Multiple Model Optimal Sampling Promotes Accurate Vancomycin Area-Under-the-Curve Estimation Using a Single Sample in Critically Ill Children

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. The authors prospectively enrolled critically ill children receiving intravenous (IV) vancomyc...

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Published inTherapeutic drug monitoring Vol. 47; no. 4; p. 512
Main Authors Downes, Kevin J, Sharova, Anna, Malone, Judith, Odom John, Audrey R, Zuppa, Athena F, Neely, Michael N
Format Journal Article
LanguageEnglish
Published United States 01.08.2025
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Abstract 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. 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). 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. Optimal sampling supports accurate Bayesian estimation of vancomycin AUC from a single plasma sample in critically ill children.
AbstractList 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. 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). 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. Optimal sampling supports accurate Bayesian estimation of vancomycin AUC from a single plasma sample in critically ill children.
Author Malone, Judith
Zuppa, Athena F
Downes, Kevin J
Neely, Michael N
Sharova, Anna
Odom John, Audrey R
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Issue 4
Keywords limited sampling
Bayesian estimation
pediatric infectious diseases
sepsis
therapeutic drug monitoring
Language English
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Snippet Area-under-the-curve (AUC)-directed vancomycin therapy is recommended; however, AUC estimation in critically ill children is difficult owing to the need for...
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StartPage 512
SubjectTerms Adolescent
Anti-Bacterial Agents - blood
Anti-Bacterial Agents - pharmacokinetics
Anti-Bacterial Agents - therapeutic use
Area Under Curve
Bayes Theorem
Child
Child, Preschool
Critical Illness
Drug Monitoring - methods
Female
Humans
Infant
Male
Models, Biological
Prospective Studies
Vancomycin - administration & dosage
Vancomycin - blood
Vancomycin - pharmacokinetics
Vancomycin - therapeutic use
Title Multiple Model Optimal Sampling Promotes Accurate Vancomycin Area-Under-the-Curve Estimation Using a Single Sample in Critically Ill Children
URI https://www.ncbi.nlm.nih.gov/pubmed/39846757
Volume 47
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