AUTHOR=Dreyse Natalia , Salazar Nicole , Munita Jose M. , Rello Jordi , López René 

TITLE=Vancomycin levels for Bayesian dose-optimization in critical care: a prospective cohort study

JOURNAL=Frontiers in Medicine

VOLUME=Volume 12 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/medicine/articles/10.3389/fmed.2025.1575224

DOI=10.3389/fmed.2025.1575224

ISSN=2296-858X

ABSTRACT=BackgroundVancomycin dosing in critically ill patients typically requires monitoring the area under the concentration-time curve/minimum inhibitory concentration (AUC/MIC), often using at least two vancomycin levels (VLs). However, the optimal number of VLs needed for accurate AUC/MIC estimation in this population remains uncertain. This study aimed to determine the minimum number of VLs required to accurately estimate the AUC/MIC in critically ill patients treated with intermittent infusion of vancomycin.MethodsA prospective cohort study was conducted in critically ill patients, where VLs were obtained at peak, beta, and trough phases. Five AUC estimates were derived using PrecisePK™, a Bayesian software: AUC-1 [peak, beta (2 h after the end infusion), trough], AUC-2 (beta, trough), AUC-3 (peak, trough), AUC-4 (trough), and AUC-5 (only Bayesian prior, without VL). These estimates were compared for accuracy and bias (mean ± SEM) against the reference AUC calculated via the trapezoidal model (AUCRef).ResultsWe enrolled 36 adult patients with age of 65 (52–77) years, moderate severity [APACHE II 10 (5–14) and SOFA 5 (4–6)], 6 of them in ECMO and 4 in renal replacement therapy. A total of 108 blood samples for VL were analyzed. The AUC-3 (0.976 ± 0.012) showed greater accuracy compared to AUC-4 (1.072 ± 0.032, p = 0.042) and AUC-5 (1.150 ± 0.071, p = 0.042). AUC-3 also demonstrated lower bias (0.053 ± 0.009) than AUC-4 (0.134 ± 0.026, p = 0.036) and AUC-5 (0.270 ± 0.060, p = 0.003). Bland–Altman analysis indicated better agreement between AUC-3 and AUC-2 with AUCRef.ConclusionBayesian software using two vancomycin levels provides a more accurate and less biased AUC/MIC estimation in critically ill patients.