression method was used to estimate the median effective Ce,50 from the up-down method in each group. A concentration-effect (sigmoid Emax) model was built to estimate the corresponding Ce,90 for each group. These data were used to estimate propofol bolus doses and remifentanil infusion rates that would achieve effect-site concentrations between Ce,50 and Ce,90 when a TCI system is not available for use.

RESULTS

One hundred twenty-four patients were analyzed. To achieve between a 50% and 90% probability of no gag response, propofol TCIs were between 2.40 and 4.23 μg•mL (that could be achieved with a bolus of 1 mg•kg) when remifentanil TCI was fixed at 1 ng•mL, and target propofol TCIs were between 2.15 and 2.88 μg•mL (that could be achieved with a bolus of 0.75 mg•kg) when remifentanil TCI was fixed at 2 ng•mL. Remifentanil ranges were 1.00 to 4.79 ng•mL and 0.72 to 3.19 ng•mL when propofol was fixed at 2 and 3 μg•mL, respectively.

CONCLUSIONS

We identified a set of propofol and remifentanil TCIs that blocked the gag response to endoscope insertion in patients undergoing endoscopy. Propofol bolus doses and remifentanil infusion rates designed to achieve similar effect-site concentrations can be used to prevent gag response when TCI is not available.

Using the Entropy of Tracheal Sounds to Detect Apnea during Sedation in Healthy Nonobese Volunteers

Background:

Undetected apnea can lead to severe hypoxia, bradycardia, and cardiac arrest. Tracheal sounds entropy has been proved to be a robust method for estimating respiratory flow, thus maybe a more reliable way to detect obstructive and central apnea during sedation.

Methods:

A secondary analysis of a previous pharmacodynamics study was conducted. Twenty volunteers received propofol and remifentinal until they became unresponsive to the insertion of a bougie into the esophagus. Respiratory flow rate and tracheal sounds were recorded using a pneumotachometer and a microphone. The logarithm of the tracheal sound Shannon entropy (Log-E) was calculated to estimate flow rate. An adaptive Log-E threshold was used to distinguish between the presence of normal breath and apnea. Apnea detected from tracheal sounds was compared to the apnea detected from respiratory flow rate.

Results:

The volunteers stopped breathing for 15 s or longer (apnea) 322 times during the 12.9-h study. Apnea was correctly detected 310 times from both the tracheal sounds and the respiratory flow. Periods of apnea were not detected by the tracheal sounds 12 times. The absence of tracheal sounds was falsely detected as apnea 89 times. Normal breathing was detected correctly 1,196 times. The acoustic method detected obstructive and central apnea in sedated volunteers with 95% sensitivity and 92% specificity.

Conclusions:

We found that the entropy of the acoustic signal from a microphone placed over the trachea may reliably provide an early warning of the onset of obstructive and central apnea in volunteers under sedation.