RESUMO
AIMS: Bayesian forecasting software can assist in guiding therapeutic drug monitoring (TDM)-based dose adjustments for amikacin to achieve therapeutic targets. This study aimed to evaluate amikacin prescribing and TDM practices, and to determine the suitability of the amikacin model incorporated into the DoseMeRx® software as a replacement for the previously available software (Abbottbase®). METHODS: Patient demographics, pathology, amikacin dosing history, amikacin concentrations and Abbottbase® predicted TDM targets (area under the curve up to 24 hours, maximum concentration and trough concentration) were collected for adults receiving intravenous amikacin (2012-2017). Concordance with the Australian Therapeutic Guidelines was assessed. Observed and predicted amikacin concentrations were compared to determine the predictive performance (bias and precision) of DoseMeRx®. Amikacin TDM targets were predicted by DoseMeRx® and compared to those predicted by Abbottbase®. RESULTS: Overall, guideline compliance for 63 courses of amikacin in 47 patients was suboptimal. Doses were often lower than recommended. For therapy >48 h, TDM sample collection timing was commonly discordant with recommendations, therapeutic target attainment low and 34% of dose adjustments inappropriate. DoseMeRx® under-predicted amikacin concentrations by 0.9 mg/L (95% confidence interval [CI] -1.4 to -0.5) compared with observed concentrations. However, maximum concentration values (n = 19) were unbiased (-1.7 mg/L 95%CI -5.8 to 0.8) and precise (8.6% 95%CI 5.4-18.1). Predicted trough concentration values (n = 7) were, at most, 1 mg/L higher than observed. Amikacin area under the curve values estimated using Abbottbase® (181 mg h/L 95%CI 161-202) and DoseMeRx® (176 mg h/L 95%CI 152-199) were similar (P = .59). CONCLUSION: Amikacin dosing and TDM practice was suboptimal compared with guidelines. The model implemented by DoseMeRx® is satisfactory to guide amikacin dosing.
