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 in | Therapeutic drug monitoring Vol. 47; no. 4; p. 512 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
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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. |
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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 |
Author_xml | – sequence: 1 givenname: Kevin J orcidid: 0000-0001-5015-8146 surname: Downes fullname: Downes, Kevin J organization: Department of Pediatrics, Perelman School of Medicine of the University of Pennsylvania, Philadelphia, Pennsylvania – sequence: 2 givenname: Anna surname: Sharova fullname: Sharova, Anna organization: Clinical Futures, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania – sequence: 3 givenname: Judith surname: Malone fullname: Malone, Judith organization: Clinical Futures, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania – sequence: 4 givenname: Audrey R surname: Odom John fullname: Odom John, Audrey R organization: Department of Pediatrics, Perelman School of Medicine of the University of Pennsylvania, Philadelphia, Pennsylvania – sequence: 5 givenname: Athena F surname: Zuppa fullname: Zuppa, Athena F organization: Janssen Pharmaceuticals, Horsham, Pennsylvania – sequence: 6 givenname: Michael N surname: Neely fullname: Neely, Michael N organization: Keck School of Medicine of the University of Southern California, Los Angeles, California |
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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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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 |
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