Bispectral index monitoring of the clinical effects of propofol closed-loop target-controlled infusion: Systematic review and meta-analysis of randomized controlled trials

Accuracy of closed-loop and open-loop propofol delivery systems by bispectral index monitoring in breast surgery patients: a prospective randomized trial

BACKGROUND

This randomized and controlled prospective study tested the hypothesis that closed-loop Target-Controlled Infusion (TCI) of propofol would be associated with better system performance when compared with open-loop controlled delivery of propofol.

METHODS

Patients scheduled for elective breast surgery were randomly assigned to two groups: a closed-loop group, in which propofol infusion was performed by a closed-loop TCI system that used the Bispectral Index (BIS) as a feedback parameter to titrate the rate of propofol infusion, and an open-loop group, in which propofol infusion was performed manually and guided by the bispectral index.

RESULTS

A total of 156 patients were recruited for this study (closed-loop group n = 79; open-loop group n = 77). The Global Score (GS) of the closed-loop group was lower than that of the open-loop group (34.3 and 42.2) (p = 0.044). The proportions of time with a BIS value between 40 and 60 were almost identical in the closed-loop group and the open-loop group (68.7 ± 10.6% and 66.7 ± 13.3%) (p = 0.318). The individuals in the closed-loop group consumed more propofol compared with those in the open-loop group (7.20 ± 1.65 mg.kg-1.h-1 vs. 6.03 ± 1.31 mg.kg-1.h-1, p < 0.001). No intraoperative recall, somatic events or adverse events occurred. No significant difference in heart rate was observed between the two groups (p = 0.169).

CONCLUSION

The closed-loop protocol was associated with lower BIS variability and lower out-of-range BIS values, at the cost of a greater consumption of propofol when compared to the open loop group.

REGISTER NUMBER

ChiCTR-INR-17010399.

Performance of closed-loop systems for intravenous drug administration: a systematic review and meta-analysis of randomised controlled trials

Closed-loop drug delivery systems are autonomous computers able to administer medication in response to changes in physiological parameters (controlled variables). While limited evidence suggested that closed-loop systems can perform better than manual drug administration in certain settings, this technology remains a research tool with an uncertain risk/benefit profile. Our aim was comparing the performance of closed-loop systems with manual intravenous drug administration in adults. We searched MEDLINE, CENTRAL, and Embase from inception until November 2022, without restriction to language. We assessed for inclusion randomised controlled trials comparing closed-loop and manual administration of intravenous drugs in adults, intraoperatively or in the Intensive Care Unit. We identified 32 studies on closed-loop administration of propofol, noradrenaline, phenylephrine, insulin, neuromuscular blockers, and vasodilators. Most studies were at moderate or high risk of bias. The results showed that closed-loop systems reduced the duration of blood pressure outside prespecified targets during noradrenaline (MD 14.9%, 95% CI 9.6-20.2%, I2 = 66.6%) and vasodilators administration (MD 7.4%, 95% CI 5.2-9.7%, I2 = 62.3%). Closed-loop systems also decreased the duration of recovery after propofol (MD 1.3 min, 95% CI 0.4-2.1 min, I2 = 58.6%) and neuromuscular blockers (MD 9.0 min, 95% CI 7.9-10.0 min, I2 = 0%). The certainty of the evidence was low or very low for most outcomes. Automatic technology may be used to improve the hemodynamic profile during noradrenaline and vasodilators administration and reduce the duration of postanaesthetic recovery.Registration: This systematic review was registered with PROSPERO (CRD42022336950) on the 7th of June 2022.

Model enhanced reinforcement learning to enable precision dosing: A theoretical case study with dosing of propofol

Extending the potential of precision dosing requires evaluating methodologies offering more flexibility and higher degree of personalization. Reinforcement learning (RL) holds promise in its ability to integrate multidimensional data in an adaptive process built toward efficient decision making centered on sustainable value creation. For general anesthesia in intensive care units, RL is applied and automatically adjusts dosing through monitoring of patient's consciousness. We further explore the problem of optimal control of anesthesia with propofol by combining RL with state-of-the-art tools used to inform dosing in drug development. In particular, we used pharmacokinetic-pharmacodynamic (PK-PD) modeling as a simulation engine to generate experience from dosing scenarios, which cannot be tested experimentally. Through simulations, we show that, when learning from retrospective trial data, more than 100 patients are needed to reach an accuracy within the range of what is achieved with a standard dosing solution. However, embedding a model of drug effect within the RL algorithm improves accuracy by reducing errors to target by 90% through learning to take dosing actions maximizing long-term benefit. Data residual variability impacts accuracy while the algorithm efficiently coped with up to 50% interindividual variability in the PK and 25% in the PD model's parameters. We illustrate how extending the state definition of the RL agent with meaningful variables is key to achieve high accuracy of optimal dosing policy. These results suggest that RL constitutes an attractive approach for precision dosing when rich data are available or when complemented with synthetic data from model-based tools used in model-informed drug development.

Effects of different depth of anesthesia on perioperative inflammatory reaction and hospital outcomes in elderly patients undergoing laparoscopic radical gastrectomy

Background

To investigate the effect of different depth of anesthesia on inflammatory factors and hospital outcomes in elderly patients undergoing laparoscopic radical gastrectomy for gastric cancer, in order to select an appropriate depth of anesthesia to improve the prognosis of patients undergoing surgery and improve the quality of life of patients.

Methods

A total of 80 elderly patients aged 65 and above who underwent laparoscopic radical gastrectomy in our hospital were by convenience sampling and randomly divided into two groups : 55 groups ( group H ) and 45 groups ( group L ), 40 cases in each group. The depth of anesthesia was maintained using a closed-loop target-controlled infusion system: the EEG bispectral index was set to 55 in the H group and 45 in the L group. Venous blood samples were collected 2 h (T2), 24 h (T3) and 72 h (T4) after the start of surgery. The intraoperative dosage of propofol and remifentanil, operation duration, postoperative PACU stay time, intraoperative consciousness occurrence, postoperative hospital stay and postoperative pulmonary inflammatory events were recorded.

Results

The patient characteristic of the two groups had no statistical difference and were comparable (P > 0.05). The intraoperative dosage of propofol in group H was lower than that in group L (P < 0.05). Compared with the L group, the plasma IL-6 and IL-10 concentrations in the H group were significantly increased at T2 (P < 0.05), and the plasma IL-10 concentration was significantly increased at T4 (P < 0.05). The plasma concentrations of IL-6 and IL-10 were higher in both groups at T2, T3 and T4 than at T1, while at T4, the concentration of TNF-α in group H was higher than at T1 (P < 0.05).

Conclusion

When the BIS value of the depth of anesthesia is 45, the perioperative release of inflammatory factors in elderly patients with laparoscopic radical gastrectomy for gastric cancer is less than BIS 55, and does not affect the prognosis.

The Median Effective Dose and Bispectral Index of Remimazolam Tosilate for Anesthesia Induction in Elderly Patients: An Up-and-Down Sequential Allocation Trial

Purpose

Remimazolam is a new type of ultrashort benzodiazepine drug with an unclear optimal dose for general anesthesia induction in elderly patients aged >60 years. Therefore, this study aimed to determine the effective dose of remimazolam tosilate induction and explore its correlation with the bispectral index (BIS).

Patients and Methods

A total of 42 elderly patients were divided into two age groups: 60–69 (group A) and 70–85 (group B) years. An initial dose of 0.1mg/kg(Group A) and 0.05 mg/kg(Group B) remimazolam tosilate was administered, and the Modified Observer’s Assessment of Alertness/Sedation scale was used to assess adequate responses. The dose was calculated using the up-and-down allocation technique based on the previous response. The sequential formula and probit regression model were used to calculate ED50 and BIS50. ED95 was determined using the probit regression model.

Results

The ED50 of remimazolam tosilate for anesthesia induction were 0.088 mg/kg (95% confidence interval [CI] 0.071–0.108) and 0.061 mg/kg (95% CI 0.053–0.069) in groups A and B, respectively. ED95 was 0.118 mg/kg (95% CI 0.103–0.649) and 0.090 mg/kg (95% CI 0.075–0.199) in groups A and B, respectively. The remimazolam tosilate administration could decrease BIS. BIS50 was 86.0 (95% CI 83.7–88.6) and 85.4 (95% CI 84.1–86.8) in groups A and B, respectively.

Conclusion

During the induction process, patients’ consciousness should be observed. The dose of remimazolam tosilate could be chosen after careful consideration of individual variations.

The effects of target-controlled infusion of lidocaine undergoing vocal cord polypectomy: A randomized controlled trial (CONSORT compliant)

BACKGROUND

The present study aimed to assess the efficacy and safety of general anesthesia-assisted target-controlled plasma infusion of lidocaine in patients with vocal cord polypectomy using a supporting laryngoscope.

METHODS

In total, 80 patients undergoing vocal cord polypectomy using a supporting laryngoscope were randomly divided into an intervention group and a control group; each group contained 40 subjects: both groups received general anesthesia; subjects in the intervention also received an additional 3 mg/L of lidocaine by target-controlled plasma infusion during induction and maintenance of anesthesia; heart rate (HR) mean arterial pressure (MAP), propofol and urapidil consumption (Uradil, which is a blood pressure drug that blocks alpha-1, is called Urapidi Hydrochloride Injection. It is produced by Germany, the enterprise name is Nycomed Deutschland GmbH, the import drug registration number is H20090715, and it is widely used in China), recovery time, and cough score (measured by Minogue et al's 5-grade scoring method) during extubation, and throat pain score (measured by visual analogue scale,[VAS]) after extubation and adverse events were recorded.

RESULTS

Significant differences were observed in HR (P < .05) and MAP (P < .05) immediately after intubation (T2), immediately after the operation starting to support laryngoscope exposure (T3), immediately after operation field adrenergic tampon hemostasis (T4), and 5 minutes after hemostasis (T5) between the 2 groups, and significant differences were also observed in HR (P < .05) before intubation (T1). Moreover, significant differences were observed in propofol consumption (P < .05), urapidil consumption (P < .05), cough score during extubation (P < .05), and throat pain score after extubation (P < .05). However, no significant difference was observed in the recovery time (P > .05). Furthermore, no adverse events were detected in either group.

CONCLUSION

The results of this study showed that target-controlled plasma infusion of lidocaine can reduce propofol consumption in patients undergoing vocal cord polypectomy by supporting laryngoscopy, and the hemodynamics are more stable and reduce the coughing reaction in the wake period and throat pain after extubation without adverse events.

Reinforcement learning as an innovative model-based approach: Examples from precision dosing, digital health and computational psychiatry

Model-based approaches are instrumental for successful drug development and use. Anchored within pharmacological principles, through mathematical modeling they contribute to the quantification of drug response variability and enables precision dosing. Reinforcement learning (RL)-a set of computational methods addressing optimization problems as a continuous learning process-shows relevance for precision dosing with high flexibility for dosing rule adaptation and for coping with high dimensional efficacy and/or safety markers, constituting a relevant approach to take advantage of data from digital health technologies. RL can also support contributions to the successful development of digital health applications, recognized as key players of the future healthcare systems, in particular for reducing the burden of non-communicable diseases to society. RL is also pivotal in computational psychiatry-a way to characterize mental dysfunctions in terms of aberrant brain computations-and represents an innovative modeling approach forpsychiatric indications such as depression or substance abuse disorders for which digital therapeutics are foreseen as promising modalities.