Frontiers in medicine · 2026
Vancomycin population pharmacokinetics in patients with burns.
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Shi Yan, Yao Yijin, He Xiaoshuang, Bian Xiaolan, Yu Xunben, Fang Jie, Wang Huan, Dou Yi
Аннотация
BACKGROUND: Vancomycin is used to treat severe infections caused by methicillin-resistant gram-positive bacteria such as methicillin-resistant Staphylococcus aureus (MRSA). Although several pharmacokinetic studies on vancomycin in burn patients have been reported, a robust population pharmacokinetic model based on routine therapeutic drug monitoring data from a large cohort is still lacking. This study aimed to develop a PopPK model for vancomycin in adult burn patients and evaluate its predictive performance.
METHODS: Serum vancomycin concentrations from 93 burn patients were analyzed using non-linear mixed-effects modeling. Covariates including age, gender, creatinine clearance (CrCL), BMI, burn cause, and burn area were evaluated using stepwise forward selection and backward elimination. Model stability was assessed by bootstrap. Predictive performance was compared with Clincalc in 9 external burn patients.
RESULTS: A one-compartment model best described vancomycin PK in burn patients. The final model identified CrCL as a significant covariate on clearance: CL (L/h) = 6.73 × (CrCL/111.67)0.708, with a volume of distribution of 49.1 L. Bootstrap analysis confirmed good model stability. Our model demonstrated superior predictive accuracy compared with Clincalc.
CONCLUSION: Vancomycin clearance is increased in burn patients and significantly correlated with CrCL. The developed PopPK model provides a reliable basis for individualized vancomycin dosing in this specific population.
METHODS: Serum vancomycin concentrations from 93 burn patients were analyzed using non-linear mixed-effects modeling. Covariates including age, gender, creatinine clearance (CrCL), BMI, burn cause, and burn area were evaluated using stepwise forward selection and backward elimination. Model stability was assessed by bootstrap. Predictive performance was compared with Clincalc in 9 external burn patients.
RESULTS: A one-compartment model best described vancomycin PK in burn patients. The final model identified CrCL as a significant covariate on clearance: CL (L/h) = 6.73 × (CrCL/111.67)0.708, with a volume of distribution of 49.1 L. Bootstrap analysis confirmed good model stability. Our model demonstrated superior predictive accuracy compared with Clincalc.
CONCLUSION: Vancomycin clearance is increased in burn patients and significantly correlated with CrCL. The developed PopPK model provides a reliable basis for individualized vancomycin dosing in this specific population.