Johannes Pieter van Den Berg

Melatonin (MEL) is an endogenous hormone that regulates circadian rhythm, immune function and oxidative stress responses. Norepinephrine (NE), an endogenous catecholamine, increases blood pressure through the sympathetic nervous system and is commonly administered intraoperatively or in the clinically ill patient for hemodynamic support. Although endogenous NE is known to stimulate MEL synthesis, the effects of exogenous intravenous NE on plasma MEL concentration, particularly under general anaesthesia (GA), remain poorly characterised. This study examined the influence of intravenous NE on plasma MEL concentrations in healthy volunteers, both awake and under general anaesthesia. A secondary analysis was conducted using data from a prospective, single‐centre, cross‐over study involving volunteers who received stepwise NE infusions while awake and under total intravenous general anaesthesia. Arterial blood samples were collected to determine plasma MEL and NE concentrations. Linear mixed‐effects modelling was used to assess the relationship between NE and MEL concentrations. A total of 36 healthy volunteers were enroled, yielding 417 MEL‐NE samples. Intravenous NE administration was significantly associated with higher plasma MEL concentration, corresponding to an estimated 26% increase in MEL per 1 standard‐deviation increase in NE concentration (Estimate = 0.230, p < 0.001). MEL concentrations were approximately 43% higher in the awake phase compared to GA (Estimate = 0.356, p < 0.001). GA did not significantly modify the NE‐MEL association (Estimate = −0.02877, p = 0.528). Substantial positive correlation was observed between baseline MEL concentrations and the magnitude of the response to NE administration ( r = 0.74). In conclusion, intravenous NE increases plasma MEL concentrations in both awake and anaesthetised individuals. Substantial interindividual variation in MEL response suggests underlying physiological differences. Future studies should explore the long‐term effects of NE administration on MEL concentrations. Trial Registration: The study is registered in the Dutch Trial Register (NL9312).

Target-controlled infusion (TCI) systems, originally developed for intravenous drug administration of anesthetic drugs, enable precise drug delivery based on pharmacokinetic-pharmacodynamic (PKPD) models. While widely used in the operating room, their application in the intensive care unit (ICU) remains limited despite the complexity of drug dosing in critically ill patients. This scoping review evaluates existing evidence on the use of TCI systems in ICU settings, focusing on sedation, analgesia, and antibiotic administration. A systematic literature search was conducted in Medline and the Cochrane Library up to August 2024. Studies involving adult ICU patients receiving TCI for any drug were included. Data were extracted on study design, PKPD models, performance metrics, and clinical endpoints. A total of 281 studies were identified; 14 focused on sedatives, particularly propofol and remifentanil, using the Marsh and Minto models. TCI was associated with more stable sedation, improved titration, and fewer adverse events. Evidence on dexmedetomidine and midazolam was limited. Only three studies explored antibiotic TCI, mainly for vancomycin and cefepime, showing potential but lacking robust clinical validation. In conclusion, while current findings are promising, the evidence base supporting TCI—especially in the context of newer, generalized pharmacokinetic models and antibiotics—remains insufficient, and its broader application requires further clinical research and model validation.

Post-induction hypotension (MAP < 65 mmHg) occurs frequently and is usually caused by the cardiovascular adverse effects of the anaesthetic induction drugs used. We hypothesize that a clinically significant difference in the incidence and severity of hypotension will be found when different doses of propofol and remifentanil are used for induction of anaesthesia. Methods: This is a secondary analysis of a randomised controlled trial wherein four groups (A-D) of patients received one out of four different combinations of propofol and remifentanil, titrated to a predicted equipotency in probability of tolerance to laryngoscopy (PTOL) according to the Bouillon interaction model. In group A, a high dose of propofol and a low dose of remifentanil was administered, and across the groups this ratio was gradually changed until it was reversed in group D. Mean and systolic arterial blood pressure (MAP, SAP) were compared at four time points (T_baseline, T_post−bolus, T_3min, T_nadir) within and between groups Heart rate, bispectral index (BIS) and the incidence of hypotension were compared. Results: Data from 76 patients was used. At T_post−bolus a statistically significant lower MAP and SAP was found in group A versus D (p = 0.011 and p = 0.002). A significant higher heart rate was found at T_3min and T_nadir between groups A and B when compared to groups C and D (p = < 0.001 and p = 0.002). A significant difference in BIS value was found over all groups at T_3min and T_nadir (both p < 0.001). All other outcomes did not differ significantly between groups. Conclusion: Induction of anaesthesia with different predicted equipotent combinations of propofol and remifentanil did result in statistically different but clinically irrelevant differences in haemodynamic endpoints during induction of anaesthesia. Our study could not identify preferable drug combinations that decrease the risk for hypotension after induction, although they all yield a similar predicted PTOL.

This single blinded randomized controlled trial aims to assess whether the application of a Bayesian-adjusted Ce_PROP (effect-site of propofol) advisory tool leads towards a more stringent control of the cerebral drug effect during anaesthesia, using qCON as control variable. 100 patients scheduled for elective surgery were included and randomized into a control or intervention group (1:1 ratio). In the intervention group the advisory screen was made available to the clinician, whereas it was blinded in the control group. The settings of the target-controlled infusion pumps could be adjusted at any time by the clinician. Cerebral drug effect was quantified using processed EEG (CONOX monitor, Fresenius Kabi, Bad Homburg, Germany). The time of qCON between the desired range (35–55) during anaesthesia maintenance was defined as our primary end point. Induction parameters and recovery times were considered secondary end points and coefficient of variance of qCON and Ce_PROP was calculated in order to survey the extent of control towards the mean of the population. The desired range of qCON between 35 and 55 was maintained in 84% vs. 90% (p = 0.15) of the case time in the control versus intervention group, respectively. Secondary endpoints showed similar results in both groups. The coefficient of variation for Ce_PROP was higher in the intervention group. The application of the Bayesian-based Ce_PROP advisory system in this trial did not result in a different time of qCON between 35 and 55 (84 [21] vs. 90 [18] percent of the case time). Significant differences between groups were hard to establish, most likely due to a very high performance level in the control group. More extensive control efforts were found in the intervention group. We believe that this advisory tool could be a useful educational tool for novices to titrate propofol effect-site concentrations.

This narrative review intends to provide the anesthesiologist with the basic knowledge of the Bayesian concepts and should be considered as a tutorial for anesthesiologists in the concept of Bayesian statistics. The Bayesian approach represents the mathematical formulation of the idea that we can update our initial belief about data with the evidence obtained from any kind of acquired data. It provides a theoretical framework and a statistical method to use pre-existing information within the context of new evidence. Several authors have described the Bayesian approach as capable of dealing with uncertainty in medical decision-making. This review describes the Bayes theorem and how it is used in clinical studies in anesthesia and critical care. It starts with a general introduction to the theorem and its related concepts of prior and posterior probabilities. Second, there is an explanation of the basic concepts of the Bayesian statistical inference. Last, a summary of the applicability of some of the Bayesian statistics in current literature is provided, such as Bayesian analysis of clinical trials and PKPD modeling.