Monitoring of sedation depth in intensive care unit by therapeutic drug monitoring? A prospective observation study of medical intensive care patients

Recommended dosages of analgesic and sedative drugs in intensive care result in a low incidence of potentially toxic blood concentrations

Background

Standard dosages of analgesic and sedative drugs are given to intensive care patients. The resulting range of blood concentrations and corresponding clinical responses need to be better examined. The purpose of this study was to describe daily dosages, measured blood concentrations, and clinical responses in critically ill patients. The purpose was also to contribute to establishing whole blood concentration reference values of the drugs investigated.

Methods

A descriptive study of prospectively collected data from 302 admissions to a general intensive care unit (ICU) at a university hospital. Ten drugs (clonidine, fentanyl, morphine, dexmedetomidine, ketamine, ketobemidone, midazolam, paracetamol, propofol, and thiopental) were investigated, and daily dosages recorded. Blood samples were collected twice daily, and drug concentrations were measured. Clinical responses were registered using Richmond agitation-sedation scale (RASS) and Numeric rating scale (NRS).

Results

Drug dosages were within recommended dose ranges. Blood concentrations for all 10 drugs showed a wide variation within the cohort, but only 3% were above therapeutic interval where clonidine (57 of 122) and midazolam (38 of 122) dominated. RASS and NRS were not correlated to drug concentrations.

Conclusion

Using recommended dose intervals for analgesic and sedative drugs in the ICU setting combined with regular monitoring of clinical responses such as RASS and NRS leads to 97% of concentrations being below the upper limit in the therapeutic interval. This study contributes to whole blood drug concentration reference values regarding these 10 drugs.

Pharmacokinetics, Pharmacodynamics, and Side Effects of Midazolam: A Review and Case Example

Midazolam, a short-acting benzodiazepine, is widely used to alleviate patient anxiety, enhance compliance, and aid in anesthesia. While its side effects are typically dose-dependent and manageable with vigilant perioperative monitoring, serious cardiorespiratory complications, including fatalities and permanent neurological impairment, have been documented. Prolonged exposure to benzodiazepines, such as midazolam, has been associated with neurological changes in infants. Despite attempts to employ therapeutic drug monitoring for optimal sedation dosing, its efficacy has been limited. Consequently, efforts are underway to identify alternative predictive markers to guide individualized dosing and mitigate adverse effects. Understanding these factors is crucial for determining midazolam's suitability for future administration, particularly after a severe adverse reaction. This article aims to elucidate the factors influencing midazolam's pharmacokinetics and pharmacodynamics, potentially leading to adverse events. Finally, a case study is presented to exemplify the complex investigation into the causative factors of midazolam-related adverse events.

The Clearance of Midazolam and Metabolites during Continuous Renal Replacement Therapy in Critically Ill Patients with COVID-19

INTRODUCTION

Midazolam-based continuous intravenous sedation in patients admitted to the intensive care unit (ICU) was a necessity during the COVID-19 pandemic. However, benzodiazepine-based sedation is associated with a high incidence of benzodiazepine-related delirium and additional days on mechanical ventilation. Due to the requirement of high midazolam doses in combination with the impaired renal clearance (CL) of the pharmacological active metabolite 1-OH-midazolam-glucuronide (10% compared to midazolam), ICU patients with COVID-19 and continuous renal replacement therapy (CRRT) were at risk of unintended prolonged sedation. Several CRRT-related factors may have influenced the delivered CL of midazolam and its metabolites. Therefore, the aim of the study was to identify and describe these CRRT-related factors.

METHODS

Pre-filter blood samples and ultrafiltrate samples were collected simultaneously. Midazolam, 1-OH-midazolam, and 1-OH-midazolam-glucuronide plasma samples were analyzed using an UPLC-MS/MS method. The prescribed CRRT dose was corrected for downtime and filter integrity using the urea ratio (urea concentration in effluent/urea concentration plasma). CL of midazolam and its metabolites were calculated with the delivered CRRT dose (corrected for downtime and saturation coefficient [SD]).

RESULTS

Three patients on continuous venovenous hemodialysis (CVVHD) and 2 patients on continuous venovenous hemodiafiltration (CVVHDF) were included. Midazolam, 1-OH-midazolam, and 1-OH-midazolam-glucuronide concentrations were 2,849 (0-6,700) μg/L, 153 (0-295) μg/L, and 27,297 (1,727-39,000) μg/L, respectively. The SD was 0.03 (0.02-0.03) for midazolam, 0.05 (0.05-0.06) for 1-OH-midazolam, and 0.33 (0.23-0.43) for 1-OH-midazolam-glucuronide. The delivered CRRT CL was 1.4 (0-1.7) mL/min for midazolam, 2.7 (0-3.5) mL/min for 1-OH-midazolam, and 15.7 (4.0-27.7) mL/min for 1-OH-midazolam-glucuronide.

CONCLUSIONS

Midazolam and 1-OH-midazolam were not removed during CVVHD and CVVHDF. However, 1-OH-midazolam-glucuronide was removed reasonably, approximately up to 43%. CRRT modality, filter integrity, and downtime affect this removal. These data imply a personalized titration of midazolam in critically ill patients with renal failure and awareness for the additional sedative effects of its active metabolites.

Hyperinflammation Reduces Midazolam Metabolism in Critically Ill Adults with COVID-19

BACKGROUND AND OBJECTIVE

Many patients treated for COVID-19 related acute respiratory distress syndrome in the intensive care unit are sedated with the benzodiazepine midazolam. Midazolam undergoes extensive metabolism by CYP3A enzymes, which may be inhibited by hyperinflammation. Therefore, an exaggerated proinflammatory response, as often observed in COVID-19, may decrease midazolam clearance. To develop a population pharmacokinetic model for midazolam in adult intensive care unit patients infected with COVID-19 and to assess the effect of inflammation, reflected by IL-6, on the pharmacokinetics of midazolam.

METHODS

Midazolam blood samples were collected once a week between March 31 and April 30 2020. Patients were excluded if they concomitantly received CYP3A4 inhibitors, CYP3A4 inducers and/or continuous renal replacement therapy. Midazolam and metabolites were analyzed with an ultra-performance liquid chromatography-tandem mass spectrometry method. A population pharmacokinetic model was developed, using nonlinear mixed effects modelling. IL-6 and CRP, markers of inflammation, were analyzed as covariates.

RESULTS

The data were described by a one-compartment model for midazolam and the metabolites 1-OH-midazolam and 1-OH-midazolam-glucuronide. The population mean estimate for midazolam clearance was 6.7 L/h (4.8-8.5 L/h). Midazolam clearance was reduced by increased IL-6 and IL-6 explained more of the variability within our patients than CRP. The midazolam clearance was reduced by 24% (6.7-5.1 L/h) when IL-6 increases from population median 116 to 300 pg/mL.

CONCLUSIONS

Inflammation, reflected by high IL-6, reduces midazolam clearance in critically ill patients with COVID-19. This knowledge may help avoid oversedation, but further research is warranted.

Electroencephalogram-Based Evaluation of Impaired Sedation in Patients with Moderate to Severe COVID-19 ARDS

The sedation management of patients with severe COVID-19 is challenging. Processed electroencephalography (pEEG) has already been used for sedation management before COVID-19 in critical care, but its applicability in COVID-19 has not yet been investigated. We performed this prospective observational study to evaluate whether the patient sedation index (PSI) obtained via pEEG may adequately reflect sedation in ventilated COVID-19 patients. Statistical analysis was performed by linear regression analysis with mixed effects. We included data from 49 consecutive patients. None of the patients received neuromuscular blocking agents by the time of the measurement. The mean value of the PSI was 20 (±23). The suppression rate was determined to be 14% (±24%). A deep sedation equivalent to the Richmond Agitation and Sedation Scale of −3 to −4 (correlation expected PSI 25−50) in bedside examination was noted in 79.4% of the recordings. Linear regression analysis revealed a significant correlation between the sedative dosages of propofol, midazolam, clonidine, and sufentanil (p < 0.01) and the sedation index. Our results showed a distinct discrepancy between the RASS and the determined PSI. However, it remains unclear to what extent any discrepancy is due to the electrophysiological effects of neuroinflammation in terms of pEEG alteration, to the misinterpretation of spinal or vegetative reflexes during bedside evaluation, or to other causes.

Association Between Processed Electroencephalogram-Based Objectively Measured Depth of Sedation and Cerebrovascular Response: A Systematic Scoping Overview of the Human and Animal Literature

Background: Current understanding of the impact that sedative agents have on neurovascular coupling, cerebral blood flow (CBF) and cerebrovascular response remains uncertain. One confounding factor regarding the impact of sedative agents is the depth of sedation, which is often determined at the bedside using clinical examination scoring systems. Such systems do not objectively account for sedation depth at the neurovascular level. As the depth of sedation can impact CBF and cerebral metabolism, the need for objective assessments of sedation depth is key. This is particularly the case in traumatic brain injury (TBI), where emerging literature suggests that cerebrovascular dysfunction dominates the burden of physiological dysfunction. Processed electroencephalogram (EEG) entropy measures are one possible solution to objectively quantify depth of sedation. Such measures are widely employed within anesthesia and are easy to employ at the bedside. However, the association between such EEG measures and cerebrovascular response remains unclear. Thus, to improve our understanding of the relationship between objectively measured depth of sedation and cerebrovascular response, we performed a scoping review of the literature.

Methods: A systematically conduced scoping review of the existing literature on objectively measured sedation depth and CBF/cerebrovascular response was performed, search multiple databases from inception to November 2020. All available literature was reviewed to assess the association between objective sedation depth [as measured through processed electroencephalogram (EEG)] and CBF/cerebral autoregulation.

Results: A total of 13 articles, 12 on adult humans and 1 on animal models, were identified. Initiation of sedation was found to decrease processed EEG entropy and CBF/cerebrovascular response measures. However, after this initial drop in values there is a wide range of responses in CBF seen. There were limited statistically reproduceable associations between processed EEG and CBF/cerebrovascular response. The literature body remains heterogeneous in both pathological states studied and sedative agent utilized, limiting the strength of conclusions that can be made.

Conclusions: Conclusions about sedation depth, neurovascular coupling, CBF, and cerebrovascular response are limited. Much further work is required to outline the impact of sedation on neurovascular coupling.

Negative drift of sedation depth in critically ill patients receiving constant minimum alveolar concentration of isoflurane, sevoflurane, or desflurane: a randomized controlled trial

Background

Intensive care unit (ICU) physicians have extended the minimum alveolar concentration (MAC) to deliver and monitor long-term volatile sedation in critically ill patients. There is limited evidence of MAC’s reliability in controlling sedation depth in this setting. We hypothesized that sedation depth, measured by the electroencephalography (EEG)-derived Narcotrend-Index (burst-suppression N_Index 0—awake N_Index 100), might drift downward over time despite constant MAC values.

Methods

This prospective single-centre randomized clinical study was conducted at a University Hospital Surgical Intensive Care Unit and included consecutive, postoperative ICU patients fulfilling the inclusion criteria. Patients were randomly assigned to receive uninterrupted inhalational sedation with isoflurane, sevoflurane, or desflurane. The end-expiratory concentration of the anaesthetics and the EEG-derived index were measured continuously in time-stamped pairs. Sedation depth was also monitored using Richmond-Agitation-Sedation-Scale (RASS). The paired t-test and linear models (bootstrapped or multilevel) have been employed to analyze MAC, N_Index and RASS across the three groups.

Results

Thirty patients were recruited (female/male: 10/20, age 64 ± 11, Simplified Acute Physiology Score II 30 ± 10). In the first 24 h, 21.208 pairs of data points (N_Index and MAC) were recorded. The median MAC of 0.58 ± 0.06 remained stable over the sedation time in all three groups. The t-test indicated in the isoflurane and sevoflurane groups a significant drop in RASS and EEG-derived N_Index in the first versus last two sedation hours. We applied a multilevel linear model on the entire longitudinal data, nested per patient, which produced the formula N_Index = 43 − 0.7·h (R² = 0.76), showing a strong negative correlation between sedation’s duration and the N_Index. Bootstrapped linear models applied for each sedation group produced: N_Index of 43–0.9, 45–0.8, and 43–0.4·h for isoflurane, sevoflurane, and desflurane, respectively. The regression coefficient for desflurane was almost half of those for isoflurane and sevoflurane, indicating a less pronounced time-effect in this group.

Conclusions

Maintaining constant MAC does not guarantee stable sedation depth. Thus, the patients necessitate frequent clinical assessments or, when unfeasible, continuous EEG monitoring. The differences across different volatile anaesthetics regarding their time-dependent negative drift requires further exploration.

Trial registration: NCT03860129.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13054-021-03556-y.

Continuous monitoring of propofol in human serum with fouling compensation by support vector classifier

We present a new method for electrochemical sensing, which compensates the fouling effect of propofol through machine learning (ML) model. Direct and continuous monitoring of propofol is crucial in the development of automatic systems for control of drug infusion in anaesthesiology. The fouling effect on electrodes discourages the possibility of continuous online monitoring of propofol since polymerization of the surface produces sensor drift. Several approaches have been proposed to limit the phenomenon at the biochemical interface; instead, here, we present a novel ML-based calibration procedure. In this paper, we analyse a dataset of 600 samples acquired through staircase cyclic voltammetry (SCV), resembling the scenario of continuous monitoring of propofol, both in PBS and in undiluted human serum, to demonstrate that ML-based model solves electrode fouling of anaesthetics. The proposed calibration approach is based on Gaussian radial basis function support vector classifier (RBF-SVC) that achieves classification accuracy of 98.9% in PBS, and 100% in undiluted human serum. The results prove the ability of the ML-based model to correctly classify propofol concentration in the therapeutic range between 1μM and 60μM with levels of 10μM, continuously up to ten minutes, with one sample every 30s.

Therapeutic Drug Monitoring Is a Feasible Tool to Personalize Drug Administration in Neonates Using New Techniques: An Overview on the Pharmacokinetics and Pharmacodynamics in Neonatal Age

Therapeutic drug monitoring (TDM) should be adopted in all neonatal intensive care units (NICUs), where the most preterm and fragile babies are hospitalized and treated with many drugs, considering that organs and metabolic pathways undergo deep and progressive maturation processes after birth. Different developmental changes are involved in interindividual variability in response to drugs. A crucial point of TDM is the choice of the bioanalytical method and of the sample to use. TDM in neonates is primarily used for antibiotics, antifungals, and antiepileptic drugs in clinical practice. TDM appears to be particularly promising in specific populations: neonates who undergo therapeutic hypothermia or extracorporeal life support, preterm infants, infants who need a tailored dose of anticancer drugs. This review provides an overview of the latest advances in this field, showing options for a personalized therapy in newborns and infants.