Abstract
BACKGROUND: Gentamicin therapy in neonates is optimized through achieving specific peak and trough concentrations. The objective of this study was to compare the ability a Bayesian clinical decision support system (CDSS) with standard of care (SOC) in determining personalized gentamicin therapies for neonates, at regimen initiation and in response to measured drug concentrations. METHODS: This retrospective review and simulation compared target attainment among 4 arms: historical dosing according to SOC, via nomogram for initial dosing (SOC-initial) and via clinician judgment in response to measured concentrations (SOC-adjusted), and simulated dosing using the CDSS, incorporating a neonatal pharmacokinetic model for initial dosing (CDSS-initial) and incorporating maximum a posteriori-Bayesian analysis in response to measured concentrations (CDSS-adjusted). "True" patient pharmacokinetic parameters and peak and trough concentration predictions were calculated via the CDSS using the entirety of the patient dosing and concentration history. The primary outcome was pharmacokinetic target attainment of desired gentamicin peak and trough concentrations. RESULTS: The study included 564 gentamicin concentrations among 339 patients. Mean demographics were 35 weeks gestational age (52% premature births) and 2.44 kg dosing weight. Mean PK parameters were 0.0533 L/h/kg clearance, 0.458 L/kg volume of distribution, and 8.66 hours half-life. Peak concentrations in the desired range were achieved in 96% of significantly more often in the CDSS-initial regimens and 94% of CDSS-adjusted regimens versus 86% of SOC-initial regimens and 66% of SOC-adjusted regimens. No difference was found in trough target attainment among study groups. CONCLUSIONS: In simulation, a Bayesian CDSS showed superiority to SOC in achieving gentamicin pharmacokinetic exposure targets in neonates. Use of a CDSS may improve the safety and efficacy of gentamicin therapy for neonates.