Population pharmacokinetics of intravenous bolus etomidate in children over 6 months of age

Lin, Lin; Zhang, Jianwei; Huang, Yue; Bai, Jie; Cai, Minghao; Zhang, Mazhong

doi:10.1111/j.1460-9592.2011.03696.x

Cited by 16 publications

(9 citation statements)

References 26 publications

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“…In 2011, Lin et al . published the PK profile of etomidate administered to patients aged 6 months to 13 years . They found etomidate clearance to be 1.5 l/min/70 kg in a typical 4‐year‐old child without cardiac disease.…”

Section: Discussionmentioning

confidence: 99%

Population pharmacokinetics of etomidate in neonates and infants with congenital heart disease

Elkomy

Hammer

et al. 2015

Biopharm & Drug Disp

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Background Etomidate is a rapid-onset, short-acting hypnotic medication administered for induction of anesthesia. It is currently approved by the Food and Drug Administration for use in older children and adults. Pharmacokinetic data to help guide dosing in neonates and infants is lacking. Objective The aim of this study was to determine the pharmacokinetics of etomidate in neonates and infants with congenital heart disease undergoing cardiac surgery. Methods Four neonates and sixteen infants, postnatal age 0.3 – 11.7 months, requiring open-heart surgery received 0.3 mg/kg of etomidate administered as a single intravenous dose prior to surgery. Blood sampling for plasma etomidate concentration occurred immediately following etomidate administration until the initiation of cardiopulmonary bypass. A population pharmacokinetic approach using nonlinear mixed–effects modeling was applied to characterize etomidate pharmacokinetics. Results The pharmacokinetics of etomidate was described by a two-compartment model with first-order elimination. An allometric weight-based model was applied to scale results to a 70 kg adult. Covariates including age and cardiac physiology were not found to significantly impact etomidate pharmacokinetics. The study population was found to have a central and intercompartmental clearance of 0.624 L/min/70-kg and 0.44 L/min/70-kg, respectively; central and peripheral distribution volume of 9.47 and 22.8 L/70-kg, respectively. Inter-individual variability was between 94–142% for all parameters and residual variability was 29%. Conclusions The clearance of etomidate is lower in neonates and infants with congenital heart disease compared to published values for older children without congenital heart disease. In addition, etomidate pharmacokinetics is highly variable in this pediatric cardiac population.

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Section: Discussionmentioning

confidence: 99%

Population pharmacokinetics of etomidate in neonates and infants with congenital heart disease

Elkomy

Hammer

et al. 2015

Biopharm & Drug Disp

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“…Continuous infusions are not common, but doses of 1 to 25 mcg/kg/min have been reported. 3,4 It has a large volume of distribution, undergoes renal elimination (75% [80% as metabolite, 2% as unchanged drug]), and is about 80% protein bound to albumin. 5 Etomidate is primarily used during rapid-sequence intubation in pediatric patients.…”

Section: Discussionmentioning

confidence: 99%

Continuous-Infusion Etomidate in a Patient Receiving Extracorporeal Membrane Oxygenation

LaRochelle¹,

Desselle²,

Rossi³

2017

The Journal of Pediatric Pharmacology and Therapeutics

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We describe a 16-year-old, 65-kg male deployed on extracorporeal membrane oxygenation (ECMO) for refractory respiratory failure secondary to ingestion of multiple substances. During his ECMO course, standard sedative and analgesic strategies failed and alternative medications were used. The patient received various dosages of fentanyl, morphine, hydromorphone, clonidine patches, dexmedetomidine, lorazepam, methadone, pentobarbital, olanzapine, and propofol. Despite administration of multiple agents, on day 29 of ECMO the patient experienced elevated blood pressures due to agitation, and continuous infusion etomidate was started. At the time of etomidate initiation, the osmolar gap was 8 mOsm/kg. During etomidate therapy, the blood pressure remained normal, sedative agents were slowly weaned, and the patient required few PRN medications. On day 6 of etomidate, the osmolar gap increased to 127 mOsm/ kg and etomidate was discontinued. Continuous-infusion ketamine was started, but the blood pressure was not controlled. Metabolic acidosis is a known side effect of etomidate due to inclusion of propylene glycol as a pharmaceutical solvent in the formulation. Despite high-dose etomidate (20 mcg/kg/min) for approximately 6 days, our patient did not experience metabolic acidosis. Absence of this adverse effect caused us to question the role of the ECMO circuit. To our knowledge, this is the first report of the use of continuous-infusion etomidate during ECMO. Etomidate infusion could be considered in difficult-to-manage patients after other alternatives have failed. ABBREVIATIONS BUN, blood urea nitrogen; ECMO, extracorporeal membrane oxygenation.

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“…The predictable component of BSV (we term this BSVP) is explained by covariates. Since BSV is, in theory, constant for a particular population then, as BSVP increases the remaining random component (BSVR) will decrease [7][8][9]. We can only estimate BSVR from population pharmacokinetic analysis and it is represented as OMEGA (X) for parameters of interest.…”

Section: Theorymentioning

confidence: 99%

A reduction in between subject variability is not mandatory for selecting a new covariate

Lagishetty

Vajjah

Duffull

2012

J Pharmacokinet Pharmacodyn

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Population pharmacokinetic-pharmacodynamic analysis involves nonlinear hierarchical modelling where the mean response in a population and the variability in response from different sources are studied. It generally consists of two model hierarchies: a model for residual error and a model for heterogeneity termed between subject variance (BSV). The overall variability in a parameter within a population termed population parameter variance (PPV) consists of within subject variance (WSV) and BSV. Both these variances can further be split into random and predictable components. The predictable component of BSV (termed BSVP) is explained by covariates, individual characteristics e.g. weight. As BSVP increases, the remaining unpredictable (or random) between subject variability (BSVR) decreases since BSV = BSVP + BSVR, and BSV is a constant in any given data set. Since BSV and BSVR are estimated from the base and full covariate models, respectively, then BSVP = BSV-BSVR. The aim of this study was to explore the hypothesis, that a significant covariate may not always decrease BSVR. The specific aims were: (1) to explore circumstances where BSVR may not be reduced when adding a significantly correlated covariate and (2) to explore whether specific models for covariates may eliminate this anomaly when assessing BSVR. Simulations were performed using MATLAB (2011a) and estimation using NONMEM (ver 7.2) with FOCE and INTERACTION. A 1-compartment intravenous bolus PK model was used for simulation following a single unit dose (d = 1). The BSV of clearance [BSV(CL)] was described according to a log-normal distribution model with mean zero and variance ω². An additive random unexplained variability was assumed. Initially, we show through a simple simulation that BSVR can increase when a significantly correlated covariate is added to the model. We follow this with five simulation scenarios, A to E, that have various levels of correlation between the continuous covariate (Z) and CL ranging from 0 to 100 %. Each simulated scenario was replicated 100 times and estimated by a base model (i.e. without covariate addition) and six covariate models (M1-M6) which included non-nested (M1), nested (M2), and two types of interaction models for each of M1 and M2; non-nested interaction (M3, M5), nested interaction (M4, M6). Initially, through a motivating example we show that BSVR may not reduce even when there is 50 % correlation between the covariate Z and CL. It was found that with 0 % correlation M1, the non-nested covariate model (NNCM) resulted in negative BSVP (inflated BSVR) whereas M2, the nested covariate model (NCM), resulted in a calculated BSVP of zero. NNCM (M1) shows negative BSVP (BSVR > BSV) with correlation as high as 50 % and this model needs a minimum of 75 % correlation to show a positive BSVP. NCM (M2) shows positive but downwardly biased BSVP with 25, 50 and 75 % correlations. However, inclusion of a covariate-eta interaction term for both types of covariate models resulted in greater BSVP for 25, 50 and 75 % correlati...

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Population pharmacokinetics of intravenous bolus etomidate in children over 6 months of age

Cited by 16 publications

References 26 publications

Population pharmacokinetics of etomidate in neonates and infants with congenital heart disease

Population pharmacokinetics of etomidate in neonates and infants with congenital heart disease

Continuous-Infusion Etomidate in a Patient Receiving Extracorporeal Membrane Oxygenation

A reduction in between subject variability is not mandatory for selecting a new covariate

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