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This study evaluated the predictive performance of a Bayesian PK estimation method (ADAPT V) to estimate the 24-h vancomycin area under the curve (AUC) with limited pharmacokinetic (PK) sampling in adult obese patients receiving vancomycin for suspected or confirmed Gram-positive infections. This was an Albany Medical Center Institutional Review Board-approved prospective evaluation of 12 patients. Patients had a median (95% confidence interval) age of 61 years (39 to 71 years), a median creatinine clearance of 86 ml/min (75 to 120 ml/min), and a median body mass index of 45 kg/m2 (40 to 52 kg/m2 ). For each patient, five PK concentrations were measured, and four different vancomycin population PK models were used as Bayesian priors to estimate the vancomycin AUC (AUCFULL ). Using each PK model as a prior, data-depleted PK subsets were used to estimate the 24-h AUC (i.e., peak and trough data [AUCPT ], midpoint and trough data [AUCMT ], and trough-only data [AUCT ]). The 24-h AUC derived from the full data set (AUCFULL ) was compared to the AUC derived from data-depleted subsets (AUCPT , AUCMT , and AUCT ) for each model. For the four sets of analyses, AUCFULL estimates ranged from 437 to 489 mg·h/liter. The AUCPT provided the best approximation of the AUCFULL ; AUCMT and AUCT tended to overestimate AUCFULL . Further prospective studies are needed to evaluate the impact of AUC monitoring in clinical practice, but the findings from this study suggest that the vancomycin AUC can be estimated with good precision and accuracy with limited PK sampling using Bayesian PK estimation software.

Pilot Study of a Bayesian Approach To Estimate Vancomycin Exposure in Obese Patients with Limited Pharmacokinetic Sampling