A general purpose pharmacokinetic model for propofol. 2014

Douglas J Eleveld, and Johannes H Proost, and Luis I Cortínez, and Anthony R Absalom, and Michel M R F Struys
From the *Department of Anesthesiology, University Medical Center Groningen, University of Groningen, The Netherlands; †Departmento de Anestesiología, Escuela de Medicina, Pontificia Universidad Católica de Chile, Santiago, Chile; and ‡Department of Anesthesia, Ghent University, Gent, Belgium.

BACKGROUND Pharmacokinetic (PK) models are used to predict drug concentrations for infusion regimens for intraoperative displays and to calculate infusion rates in target-controlled infusion systems. For propofol, the PK models available in the literature were mostly developed from particular patient groups or anesthetic techniques, and there is uncertainty of the accuracy of the models under differing patient and clinical conditions. Our goal was to determine a PK model with robust predictive performance for a wide range of patient groups and clinical conditions. METHODS We aggregated and analyzed 21 previously published propofol datasets containing data from young children, children, adults, elderly, and obese individuals. A 3-compartmental allometric model was estimated with NONMEM software using weight, age, sex, and patient status as covariates. A predictive performance metric focused on intraoperative conditions was devised and used along with the Akaike information criteria to guide model development. RESULTS The dataset contains 10,927 drug concentration observations from 660 individuals (age range 0.25-88 years; weight range 5.2-160 kg). The final model uses weight, age, sex, and patient versus healthy volunteer as covariates. Parameter estimates for a 35-year, 70-kg male patient were: 9.77, 29.0, 134 L, 1.53, 1.42, and 0.608 L/min for V1, V2, V3, CL, Q2, and Q3, respectively. Predictive performance is better than or similar to that of specialized models, even for the subpopulations on which those models were derived. CONCLUSIONS We have developed a single propofol PK model that performed well for a wide range of patient groups and clinical conditions. Further prospective evaluation of the model is needed.

UI MeSH Term Description Entries
D007223 Infant A child between 1 and 23 months of age. Infants
D007432 Intraoperative Period The period during a surgical operation. Intraoperative Periods,Period, Intraoperative,Periods, Intraoperative
D008297 Male Males
D008875 Middle Aged An adult aged 45 - 64 years. Middle Age
D009765 Obesity A status with BODY WEIGHT that is grossly above the recommended standards, usually due to accumulation of excess FATS in the body. The standards may vary with age, sex, genetic or cultural background. In the BODY MASS INDEX, a BMI greater than 30.0 kg/m2 is considered obese, and a BMI greater than 40.0 kg/m2 is considered morbidly obese (MORBID OBESITY).
D011237 Predictive Value of Tests In screening and diagnostic tests, the probability that a person with a positive test is a true positive (i.e., has the disease), is referred to as the predictive value of a positive test; whereas, the predictive value of a negative test is the probability that the person with a negative test does not have the disease. Predictive value is related to the sensitivity and specificity of the test. Negative Predictive Value,Positive Predictive Value,Predictive Value Of Test,Predictive Values Of Tests,Negative Predictive Values,Positive Predictive Values,Predictive Value, Negative,Predictive Value, Positive
D002648 Child A person 6 to 12 years of age. An individual 2 to 5 years old is CHILD, PRESCHOOL. Children
D002675 Child, Preschool A child between the ages of 2 and 5. Children, Preschool,Preschool Child,Preschool Children
D005260 Female Females
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man

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