Discrepancies Between Bayesian Vancomycin Models Can Affect Clinical Decisions in the Critically Ill

Purpose. To assess the agreement in 24-hour area under the curve (AUC24) value estimates between commonly used vancomycin population pharmacokinetic models in the critically ill. Materials and Methods. Adults admitted to intensive care who received intravenous vancomycin and had a serum vancomycin c...

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Main Authors: Asad E. Patanwala, Danijela Spremo, Minji Jeon, Yann Thoma, Jan-Willem C. Alffenaar, Sophie Stocker
Format: Article
Language:English
Published: Wiley 2022-01-01
Series:Critical Care Research and Practice
Online Access:http://dx.doi.org/10.1155/2022/7011376
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author Asad E. Patanwala
Danijela Spremo
Minji Jeon
Yann Thoma
Jan-Willem C. Alffenaar
Sophie Stocker
author_facet Asad E. Patanwala
Danijela Spremo
Minji Jeon
Yann Thoma
Jan-Willem C. Alffenaar
Sophie Stocker
author_sort Asad E. Patanwala
collection DOAJ
description Purpose. To assess the agreement in 24-hour area under the curve (AUC24) value estimates between commonly used vancomycin population pharmacokinetic models in the critically ill. Materials and Methods. Adults admitted to intensive care who received intravenous vancomycin and had a serum vancomycin concentration available were included. AUC24 values were determined using Tucuxi (revision cd7bd7a8) for dosing intervals with a vancomycin concentration using three models (Goti 2018, Colin 2019, and Thomson 2009) previously evaluated in the critically ill. AUC24 values were categorized as subtherapeutic (<400 mg·h/L), therapeutic (400–600 mg·h/L), or toxic (>600 mg·h/L), assuming a minimum inhibitory concentration of 1 mg/L. AUC24 value categorization was compared across the three models and reported as percent agreement. Results. Overall, 466 AUC24 values were estimated in 188 patients. Overall, 52%, 42%, and 47% of the AUC24 values were therapeutic for the Goti, Colin, and Thomson models, respectively. The agreement of AUC24 values between all three models was 48% (223/466), Goti-Colin 59% (193/466), Goti-Thomson 68% (318/466), and Colin-Thomson 67% (314/466). Conclusion. In critically ill patients, vancomycin AUC24 values obtained from different pharmacokinetic models are often discordant, potentially contributing to differences in dosing decisions. This highlights the importance of selecting the optimal model.
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spelling doaj-art-65ef147781c243f1a13c3723693b9b552025-02-03T06:08:15ZengWileyCritical Care Research and Practice2090-13132022-01-01202210.1155/2022/7011376Discrepancies Between Bayesian Vancomycin Models Can Affect Clinical Decisions in the Critically IllAsad E. Patanwala0Danijela Spremo1Minji Jeon2Yann Thoma3Jan-Willem C. Alffenaar4Sophie Stocker5Faculty of Medicine and HealthDepartment of PharmacyDepartment of PharmacyREDSFaculty of Medicine and HealthFaculty of Medicine and HealthPurpose. To assess the agreement in 24-hour area under the curve (AUC24) value estimates between commonly used vancomycin population pharmacokinetic models in the critically ill. Materials and Methods. Adults admitted to intensive care who received intravenous vancomycin and had a serum vancomycin concentration available were included. AUC24 values were determined using Tucuxi (revision cd7bd7a8) for dosing intervals with a vancomycin concentration using three models (Goti 2018, Colin 2019, and Thomson 2009) previously evaluated in the critically ill. AUC24 values were categorized as subtherapeutic (<400 mg·h/L), therapeutic (400–600 mg·h/L), or toxic (>600 mg·h/L), assuming a minimum inhibitory concentration of 1 mg/L. AUC24 value categorization was compared across the three models and reported as percent agreement. Results. Overall, 466 AUC24 values were estimated in 188 patients. Overall, 52%, 42%, and 47% of the AUC24 values were therapeutic for the Goti, Colin, and Thomson models, respectively. The agreement of AUC24 values between all three models was 48% (223/466), Goti-Colin 59% (193/466), Goti-Thomson 68% (318/466), and Colin-Thomson 67% (314/466). Conclusion. In critically ill patients, vancomycin AUC24 values obtained from different pharmacokinetic models are often discordant, potentially contributing to differences in dosing decisions. This highlights the importance of selecting the optimal model.http://dx.doi.org/10.1155/2022/7011376
spellingShingle Asad E. Patanwala
Danijela Spremo
Minji Jeon
Yann Thoma
Jan-Willem C. Alffenaar
Sophie Stocker
Discrepancies Between Bayesian Vancomycin Models Can Affect Clinical Decisions in the Critically Ill
Critical Care Research and Practice
title Discrepancies Between Bayesian Vancomycin Models Can Affect Clinical Decisions in the Critically Ill
title_full Discrepancies Between Bayesian Vancomycin Models Can Affect Clinical Decisions in the Critically Ill
title_fullStr Discrepancies Between Bayesian Vancomycin Models Can Affect Clinical Decisions in the Critically Ill
title_full_unstemmed Discrepancies Between Bayesian Vancomycin Models Can Affect Clinical Decisions in the Critically Ill
title_short Discrepancies Between Bayesian Vancomycin Models Can Affect Clinical Decisions in the Critically Ill
title_sort discrepancies between bayesian vancomycin models can affect clinical decisions in the critically ill
url http://dx.doi.org/10.1155/2022/7011376
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