Validity of Bayesian forecasting programme in therapeutic drug monitoring of vancomycin in a surgical intensive care unit: a prospective evaluation.

The objectives of this study were: (a) to assess the predictive performance of a 2-compartment Bayesian vancomycin forecasting programme in critically ill patients in the surgical intensive care unit, and (b) to show the applicability of the programme, which is based on parameters derived from Western population, in our local Asian population. Twenty critically ill patients were enrolled into the study programme. All patients received multiple-dose vancomycin for infections due to methicillin-resistant staphylococcus aureus (MRSA). The patients dosage regimen were optimised by entering a set of peak and trough vancomycin serum levels into a clinical computer program (MB; USC*PACK PC collection; University of Southern California, USA) by utilising a 2-compartment Bayesian population model. The correlation between observed and predicted serum peak and trough concentrations were evaluated for both the non-fitted and fitted models by linear regression analysis. There was a significant correlation between observed and predicted concentrations using the fitted model (r = 0.97, P < 0.05). There was no significant correlation of these concentrations in the non-fitted model (r = 0.8). This study shows that the Bayesian programme is able to accurately predict future vancomycin concentrations in our local Asian population. It is possible to optimise patients dosage regimens with the knowledge of two concentrations of vancomycin in order to achieve targeted therapeutic goals.