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Article Abstract

Bayesian modeling of vancomycin can estimate 24-hour area under the curve (AUC) using pre-steady-state concentrations. Limited literature exists comparing Bayesian AUC calculations derived from steady-state versus pre-steady-state concentrations. To assess the agreement between vancomycin AUC calculations using pre-steady-state versus steady-state concentrations, employing Bayesian modeling. This retrospective within-subjects cohort study included patients with at least 1 pre-steady-state and 1 steady-state vancomycin concentration. Patients with age >100 years, weight <40 kg, height <60 inches, or renal dysfunction were excluded. The steady-state AUC from dosing software was documented with and without hiding steady-state levels from calculations. The primary outcome was agreement between AUC without levels hidden compared with AUC with steady-state levels hidden from analysis. Secondary outcomes included the agreement between AUC with pre-steady-state levels hidden and the percentage of patients with matching AUC categories. The AUC agreement was evaluated via Bland-Altman plot and bias via linear regression. Statistical tests were performed using SPSS statistics software (IBM Corp). A total of 93 patients were included. The mean difference in AUC compared to AUC with steady-state levels hidden was 8.8 mg*h/L, and with pre-steady-state levels hidden, it was -3.7 mg*h/L. Linear regression analysis indicated a proportional bias when steady-state levels were hidden (β = 0.22; = 0.038) but not when pre-steady-state levels were hidden. Category mismatch occurred more often when steady-state levels were hidden vs when pre-steady-state levels were hidden (26% vs 8%; < 0.001). The study demonstrated overall agreement between AUC compared to AUC with steady-state levels hidden. The mean differences in AUC estimates were small, no matter which level was hidden, although tighter limits of agreement were observed when steady-state levels were utilized in Bayesian calculations. Further research with larger sample sizes is necessary.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12370660PMC
http://dx.doi.org/10.1177/87551225251362731DOI Listing

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