Multiple Model Optimal Sampling Promotes Accurate Vancomycin Area-Under-the-Curve Estimation Using a Single Sample in
Kevin J Downes1,2,3,4, Anna Sharova1,2, Judith Malone1,2
1Center for Clinical Pharmacology, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania.
Insights
Accurate vancomycin (AUC) monitoring in critically ill children is now possible using Bayesian estimation from a single, optimally timed blood sample. This method simplifies therapeutic drug monitoring and improves patient care.
Area of Science:
- Pharmacokinetics and Pharmacodynamics
- Pediatric Critical Care
- Therapeutic Drug Monitoring
Background:
- Area-under-the-curve (AUC)-guided vancomycin therapy is recommended for efficacy and safety.
- Estimating vancomycin AUC in critically ill children is challenging due to complex sampling requirements and limited predictive models.
Purpose of the Study:
- To evaluate the accuracy of Bayesian estimation of vancomycin AUC using a single, optimally timed blood sample in critically ill children.
- To determine if a simplified sampling strategy can achieve reliable AUC estimations.
Main Methods:
- Prospective enrollment of critically ill children receiving intravenous vancomycin.
- Identification of an optimal single sample time using population pharmacokinetic modeling (Pmetrics) and a multiple model optimal function.
- Individual Bayesian AUC estimation using the optimal sample versus all available samples via InsightRx NOVA software.
Main Results:
- Optimal sampling times were highly variable; trough samples were optimal in 32% of children.
- Bayesian AUC estimation using a single optimal sample demonstrated low bias (0.4% ±5.9%) and imprecision (4.6% ±3.6%) compared to all samples.
- Bias was <10% for 94% of participants using the optimal single sample method.
Conclusions:
- A single, optimally timed plasma sample enables accurate Bayesian estimation of vancomycin AUC in critically ill children.
- This approach simplifies vancomycin therapeutic drug monitoring in this vulnerable population.
Background:
Area-under-the-curve (AUC)-directed vancomycin therapy is recommended; however, AUC estimation in critically ill children is difficult owing to the need for multiple samples and lack of informative models.
Methods:
The authors prospectively enrolled critically ill children receiving intravenous (IV) vancomycin for suspected infection and evaluated the accuracy of Bayesian estimation of AUC from a single, optimally timed sample. During the dosing interval, when clinical therapeutic drug monitoring was performed, an optimally timed sample was collected, which was determined for each subject using an established population pharmacokinetic model and the multiple model optimal function of Pmetrics, a nonparametric population pharmacokinetic modeling software. The model was embedded in InsightRx NOVA (InsightRx, Inc.) for individual Bayesian estimation of AUC using the optimal sample versus all available samples (optimally timed sample + clinical samples).
Results:
Eighteen children were included. The optimal sampling time to inform Bayesian estimation of vancomycin AUC was highly variable, with trough samples being optimally informative in 32% of children. Optimal samples were collected by clinical nurses within 15 minutes of the goal time in 14 of 18 participants (78%). Compared with all samples, Bayesian AUC estimation with optimal samples had a mean bias of 0.4% (±5.9%) and mean imprecision of 4.6% (±3.6%). Bias of optimal sampling was <10% for 17 of the 18 participants (94%). When estimating AUC using only a peak sample (≤2 hours after dose) or only a trough (≤30 minutes before next dose), bias was <10% for 78% and 86% of participants, respectively.
Conclusions:
Optimal sampling supports accurate Bayesian estimation of vancomycin AUC from a single plasma sample in critically ill children.
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