February 03, 2020

Bayesian Clinical Decision Support-guided Versus Clinician-guided Vancomycin Dosing in Attainment of Targeted Pharmacokinetic Parameters in a Paediatric Population


Objectives: To compare a Bayesian clinical decision support (CDS) dose-optimizing software program with clinician judgement in individualizing vancomycin dosing regimens to achieve vancomycin pharmacokinetic (PK)/pharmacodynamic (PD) targets in a paediatric population.

Methods: A retrospective review combined with a model-based simulation of vancomycin dosing was performed on children aged 1 year to 18 years at the University of California, San Francisco Benioff Children’s Hospital Mission Bay. Dosing regimens recommended by the clinical pharmacists, ‘clinician-guided’, were compared with alternative ‘CDS-guided’ dosing regimens. The primary outcome was the percentage of occasions predicted to achieve steady-state trough levels within the target range of 10-15 mg/L, with a secondary outcome of predicted attainment of AUC24 ≥400 mg·h/L. Statistical comparison between approaches was performed using a standard t-test.

Results: A total of n=144 patient occasions were included. CDS-guided regimens were predicted to achieve vancomycin steady-state troughs in the target range on 70.8% (102/144) of occasions, as compared with 37.5% (54/144) in the clinician-guided arm (P<0.0001). An AUC24 of ≥400 mg·h/L was achieved on 93% (112/121) of occasions in the CDS-guided arm versus 72% (87/121) of occasions in the clinician-guided arm (P<0.0001).

Conclusions: In a simulated analysis, the use of a Bayesian CDS tool was better than clinician judgement in recommending vancomycin dosing regimens in which PK/PD targets would be attained in children.

David M Hughes, Srijib Goswami, Ron J Keizer, Maria-Stephanie A Hughes, Jonathan D Faldasz. Bayesian clinical decision support-guided versus clinician-guided vancomycin dosing in attainment of targeted pharmacokinetic parameters in a paediatric population. Journal of Antimicrobial Chemotherapy. 2020.https://pubmed.ncbi.nlm.nih.gov/31670812/

Ranvir Mangat
About the Author: Ranvir Mangat