Search

Background Vancomycin is a frequently used antibiotic in neonates. However, there is no consensus guideline on the optimal dosing regimen and therapeutic drug monitoring (TDM) practices in this patient population. Objective To document the variability in the current dosing and TDM practices in neonatal intensive care units (NICU). Setting Belgian and Dutch NICUs. Method An online questionnaire was disseminated by e-mail to potential respondents. Main outcome measure Differences in vancomycin dosing and TDM practices in comparison with a reference source, the Dutch Paediatric Formulary. Results Eighteen NICUs (response rate 62%) participated. Eleven different dosing regimens are applied, with 83% using intermittent dosing regimens. Stratifying covariates used to determine the (initial) dosage include gestational age, postnatal age, serum creatinine, concurrent use of non-steroidal anti-inflammatory drugs, birth weight and current weight. Large variability is observed with regard to TDM practice as well, both for the concentration target range and the times of (re)sampling. Dosing calculators are more commonly used in the Netherlands than Belgium. Conclusion Significant inter-centre variability in dosing and TDM practices was found. The development of international consensus guidelines is required to optimize therapy. Dosing calculators to guide dosing are not yet considered as part of standard-of-care.

Objectives: The aim of this study was to develop a mechanistic protein-binding model to predict the unbound flucloxacillin concentrations in different patient populations. Methods: A mechanistic protein-binding model was fitted to the data using non-linear mixed-effects modelling. Data were obtained from four datasets, containing 710 paired total and unbound flucloxacillin concentrations from healthy volunteers, non-critically ill and critically ill patients. A fifth dataset with data from hospitalized patients was used for evaluation of our model. The predictive performance of the mechanistic model was evaluated and compared with the calculation of the unbound concentration with a fixed unbound fraction of 5%. Finally, we performed a fit-for-use evaluation, verifying whether the model-predicted unbound flucloxacillin concentrations would lead to clinically incorrect dose adjustments. Results: The mechanistic protein-binding model predicted the unbound flucloxacillin concentrations more accurately than assuming an unbound fraction of 5%. The mean prediction error varied between –26.2% to 27.8% for the mechanistic model and between –30.8% to 83% for calculation with a fixed factor of 5%. The normalized root mean squared error varied between 36.8% and 69% respectively between 57.1% and 134%. Predicting the unbound concentration with the use of the mechanistic model resulted in 6.1% incorrect dose adjustments versus 19.4% if calculated with a fixed unbound fraction of 5%. Conclusions: Estimating the unbound concentration with a mechanistic protein-binding model outperforms the calculation with the use of a fixed protein binding factor of 5%, but neither demonstrates acceptable performance. When performing dose individualization of flucloxacillin, this should be done based on measured unbound concentrations rather than on estimated unbound concentrations from the measured total concentrations. In the absence of an assay for unbound concentrations, the mechanistic bin