학술논문

External Validation of Obese/Critically Ill Vancomycin Population Pharmacokinetic Models in Critically Ill Patients Who Are Obese.
Document Type
Article
Source
Journal of Clinical Pharmacology. Mar2024, Vol. 64 Issue 3, p353-361. 9p.
Subject
*OBESITY complications
*ONLINE information services
*CRITICALLY ill
*AGE distribution
*VANCOMYCIN
*PATIENTS
*RETROSPECTIVE studies
*ACQUISITION of data
*INFECTION
*COMPARATIVE studies
*MEDICAL records
*RESEARCH funding
*PREDICTION models
*MEDLINE
*DATA analysis software
*BODY mass index
*LONGITUDINAL method
*CREATININE
RESEARCH evaluation
Language
ISSN
0091-2700
Abstract
Obesity combined with critical illness might increase the risk of acquiring infections and hence mortality. In this patient population the pharmacokinetics of antimicrobials vary significantly, making antimicrobial dosing challenging. The objective of this study was to assess the predictive performance of published population pharmacokinetic models of vancomycin in patients who are critically ill or obese for a cohort of critically ill patients who are obese. This was a multi‐center retrospective study conducted at 2 hospitals. Adult patients with a body mass index of ≥30 kg/m2 were included. PubMed was searched for published population pharmacokinetic studies in patients who were critically ill or obese. External validation was performed using Monolix software. A total of 4 models were identified in patients who were obese and 5 models were identified in patients who were critically ill. In total, 138 patients who were critically ill and obese were included, and the most accurate models for these patients were the Goti and Roberts models. In our analysis, models in patients who were critically ill outperformed models in patients who were obese. When looking at the most accurate models, both the Goti and the Roberts models had patient characteristics similar to ours in terms of age and creatinine clearance. This indicates that when selecting the proper model to apply in practice, it is important to account for all relevant variables, besides obesity. [ABSTRACT FROM AUTHOR]