Continuous infusion of vancomycin improved therapeutic levels in term and preterm infants

Round, Antonia; Clifton, Emily; Stachow, Lucy; Mittal, Sumit; Yadav, K; Ashraf, Hira; Sanghera, Ranveer; Ng, Khuen Foong

doi:10.1038/s41372-020-00909-3

Cited by 2 publications

(1 citation statement)

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“…Vancomycin continuous IV infusion has many advantages over intermittent infusions: it shortens the time to achieve target concentrations and increases the probability of drug concentrations in the therapeutic range [8], reduces drug toxicity and the need for plasma drug measurements [9,10]. Studies dealing with continuous infusion of vancomycin in pediatric patients are heterogenous, and the optimal dosage is still to be identified, which will require studies in larger population [11].…”

Section: Introductionmentioning

confidence: 99%

Optimization of Vancomycin Initial Dose in Term and Preterm Neonates by Machine Learning

et al. 2022

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Introduction: Vancomycin is one of the antibiotics most used in neonates. Continuous infusion has many advantages over intermittent infusions, but no consensus has been achieved regarding the optimal initial dose.The objectives of this study were: to develop a Machine learning (ML) algorithm based on pharmacokinetic profiles obtained by Monte Carlo simulations using a population pharmacokinetic model (POPPK) from the literature, in order to derive the best vancomycin initial dose in preterm and term neonates, and to compare ML performances with those of an literature equation (LE) derived from a POPPK previously published.Materials and methods: The parameters of a previously published POPPK model of vancomycin in children and neonates were used in the mrgsolve R package to simulate 1900 PK profiles. ML algorithms were developed from these simulations using Xgboost, GLMNET and MARS in parallel, benchmarked and used to calculate the ML first dose. Performances were evaluated in a second simulation set and in an external set of 82 real patients and compared to those of a LE.Results: The Xgboost algorithm yielded numerically best performances and target attainment rates: 46.9% in the second simulation set of 400-600 AUC/MIC ratio vs. 41.4% for the LE model (p=0.0018); and 35.3% vs. 28% in real patients (p=0.401), respectively). The Xgboost model resulted in less AUC/MIC>600, thus decreasing the risk of nephrotoxicity. Conclusion:The Xgboost algorithm developed to estimate the initial dose of vancomycin in term or preterm infants has better performances than a previous validated LE and should be evaluated prospectively.

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