The pharmacokinetics of propofol in ICU patients undergoing long-term sedation.
Piotr SmuszkiewiczPaweł WiczlingKrzysztof PrzybyłowskiAgnieszka BorsukIwona TrojanowskaMarta PaterskaJan MatysiakZenon J KokotEdmund GrześkowiakAgnieszka BienertPublished in: Biopharmaceutics & drug disposition (2016)
The aim of this study was to characterize the pharmacokinetics (PK) of propofol in ICU patients undergoing long-term sedation and to assess the influence of routinely collected covariates on the PK parameters. Propofol concentration-time profiles were collected from 29 patients. Non-linear mixed-effects modelling in NONMEM 7.2 was used to analyse the observed data. The propofol pharmacokinetics was best described with a three-compartment disposition model. Non-parametric bootstrap and a visual predictive check were used to evaluate the adequacy of the developed model to describe the observations. The typical value of the propofol clearance (1.46 l/min) approximated the hepatic blood flow. The volume of distribution at steady state was high and was equal to 955.1 l, which is consistent with other studies involving propofol in ICU patients. There was no statistically significant covariate relationship between PK parameters and opioid type, SOFA score on the day of admission, APACHE II, predicted death rate, reason for ICU admission (sepsis, trauma or surgery), gender, body weight, age, infusion duration and C-reactive protein concentration. The population PK model was developed successfully to describe the time-course of propofol concentration in ICU patients undergoing prolonged sedation. Despite a very heterogeneous group of patients, consistent PK profiles were observed. Copyright © 2016 John Wiley & Sons, Ltd.
Keyphrases
- patients undergoing
- intensive care unit
- end stage renal disease
- mechanical ventilation
- newly diagnosed
- ejection fraction
- chronic kidney disease
- emergency department
- blood flow
- peritoneal dialysis
- body weight
- patient reported outcomes
- machine learning
- low dose
- mental health
- minimally invasive
- acute kidney injury
- acute coronary syndrome
- acute respiratory distress syndrome
- big data
- atrial fibrillation
- artificial intelligence
- coronary artery bypass