Abstract

Aim: This study aimed to evaluate the current status of vancomycin population pharmacokinetic modeling and assess four pharmacokinetic prediction models for predicting vancomycin blood levels in patients receiving intravenous vancomycin at our hospital. The goal was to establish a basis for personalized vancomycin dosing to minimize adverse reactions.
Materials and methods: This retrospective study analyzed patients receiving intravenous vancomycin treatment for infections at the First Affiliated Hospital of Shantou University Medical College from January 2021 to December 2023. Patient data, including demographics and vancomycin treatment specifics, were retrieved from the hospital’s integrated healthcare workstation. We evaluated the predictive performance of four vancomycin dosing algorithms using PE, APE, and p-value to assess their accuracy in forecasting steady-state vancomycin blood trough concentrations. Additionally, paired t-tests were conducted to examine the correlation between measured and predicted values across the four models.
Results: The Vancomycin Individualized Dosing Platform, Smart Dose as well as the Vancomycin Dosage Recommendation and Blood Concentration Prediction System had substandard mean prediction errors and mean absolute prediction errors, all of which were poorly predictive for all age groups.
Conclusion: Of the four pharmacokinetic prediction models assessed, only the Vancomycin Calculator accurately predicted vancomycin dosing for adult non-critical patients aged 18 – 59 years at our hospital. The other three models demonstrated suboptimal performance and did not achieve the necessary level of predictive accuracy. It is essential to exercise caution when using unvalidated pharmacokinetic models. Although the Vancomycin Calculator performed well, the other models need thorough validation before being used clinically, especially in diverse populations and settings.

Author Details

Authors

• Chuzhu Huang
• Jia Wang
• Yan Chen
• Yilin Huang
• Zhuomin Wu

Departments

• The First Affiliated Hospital of Shantou University Medical College, Shantou, China

Address

Zhuomin Wu
The First Affiliated Hospital of Shantou
University Medical College
Shantou 515041, China
Email: [email protected]

Citation