Refining Target-Controlled Infusion: An Assessment of Pharmacodynamic Target-Controlled Infusion of Propofol and Remifentanil Using a Response Surface Model of Their Combined Effects on Bispectral Index

Postoperative Sleep Quality of Insomnia Patients After TIVA Anesthesia: A Prospective Study

PURPOSE

The purpose of this study is to observe the postoperative sleep quality of insomnia patients undergoing laparoscopic gynecologic oncology surgery after total intravenous anesthesia.

DESIGN

Prospective study.

METHODS

We conducted a prospective, observational study in our hospital. All patients underwent propofol-remifentanil anesthesia without other sedative medications before or during the operation. Pittsburgh Sleep Quality Index (PSQI) scores of the baseline value, night-1 (the first night after surgery), night-3, night-5, and night-30 were observed.

FINDINGS

Sixty-nine female insomnia patients were allocated based on the results of the PSQI and the diagnostic criteria of insomnia. The PSQI global scores were respectively 6 (5-8), 5 (4-6), 5 (3-6), and 6 (5-7) on night-1, night-3, night-5, and night-30, significantly lower than the baseline 7 (6-8) (P < 0.05). The 5 components (subjective sleep quality, sleep latency, sleep duration, sleep efficiency and daytime dysfunction) had significant changes at different postoperative time points (P < 0.05). The daytime dysfunction could also be improved 1 month after the surgery (P < 0.05). In contrast, the variations of sleep disturbance and use of sleep medication had no statistical differences.

CONCLUSIONS

The sleep quality of female patients with insomnia was improved on the first night after surgery in the sides of sleep latency and daytime dysfunction, and the improvement could also be obtained 1 month after propofol-remifentanil general anesthesia.

A Transformer-Based Prediction Method for Depth of Anesthesia During Target-Controlled Infusion of Propofol and Remifentanil

Accurately predicting anesthetic effects is essential for target-controlled infusion systems. The traditional (PK-PD) models for Bispectral index (BIS) prediction require manual selection of model parameters, which can be challenging in clinical settings. Recently proposed deep learning methods can only capture general trends and may not predict abrupt changes in BIS. To address these issues, we propose a transformer-based method for predicting the depth of anesthesia (DOA) using drug infusions of propofol and remifentanil. Our method employs long short-term memory (LSTM) and gate residual network (GRN) networks to improve the efficiency of feature fusion and applies an attention mechanism to discover the interactions between the drugs. We also use label distribution smoothing and reweighting losses to address data imbalance. Experimental results show that our proposed method outperforms traditional PK-PD models and previous deep learning methods, effectively predicting anesthetic depth under sudden and deep anesthesia conditions.

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.

Predicting anesthetic infusion events using machine learning

Recently, research has been conducted to automatically control anesthesia using machine learning, with the aim of alleviating the shortage of anesthesiologists. In this study, we address the problem of predicting decisions made by anesthesiologists during surgery using machine learning; specifically, we formulate a decision making problem by increasing the flow rate at each time point in the continuous administration of analgesic remifentanil as a supervised binary classification problem. The experiments were conducted to evaluate the prediction performance using six machine learning models: logistic regression, support vector machine, random forest, LightGBM, artificial neural network, and long short-term memory (LSTM), using 210 case data collected during actual surgeries. The results demonstrated that when predicting the future increase in flow rate of remifentanil after 1 min, the model using LSTM was able to predict with scores of 0.659 for sensitivity, 0.732 for specificity, and 0.753 for ROC-AUC; this demonstrates the potential to predict the decisions made by anesthesiologists using machine learning. Furthermore, we examined the importance and contribution of the features of each model using Shapley additive explanations-a method for interpreting predictions made by machine learning models. The trends indicated by the results were partially consistent with known clinical findings.

Practicalities of Total Intravenous Anesthesia and Target-controlled Infusion in Children

Propofol administered in conjunction with an opioid such as remifentanil is used to provide total intravenous anesthesia for children. Drugs can be given as infusion controlled manually by the physician or as automated target-controlled infusion that targets plasma or effect site. Smart pumps programmed with pharmacokinetic parameter estimates administer drugs to a preset plasma concentration. A linking rate constant parameter (keo) allows estimation of effect site concentration. There are two parameter sets, named after the first author describing them, that are commonly used in pediatric target-controlled infusion for propofol (Absalom and Kataria) and one for remifentanil (Minto). Propofol validation studies suggest that these parameter estimates are satisfactory for the majority of children. Recommended target concentrations for both propofol and remifentanil depend on the type of surgery, the degree of surgical stimulation, the use of local anesthetic blocks, and the ventilatory status of the patient. The use of processed electroencephalographic monitoring is helpful in pediatric total intravenous anesthesia and target-controlled infusion anesthesia, particularly in the presence of neuromuscular blockade.

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.

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.

Initiation of a High-Frequency Jet Ventilation Strategy for Catheter Ablation for Atrial Fibrillation: Safety and Outcomes Data

OBJECTIVES

The aim of the current investigation is to examine whether use of high-frequency jet ventilation (HFJV) during pulmonary vein isolation (PVI) performed with force-sensing catheters is associated with improved outcomes.

BACKGROUND

Catheter ablation is well established as therapy for symptomatic atrial fibrillation (AF). Reconnection following PVI is commonly observed during repeat ablation procedures. Technologies that may optimize catheter stability and lesion delivery include both force-sensing ablation catheters and HFJV.

METHODS

Patients undergoing PVI at Johns Hopkins Hospital were prospectively enrolled in a registry. The study compared procedural characteristics, adverse event rates, and 1-year procedural outcomes in patients undergoing PVI supported either by standard ventilation or HFJV. Patient and procedural aspects were otherwise constant.

RESULTS

Eighty-four HFJV patients and 84 matched control patients with 1-year outcome data were identified. Atrial arrhythmia recurrence occurred in 26 of 84 HFJV patients (31%) and 42 of 84 control patients (50%; p = 0.019). In patients with paroxysmal AF, arrhythmia recurrence in HFJV and control patients was 27.3% and 47.3%, respectively (p = 0.045). In patients with persistent AF, arrhythmia recurrence rates were not significantly different (37.9% in HFJV patients, 55.2% in control patients; p = 0.184). On multivariate analysis, HFJV was independently associated with improved freedom from arrhythmia recurrence. Vasopressor use during HFJV cases was significantly higher than during standard ventilation (79.7% vs. 22.4%; p = 0.001). Indices of catheter stability and contact force adequacy were significantly higher in the HFJV patients than in control patients. Complication rates in the 2 groups were similarly low.

CONCLUSIONS

Use of HFJV in patients undergoing PVI with radiofrequency force-sensing catheters is associated with improved outcomes, without appreciable increase in adverse procedural events.

Metabolic Profiles of Propofol and Fospropofol: Clinical and Forensic Interpretative Aspects

Propofol is an intravenous short-acting anesthetic widely used to induce and maintain general anesthesia and to provide procedural sedation. The potential for propofol dependency and abuse has been recognized, and several cases of accidental overdose and suicide have emerged, mostly among the health professionals. Different studies have demonstrated an unpredictable interindividual variability of propofol pharmacokinetics and pharmacodynamics with forensic and clinical adverse relevant outcomes (e.g., pronounced respiratory and cardiac depression), namely, due to polymorphisms in the UDP-glucuronosyltransferase and cytochrome P450 isoforms and drugs administered concurrently. In this work the pharmacokinetics of propofol and fospropofol with particular focus on metabolic pathways is fully reviewed. It is concluded that knowing the metabolism of propofol may lead to the development of new clues to help further toxicological and clinical interpretations and to reduce serious adverse reactions such as respiratory failure, metabolic acidosis, rhabdomyolysis, cardiac bradyarrhythmias, hypotension and myocardial failure, anaphylaxis, hypertriglyceridemia, renal failure, hepatomegaly, hepatic steatosis, acute pancreatitis, abuse, and death. Particularly, further studies aiming to characterize polymorphic enzymes involved in the metabolic pathway, the development of additional routine forensic toxicological analysis, and the relatively new field of ‘‘omics” technology, namely, metabolomics, can offer more in explaining the unpredictable interindividual variability.

Prediction of Bispectral Index during Target-controlled Infusion of Propofol and Remifentanil

Background

The discrepancy between predicted effect-site concentration and measured bispectral index is problematic during intravenous anesthesia with target-controlled infusion of propofol and remifentanil. We hypothesized that bispectral index during total intravenous anesthesia would be more accurately predicted by a deep learning approach.

Methods

Long short-term memory and the feed-forward neural network were sequenced to simulate the pharmacokinetic and pharmacodynamic parts of an empirical model, respectively, to predict intraoperative bispectral index during combined use of propofol and remifentanil. Inputs of long short-term memory were infusion histories of propofol and remifentanil, which were retrieved from target-controlled infusion pumps for 1,800 s at 10-s intervals. Inputs of the feed-forward network were the outputs of long short-term memory and demographic data such as age, sex, weight, and height. The final output of the feed-forward network was the bispectral index. The performance of bispectral index prediction was compared between the deep learning model and previously reported response surface model.

Results

The model hyperparameters comprised 8 memory cells in the long short-term memory layer and 16 nodes in the hidden layer of the feed-forward network. The model training and testing were performed with separate data sets of 131 and 100 cases. The concordance correlation coefficient (95% CI) were 0.561 (0.560 to 0.562) in the deep learning model, which was significantly larger than that in the response surface model (0.265 [0.263 to 0.266], P &lt; 0.001).

Conclusions

The deep learning model–predicted bispectral index during target-controlled infusion of propofol and remifentanil more accurately compared to the traditional model. The deep learning approach in anesthetic pharmacology seems promising because of its excellent performance and extensibility.

Model-based drug administration: current status of target-controlled infusion and closed-loop control

PURPOSE OF REVIEW

Drug administration might be optimized by incorporating pharmacokinetic-dynamic (PK/PD) principles and control engineering theories. This review gives an update of the actual status of target-controlled infusion (TCI) and closed-loop computer-controlled drug administration and the ongoing research in the field.

RECENT FINDINGS

TCI is becoming mature technology clinically used in many countries nowadays with proven safety. Nevertheless, changing populations might require adapting the established PK/PD models. As TCI requires accurate PK/PD models, new models have been developed which should now be incorporated into the pumps to allow more general use of this technology. Closed-loop administration of hypnotic drugs using an electro-encephalographic-derived-controlled variable has been well studied and has been shown to outperform manual administration. Computer administration for other drugs and fluids have been studied recently. Feasibility has been shown for systems controlling multiple components of anaesthesia, but more work is required to show clinical safety and efficiency.

SUMMARY

Evidence in the literature is increasing that TCI and closed-loop technology could assist the anaesthetists to optimize drug administration during anaesthesia.

Effects of remifentanil with or without midazolam pretreatment on the 95% effective dose of propofol for loss of consciousness during induction: A randomized, clinical trial

BACKGROUND

Propofol is a rapid, efficient hypnotic agent with antiemetic effects. However, a high dosage is related to hemodynamic abnormalities such as hypotension and bradycardia. Pretreatment with remifentanil can decrease injection pain and stabilize hemodynamics during the induction period. Remifentanil or midazolam in combination with propofol can provide synergistic or additive effects during anesthesia induction. However, the hypnotic doses of propofol required in patients who receive pretreatment with remifentanil or midazolam remain unclear.

METHODS

Patients aged 20 to 50 years who were scheduled to undergo surgery under general anesthesia were enrolled in this study. The patients were randomized into 3 groups using a computer-generated randomization table. Patients in Group P (Propofol) received only propofol for loss of consciousness, those in Group PR (Propofol-Remifentanil) received remifentanil prior to propofol, and those in Group PMR (Propofol-Midazolam-Remifentanil) received remifentanil and midazolam prior to propofol. After propofol administration, loss of both the eyelash reflex and verbal response represented success. The 95% effective dose of propofol for loss of consciousness in each group, which was the primary outcome, was determined using a modified biased coin up-and-down method.

RESULTS

A total of 124 patients were initially enrolled. Of these, 4 were excluded, and the remaining 120 patients were randomized to each (n = 40) of the 3 groups. The 95% effective dose of propofol for loss of consciousness was 1.74 , 1.38, and 0.92 mg/kg in Groups P, PR, and PMR, respectively. Blood pressure decreased at 2 minutes after propofol administration in all the groups. However, compared with Group P, Groups PR and PMR exhibited a significant decrease in blood pressure.

CONCLUSIONS

The effective dose of propofol for loss of consciousness could be decreased by 21% and 47% when remifentanil pretreatment was used without and with midazolam, respectively. However, the decrease in blood pressure was greater with pretreatment than sole propofol use. These findings suggest that the combination of remifentanil with or without midazolam may have no benefit on hemodynamic stability during induction using propofol.

TRIAL REGISTRATION

NCT02536690 (clinicaltrials.gov).

Drug-induced sleep endoscopy with target-controlled infusion using propofol and monitored depth of sedation to determine treatment strategies in obstructive sleep apnea

BACKGROUND

Drug-induced sleep endoscopy (DISE) has become an important diagnostic examination tool in the treatment decision process for surgical therapies in the treatment of obstructive sleep apnea (OSA). Currently, there is a variety of regimes for the performance of DISE, which renders comparison and assessment across results difficult. It remains unclear how the different regimes influence the findings of the examination and the resulting conclusions and treatment recommendations. This study aimed to investigate the correlation between increasing levels of sedation (i.e., light, medium, and deep) induced by propofol using a target-controlled infusion (TCI) pump, with the obstruction patterns at the levels of the velum, oropharynx, tongue base, and epiglottis (i.e., VOTE classification). A second goal was the establishment of a sufficient sedation level to enable a reliable decision regarding treatment recommendations.

MATERIAL AND METHODS

Forty-three patients with OSA underwent a DISE procedure using propofol TCI. Three levels of sedation were defined, depending on entropy levels and assessment of sedation: light sedation, medium sedation, and deep sedation. The evaluation of the upper airway at each level, with increasing sedation, was documented using the VOTE classification. The elapsed time at which each assessment was performed was recorded.

RESULTS

Upper airway changes occurred and were measured throughout the DISE procedure. Clinically useful determinations of airway closure occurred at medium sedation; this level of sedation was most probably achieved with a blood propofol concentration of 3.2 μg/ml. In all 43 patients, definite treatment decisions could be made at medium sedation level. Increasing sedation did not result in changes in the treatment decision.

CONCLUSIONS

Changes in upper airway collapse during DISE with propofol TCI occur at levels of medium sedation. Decisions regarding surgical treatment could be made at this level of sedation.

CLINICAL TRIAL NAME

Upper Airway Collapse in Patients with Obstructive Sleep Apnea Syndrome by Drug Induced Sleep Endoscopy (URL: https://clinicaltrials.gov/ct2/results?term=NCT02588300&Search=Search ) REGISTRATION NUMBER: NCT02588300.

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.