Optimizing Gentamicin Dosing in Pediatrics Using Monte Carlo Simulations

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Abstract

Gentamicin is known to have concentration-dependent bactericidal activity, and its nephrotoxic effect is well described. We developed a population pharmacokinetic/pharmacodynamic model to optimize gentamicin dosing in pediatrics. Data were retrospectively collected for pediatric patients 1 month to 12 years of age, admitted to general pediatric wards or intensive care units and received gentamicin for suspected or proven Gram-negative infections at King Saud University Medical City, Riyadh, Saudi Arabia. A total of 306 gentamicin peak and trough concentrations sets from 107 patients were analyzed with mean (±standard deviation) patient age and weight of 4.5 ± 3.5 years and 16.7 ± 10.8 kg, respectively. Gentamicin pharmacokinetics were adequately described with a one compartment system (R2 = 0.82, bias = 1.75% and precision = 88% for population predictions and R2 = 0.94, bias = 5% and precision = 29% for individual predictions). The gentamicin pharmacokinetic parameters were as follows: volume of distribution = 8.9 L, total body clearance = 2.8 L/h for a 20-kg patient. Monte Carlo simulations showed that doses of 5-6 mg/kg/dose once daily are adequate only to treat infections with Gram-negative organisms having minimal inhibitory concentration less than 1 μg/mL. While, at minimal inhibitory concentration of 1 μg/mL, higher doses (7-8 mg/kg/dose once daily) are needed to maximize the efficacy of gentamicin. However, at minimal inhibitory concentration of 2 μg/mL, even a 10 mg/kg dose showed poor target attainment (52%). The finding of this study highlights the need to reevaluate the current breakpoints of gentamicin and also to assess the safety of higher doses of gentamicin in pediatrics.

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Alsultan, A., Abouelkheir, M., Elsharawy, Y., Alkoraishi, A., Osman, R., Neely, M. N., … Algahtani, S. (2019). Optimizing Gentamicin Dosing in Pediatrics Using Monte Carlo Simulations. Pediatric Infectious Disease Journal, 38(4), 390–395. https://doi.org/10.1097/INF.0000000000002120

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