A Review of Modern Control Strategies for Clinical Evaluation of Propofol Anesthesia Administration Employing Hypnosis Level Regulation

Ilyas, Muhammad; Butt, Muhammad Fasih Uddin; Bilal, Muhammad; Kazemzad, Mahmood; Khaqan, Ali; Riaz, Raja Ali

doi:10.1155/2017/7432310

Cited by 25 publications

(11 citation statements)

References 51 publications

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“…Propofol is widely applied in the clinic as an intravenous anesthetic; however, it frequently causes hypotension at the time of induction of anesthesia ( 20 ), particularly in elderly and hypertension patients, whose cardiac cycle fluctuations are more obvious, and which may contribute to various conditions of the cardiovascular system, including arrhythmias, myocardial ischemia and myocardial infarction ( 21 ). The blood pressure in the circulatory system is dependent on blood volume, cardiac ejection and peripheral resistance.…”

Section: Discussionmentioning

confidence: 99%

Propofol‑induced vasodilation of mesenteric arterioles via BKCa channel and gap junction

Wan

Wang

et al. 2018

Exp Ther Med

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The present study aimed to investigate the role of propofol in mediating the vasomotor activity of the mesenteric arteriole (MA) of Sprague Dawley (SD) rats, and to elucidate the underlying mechanisms. The pressure myograph technique was used to examine the effect of different concentrations of propofol on the relaxation of blood vessels in the 2–3 mm MA segments freshly separated from the SD rats. The whole-cell patch-clamp technique was applied to observe the outward current of single vascular smooth muscle cells (VSMCs) obtained from the MAs of the SD rats. Furthermore, immunofluorescence was utilized to assess the expression of connexin (Cx) in the MAs of SD rats. The results indicated the following: i) Propofol relaxed the MA of SD rats in a concentration-dependent manner from 1×10−7 to 3×10−4 mol/l; ii) in the acutely dissociated VSMCs, propofol (1×10−7 to 3×10−4 mol/l) enhanced the outward current of VSMCs in a concentration-dependent manner; iii) the enhanced outward currents induced by propofol (1×10−5 mol/l) may be reversed by tetraethylammonium (TEA; 1 mmol/l), a calcium-activated K+ channel inhibitor; iv) the effect of propofol on the relaxation of the vasculature wAS reduced after perfusion with 1 mmol/l TEA; v) Cx40, Cx43 and Cx45 were expressed on the MA; 6) 18β-glycyrrhetintic acid and 2-aminoethoxydiphenyl borate, two types of gap junction blocker, inhibited the propofol-induced relaxation. The present study provides evidence that propofol relaxes the MA, which may be associated with its effect of enhancing the channel current of large-conductance calcium voltage-activated potassium channels, contributing to the K+ outflow and leading to VSMC hyperpolarization; the gap junction may facilitate the hyperpolarization, which may lead to vascular synchronized relaxation and thereby reduce the blood pressure.

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Section: Discussionmentioning

confidence: 99%

Propofol‑induced vasodilation of mesenteric arterioles via BKCa channel and gap junction

Wan

Wang

et al. 2018

Exp Ther Med

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“…Adequate dosing of anaesthetic drugs is required to avoid awareness, maintain homeostasis, and reduce postoperative discomfort and recovery times in the post-anaesthesia care unit [1]. This requires continuous monitoring of the patient's anaesthetic state, enabling the anaesthesiologist to adapt drug titration as needed.…”

Section: Introductionmentioning

confidence: 99%

Robust PID control of propofol anaesthesia: Uncertainty limits performance, not PID structure

González-Cava

Carlson

Troeng

et al. 2021

Computer Methods and Programs in Biomedicine

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Background and Objective: New proposals to improve the regulation of hypnosis in anaesthesia based on the development of advanced control structures emerge continuously. However, a fair study to analyse the real benefits of these structures compared to simpler clinically validated PID-based solutions has not been presented so far. The main objective of this work is to analyse the performance limitations associated with using a filtered PID controller, as compared to a high-order controller, represented through a Youla parameter.Methods: The comparison consists of a two-steps methodology. First, two robust optimal filtered PID controllers, considering the effect of the inter-patient variability, are synthesised. A set of 47 validated paediatric pharmacological models, identified from clinical data, is used to this end. This model set provides representative inter-patient variability Second, individualised filtered PID and Youla controllers are synthesised for each model in the set. For fairness of comparison, the same performance objective is optimised for all designs, and the same robustness constraints are considered. Controller synthesis is performed utilising convex optimisation and gradient-based methods relying on algebraic differentiation. The worst-case performance over the patient model set is used for the comparison.

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“…Later, when the BIS became the standard measure of patient sedation, a closed-loop control method was proposed with the goal of maintaining a constant BIS 19 . Specifically, there has been significant research on propofol control, and various methods have been proposed, including methods using target controlled infusion with PK/PD models and methods using proportional integral derivative, as described in the review by Ilyas et al 20 . Recent studies have proposed reinforcement learning methods that consider PK/PD models and use deep learning for reinforcement learning 21,22 .…”

Section: Introductionmentioning

confidence: 99%

Predicting Anesthetic Infusion Events Using Machine Learning

Miyaguchi

Takeuchi

Kashima

et al. 2021

Preprint

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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.

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A Review of Modern Control Strategies for Clinical Evaluation of Propofol Anesthesia Administration Employing Hypnosis Level Regulation

Cited by 25 publications

References 51 publications

Propofol‑induced vasodilation of mesenteric arterioles via BKCa channel and gap junction

Propofol‑induced vasodilation of mesenteric arterioles via BKCa channel and gap junction

Robust PID control of propofol anaesthesia: Uncertainty limits performance, not PID structure

Predicting Anesthetic Infusion Events Using Machine Learning

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