Sarah F Cook1, Jessica K Roberts2, Samira Samiee-Zafarghandy3,4, Chris Stockmann2,5, Amber D King1, Nina Deutsch6, Elaine F Williams3, Karel Allegaert7,8, Diana G Wilkins1,9, Catherine M T Sherwin10, John N van den Anker3,11,12,13. 1. Center for Human Toxicology, Department of Pharmacology and Toxicology, University of Utah, Salt Lake City, UT, USA. 2. Division of Clinical Pharmacology, Department of Pediatrics, University of Utah School of Medicine, 295 Chipeta Way, Salt Lake City, UT, 84108, USA. 3. Division of Clinical Pharmacology, Children's National Health System, Washington, DC, USA. 4. Division of Neonatology, Department of Pediatrics, McMaster University, Hamilton, ON, Canada. 5. Department of Pharmacology and Toxicology, University of Utah, Salt Lake City, UT, USA. 6. Division of Anesthesiology, Sedation, and Perioperative Medicine, Children's National Health System, Washington, DC, USA. 7. Neonatal Intensive Care Unit, University Hospitals Leuven, Leuven, Belgium. 8. Department of Development and Regeneration, KU Leuven, Leuven, Belgium. 9. Division of Medical Laboratory Sciences, Department of Pathology, University of Utah School of Medicine, Salt Lake City, UT, USA. 10. Division of Clinical Pharmacology, Department of Pediatrics, University of Utah School of Medicine, 295 Chipeta Way, Salt Lake City, UT, 84108, USA. catherine.sherwin@hsc.utah.edu. 11. Departments of Pediatrics, Integrative Systems Biology, Pharmacology and Physiology, George Washington University School of Medicine and Health Sciences, Washington, DC, USA. 12. Intensive Care and Department of Pediatric Surgery, Erasmus Medical Center-Sophia Children's Hospital, Rotterdam, The Netherlands. 13. Department of Paediatric Pharmacology, University Children's Hospital Basel, Basel, Switzerland.
Abstract
OBJECTIVES: The aims of this study were to develop a population pharmacokinetic model for intravenous paracetamol in preterm and term neonates and to assess the generalizability of the model by testing its predictive performance in an external dataset. METHODS: Nonlinear mixed-effects models were constructed from paracetamol concentration-time data in NONMEM 7.2. Potential covariates included body weight, gestational age, postnatal age, postmenstrual age, sex, race, total bilirubin, and estimated glomerular filtration rate. An external dataset was used to test the predictive performance of the model through calculation of bias, precision, and normalized prediction distribution errors. RESULTS: The model-building dataset included 260 observations from 35 neonates with a mean gestational age of 33.6 weeks [standard deviation (SD) 6.6]. Data were well-described by a one-compartment model with first-order elimination. Weight predicted paracetamol clearance and volume of distribution, which were estimated as 0.348 L/h (5.5 % relative standard error; 30.8 % coefficient of variation) and 2.46 L (3.5 % relative standard error; 14.3 % coefficient of variation), respectively, at the mean subject weight of 2.30 kg. An external evaluation was performed on an independent dataset that included 436 observations from 60 neonates with a mean gestational age of 35.6 weeks (SD 4.3). The median prediction error was 10.1 % [95 % confidence interval (CI) 6.1-14.3] and the median absolute prediction error was 25.3 % (95 % CI 23.1-28.1). CONCLUSIONS: Weight predicted intravenous paracetamol pharmacokinetics in neonates ranging from extreme preterm to full-term gestational status. External evaluation suggested that these findings should be generalizable to other similar patient populations.
OBJECTIVES: The aims of this study were to develop a population pharmacokinetic model for intravenous paracetamol in preterm and term neonates and to assess the generalizability of the model by testing its predictive performance in an external dataset. METHODS: Nonlinear mixed-effects models were constructed from paracetamol concentration-time data in NONMEM 7.2. Potential covariates included body weight, gestational age, postnatal age, postmenstrual age, sex, race, total bilirubin, and estimated glomerular filtration rate. An external dataset was used to test the predictive performance of the model through calculation of bias, precision, and normalized prediction distribution errors. RESULTS: The model-building dataset included 260 observations from 35 neonates with a mean gestational age of 33.6 weeks [standard deviation (SD) 6.6]. Data were well-described by a one-compartment model with first-order elimination. Weight predicted paracetamol clearance and volume of distribution, which were estimated as 0.348 L/h (5.5 % relative standard error; 30.8 % coefficient of variation) and 2.46 L (3.5 % relative standard error; 14.3 % coefficient of variation), respectively, at the mean subject weight of 2.30 kg. An external evaluation was performed on an independent dataset that included 436 observations from 60 neonates with a mean gestational age of 35.6 weeks (SD 4.3). The median prediction error was 10.1 % [95 % confidence interval (CI) 6.1-14.3] and the median absolute prediction error was 25.3 % (95 % CI 23.1-28.1). CONCLUSIONS: Weight predicted intravenous paracetamol pharmacokinetics in neonates ranging from extreme preterm to full-term gestational status. External evaluation suggested that these findings should be generalizable to other similar patient populations.
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