Bayesian‐Estimated Vancomycin AUC24 as a Near‐Term Renal Risk Signal after Therapeutic Drug Monitoring: A Multicenter Cohort Study

Abstract

Vancomycin therapeutic drug monitoring has moved toward area under the concentration–time curve (AUC)‐guided dosing, but the clinical meaning of a Bayesian‐estimated AUC generated at an individual monitoring episode remains uncertain when renal clearance may already be changing. We conducted a retrospective multicenter cohort study using inpatient dosing, pharmacy, therapeutic drug monitoring, and laboratory data from two hospitals in Hai Phong, Viet Nam, between 2019 and 2025. The analysis included 898 adult index vancomycin monitoring episodes with valid Bayesian‐estimated AUC24 and sufficient serum creatinine data to ascertain acute kidney injury (AKI) within 48 h. AUC24 was estimated within the institutional Bayesian monitoring workflow using SmartDoseAI, with BestDose version 2.4.3 used as an independent pharmacokinetic cross‐check in selected clinically uncertain episodes. AKI occurred in 84 episodes (9.4%). Higher continuous AUC24 was associated with AKI in the minimally adjusted model (odds ratio, 1.16 per 100 mg·h/L; 95% confidence interval, 1.02–1.33; P = .023), whereas categorical AUC contrasts were imprecise. The association attenuated after exclusion of 23 episodes with possible pre‐existing AKI before the index monitoring episode (odds ratio, 1.12; 95% confidence interval, 0.96–1.31; P = .159), and restricted cubic spline modeling did not identify a distinct nonlinear threshold. Bayesian‐estimated AUC24 at monitoring may therefore be most useful as a near‐term renal risk signal that integrates vancomycin exposure with evolving renal clearance, rather than as a standalone causal toxicity threshold.