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TDM coupled with Bayesian forecasting should be considered an invaluable tool for optimizing vancomycin daily exposure in unstable critically ill patients.

Federico Pea·Massimo Bertolissi·Adriana Di Silvestre·Donatella Poz·Francesco Giordano·Mario Furlanut
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Abstract

A randomized two-arm prospective study was planned to assess the role of therapeutic drug monitoring (TDM) coupled with a Bayesian approach in tailoring vancomycin dosages in unstable critically ill patients. Group A (n=16) had their regimen adjusted day-by-day according to TDM and Bayesian forecasting (D(a)); group B (n=16) had their regimen adjusted day-by-day according to Moellering's nomogram (D(M)). Blood samples were collected every 1-2 days to assess the trough and peak plasma concentrations. In group A, the tailored D(a) required for optimizing vancomycin exposure were considerably higher than the D(M) in 7/16 cases, and lower than the D(M) in 1/16 cases. In group B, standard D(M) caused under-treatment in 3/16 cases and over-treatment in 4/16 cases. Most of these patients concomitantly had some conditions that might have altered vancomycin disposition. The TDM-guided Bayesian-based approach should be considered an invaluable tool for clinicians to handle appropriately on real-time vancomycin therapy in critically ill patients.

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AdultAgedAnti-Bacterial AgentsBayes TheoremCritical IllnessDrug MonitoringDrug Resistance, Multiple, BacterialFemaleGram-Positive BacteriaGram-Positive Bacterial InfectionsHumansMaleMiddle AgedVancomycinClinical TrialJournal ArticleRandomized Controlled Trial

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Federico Pea, Massimo Bertolissi, Adriana Di Silvestre, Donatella Poz, Francesco Giordano, Mario Furlanut. 2002. TDM coupled with Bayesian forecasting should be considered an invaluable tool for optimizing vancomycin daily exposure in unstable critically ill patients.. https://doi.org/10.1016/s0924-8579(02)00188-7

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