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Table 3 Characteristics of the included studies for target AUC based on nephrotoxicity

From: The monitoring of vancomycin: a systematic review and meta-analyses of area under the concentration-time curve-guided dosing and trough-guided dosing

Study Design of study Country Duration of study Age of patients Patient’s condition Definition of AUC values Target AUC breakpoint
Chavada 2017 [43] Retrospective Australia 2006–2012 > 18% of patient age ≥ 70:
AKI 50.0%
Non-AKI 41.1%
MRSA bacteremia Values estimated by the maximum a posteriori Bayesian estimation, using a priori pharmacokinetic parameters of a previous population pharmacokinetic model ≥ 563
Zasowski 2018 [44] Retrospective America 2014–2015 > 18
Mean ± SD:
61.7 ± 16.8
Confirmed or suspected bacteremiaor pneumonia Values estimated via the maximum a posteriori probability Bayesian function using a previously published 2-compartment population pharmacokinetic model as the Bayesian prior ≥ 683
Meng 2019 [15] Prospective America 2018 ≥18
Median ± SD (IQR):
AKI 51 ± 19 (37–62)
Non-AKI 63 ± 17 (50–69)
Pulmonary, skin and soft tissue infection, osteoarticular, febrile neutropenia, abdominal, pelvic, intrathoracic, bacteremia, central nervous system, endocarditis, cardiovascular implantable, electronic device infections, vascular graft Values obtained by a Stanford hospital–specific spreadsheet calculator with prebuilt pharmacokinetic equations using Microsoft Excel (http://med.stanford.edu/bugsanddrugs.html) ≥ 600
Brunetti 2020 [45] Retrospective America 2011–2018 ≥18
Mean ± SD: 57 ± 16.4
N/A Values estimated by DoseMe software, which uses a Bayesian approach > 600
Lodise 2020 [46] Prospective America 2014–2015 ≥18
Mean ± SD: 60.7 ± 17.3
MRSA bloodstream infection Values estimated post hoc using the maximal a posteriori probability procedure ≥ 550
  1. N/A not available
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