Etomidate and its Analogs:A Review of Pharmacokinetics and Pharmacodynamics

Etomidate is a hypnotic agent that is used for the induction of anesthesia. It produces its effect by acting as a positive allosteric modulator on the gamma-aminobutyric acid type A receptor and thus enhancing the effect of the inhibitory neurotransmitter gamma-aminobutyric acid. Etomidate stands out among other anesthetic agents by having a remarkably stable cardiorespiratory profile, producing no cardiovascular or respiratory depression. However, etomidate suppresses the adrenocortical axis by the inhibition of the enzyme 11 beta-hydroxylase. This makes the drug unsuitable for administration by a prolonged infusion. It also makes the drug unsuitable for administration to critically ill patients. Etomidate has relatively large volumes of distributions and is rapidly metabolized by hepatic esterases into an inactive carboxylic acid through hydrolyzation. Because of the decrease in popularity of etomidate, few modern extensive pharmacokinetic or pharmacodynamic studies exist. Over the last decade, several analogs of etomidate have been developed, with the aim of retaining its stable cardiorespiratory profile, whilst eliminating its suppressive effect on the adrenocortical axis. One of these molecules, ABP-700, was studied in extensive phase I clinical trials. These found that ABP-700 is characterized by small volumes of distribution and rapid clearance. ABP-700 is metabolized similarly to etomidate, by hydrolyzation into an inactive carboxylic acid. Furthermore, ABP-700 showed a rapid onset and offset of clinical effect. One side effect observed with both etomidate and ABP-700 is the occurrence of involuntary muscle movements. The origin of these movements is unclear and warrants further research

Clinical pharmacokinetics and pharmacodynamics of propofol

Propofol is an intravenous hypnotic drug that is used for induction and maintenance of sedation and general anaesthesia. It exerts its effects through potentiation of the inhibitory neurotransmitter -aminobutyric acid (GABA) at the GABA(A) receptor, and has gained widespread use due to its favourable drug effect profile. The main adverse effects are disturbances in cardiopulmonary physiology. Due to its narrow therapeutic margin, propofol should only be administered by practitioners trained and experienced in providing general anaesthesia. Many pharmacokinetic (PK) and pharmacodynamic (PD) models for propofol exist. Some are used to inform drug dosing guidelines, and some are also implemented in so-called target-controlled infusion devices, to calculate the infusion rates required for user-defined target plasma or effect-site concentrations. Most of the models were designed for use in a specific and well-defined patient category. However, models applicable in a more general population have recently been developed and published. The most recent example is the general purpose propofol model developed by Eleveld and colleagues. Retrospective predictive performance evaluations show that this model performs as well as, or even better than, PK models developed for specific populations, such as adults, children or the obese; however, prospective evaluation of the model is still required. Propofol undergoes extensive PK and PD interactions with both other hypnotic drugs and opioids. PD interactions are the most clinically significant, and, with other hypnotics, tend to be additive, whereas interactions with opioids tend to be highly synergistic. Response surface modelling provides a tool to gain understanding and explore these complex interactions. Visual displays illustrating the effect of these interactions in real time can aid clinicians in optimal drug dosing while minimizing adverse effects. In this review, we provide an overview of the PK and PD of propofol in order to refresh readers' knowledge of its clinical applications, while discussing the main avenues of research where significant recent advances have been made

Acute and life-threatening remifentanil overdose resulting from the misuse of a syringe pump.

In the perioperative setting, syringe pumps are frequently used. They guarantee constant plasma levels of hypnotics, opioids, cardiovascular medication, insulin or other drugs. We present a case in which an inadvertent rapid intravenous injection of 2 mg remifentanil occurred due to the misuse of a syringe pum

Autonomous systems in anesthesia : where do we stand in 2020? A narrative review

As most of us are aware, almost every facet of our society is becoming, for better or worse, progressively more technology-dependent. Technological advancement has made autonomous systems, also known as robots, an integral part of our life in several fields, including medicine. The application of robots in anesthesia could be classified into 3 types of robots. The first ones are pharmacological robots. These robots are based on closed-loop systems that allow better-individualized anesthetic drug titration for optimal homeostasis during general anesthesia and sedation. Recent evidence also demonstrates that autonomous systems could control hemodynamic parameters proficiently outperforming manual control in the operating room. The second type of robot is mechanical. They enable automated motorized reproduction of tasks requiring high manual dexterity level. Such robots have been advocated to be more accurate than humans and, thus, could be safer for the patient. The third type is a cognitive robot also known as decision support system. This type of robot is able to recognize crucial clinical situation that requires human intervention. When these events occur, the system notifies the attending clinician, describes relevant related clinical observations, proposes pertinent therapeutic options and, when allowed by the attending clinician, may even administer treatment. It seems that cognitive robots could increase patients' safety. Robots in anesthesia offer not only the possibility to free the attending clinicians from repetitive tasks but can also reduce mental workload allowing them to focus on tasks that require human intelligence such as analytical and clinical approach, lifesaving decision-making capacity, and interpersonal interaction. Nevertheless, further studies have yet to be done to test the combination of these 3 types of robots to maintain simultaneously the homeostasis of multiple biological variables and to test the safety of such combination on a large-scale population

Qualitative development and content validation of the "SPART" model:a focused ethnography study of observable diagnostic and therapeutic activities in the emergency medical services care process

Abstract Background Clinical reasoning is a crucial task within the Emergency Medical Services (EMS) care process. Both contextual and cognitive factors make the task susceptible to errors. Understanding the EMS care process’ structure could help identify and address issues that interfere with clinical reasoning. The EMS care process is complex and only basically described. In this research, we aimed to define the different phases of the process and develop an overarching model that can help detect and correct potential error sources, improve clinical reasoning and optimize patient care. Methods We conducted a focused ethnography study utilizing non-participant video observations of real-life EMS deployments combined with thematic analysis of peer interviews. After an initial qualitative analysis of 7 video observations, we formulated a tentative conceptual model of the EMS care process. To test and refine this model, we carried out a qualitative, thematic analysis of 28 video-recorded cases. We validated the resulting model by evaluating its recognizability with a peer content analysis utilizing semi-structured interviews. Results Based on real-life observations, we were able to define and validate a model covering the distinct phases of an EMS deployment. We have introduced the acronym “SPART” to describe ten different phases: Start, Situation, Prologue, Presentation, Anamnesis, Assessment, Reasoning, Resolution, Treatment, and Transfer. Conclusions The “SPART” model describes the EMS care process and helps to understand it. We expect it to facilitate identifying and addressing factors that influence both the care process and the clinical reasoning task embedded in this process

Mechanism-based pharmacodynamic model for propofol haemodynamic effects in healthy volunteers☆

Background: The adverse haemodynamic effects of the intravenous anaesthetic propofol are well known, yet few empirical models have explored the dose-response relationship. Evidence suggests that hypotension during general anaesthesia is associated with postoperative mortality. We developed a mechanism-based model that quantitatively characterises the magnitude of propofol-induced haemodynamic effects during general anaesthesia. Methods: Mean arterial pressure (MAP), heart rate (HR) and pulse pressure (PP) measurements were available from 36 healthy volunteers who received propofol in a step-up and step-down fashion by target-controlled infusion using the Schnider pharmacokinetic model. A mechanistic pharmacodynamic model was explored based on the Snelder model. To benchmark the performance of this model, we developed empirical models for MAP, HR, and PP. Results: The mechanistic model consisted of three turnover equations representing total peripheral resistance (TPR), stroke volume (SV), and HR. Propofol-induced changes were implemented by E-max models on the zero-order production rates of the turnover equations for TPR and SV. The estimated 50% effective concentrations for propofol-induced changes in TPR and SV were 2.96 and 0.34 mu g ml(-1), respectively. The goodness-of-fit for the mechanism-based model was indistinguishable from the empirical models. Simulations showed that predictions from the mechanism-based model were similar to previously published MAP and HR observations. Conclusions: We developed a mechanism-based pharmacodynamic model for propofol-induced changes in MAP, TPR, SV, and HR as a potential approach for predicting haemodynamic alterations