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Performance of Bayesian Area Under the Concentration-Time Curve-Based Pharmacokinetic Dosing Based on a One-Compartment Model and Trough-Only Monitoring for Vancomycin.
Salehpour, Niloufar; Riley, Lacey D; Gonzales, Marcos J; Kobic, Emir; Nix, David E.
Afiliação
  • Salehpour N; Department of Pharmacy Practice and Science, University of Arizona College of Pharmacy, Tucson, Arizona, USA.
  • Riley LD; Department of Pharmacy Practice and Science, University of Arizona College of Pharmacy, Tucson, Arizona, USA.
  • Gonzales MJ; Banner University Medical Center-Phoenix, Phoenix, Arizona, USA.
  • Kobic E; Department of Pharmacy Practice and Science, University of Arizona College of Pharmacy, Tucson, Arizona, USA.
  • Nix DE; Department of Pharmacy Practice and Science, University of Arizona College of Pharmacy, Tucson, Arizona, USA.
Antimicrob Agents Chemother ; 67(6): e0017223, 2023 06 15.
Article em En | MEDLINE | ID: mdl-37133362
ABSTRACT
A novel Bayesian method was developed to interpret serum vancomycin concentrations (SVCs) following the administration of one or more vancomycin doses with potential varying doses and intervals based on superposition principles. The method was evaluated using retrospective data from 442 subjects from three hospitals. The patients were required to receive vancomycin for more than 3 days, have stable renal function (fluctuation in serum creatinine of ≤0.3 mg/dL), and have at least 2 trough concentrations reported. Pharmacokinetic parameters were predicted using the first SVC, and the fitted parameters were then used to predict subsequent SVCs. Using only covariate-adjusted population prior estimates, the first two SVC prediction errors were 47.3 to 54.7% for the scaled mean absolute error (sMAE) and 62.1 to 67.8% for the scaled root mean squared error (sRMSE). "Scaled" refers to the division of the MAE or RMSE by the mean value. The Bayesian method had minimal errors for the first SVC (by design), and for the second SVC, the sMAE was 8.95%, and the sRMSE was 36.5%. The predictive performance of the Bayesian method did degrade with subsequent SVCs, which we attributed to time-dependent pharmacokinetics. The 24-h area under the concentration-time curve (AUC) was determined from simulated concentrations before and after the first SVC was reported. Prior to the first SVC, 170 (38.4%) patients had a 24-h AUC of <400 mg · h/L, 186 (42.1%) had a 24-h AUC within the target range, and 86 (19.5%) had a 24-h AUC of >600 mg · h/L. After the first SVC was reported, 322 (72.9%) had a 24-h AUC within the target range, 68 (15.4%) had low values, and 52 (11.8%) had high values based on the model simulation. Target attainments were 38% before the first SVC and 73% after the first SVC. The hospitals had no policies or procedures in place for targeting 24-h AUCs, although the trough target was typically 13 to 17 mg/L. Our data provide evidence of time-dependent pharmacokinetics, which will require regular therapeutic drug monitoring regardless of the method used to interpret SVCs.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Vancomicina / Monitoramento de Medicamentos Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Vancomicina / Monitoramento de Medicamentos Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article