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64. Novel Biomarkers Improve Estimation of Vancomycin Clearance in Critically Ill Children

BACKGROUND: There are a paucity of robust population PK (popPK) models to inform vancomycin (VAN) dosing in critically ill children. The majority of published models incorporate peak/trough data and rely on flawed estimates of renal function. We sought to develop a popPK model for IV VAN in critical...

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Autores principales: Downes, Kevin J, Zuppa, Athena F, Sharova, Anna, Gianchetti, Lauren, Duffey, Emily, Goldstein, Stuart L, Neely, Michael
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
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Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8643886/
http://dx.doi.org/10.1093/ofid/ofab466.064
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author Downes, Kevin J
Zuppa, Athena F
Sharova, Anna
Gianchetti, Lauren
Duffey, Emily
Goldstein, Stuart L
Neely, Michael
author_facet Downes, Kevin J
Zuppa, Athena F
Sharova, Anna
Gianchetti, Lauren
Duffey, Emily
Goldstein, Stuart L
Neely, Michael
author_sort Downes, Kevin J
collection PubMed
description BACKGROUND: There are a paucity of robust population PK (popPK) models to inform vancomycin (VAN) dosing in critically ill children. The majority of published models incorporate peak/trough data and rely on flawed estimates of renal function. We sought to develop a popPK model for IV VAN in critically ill children utilizing novel plasma and urinary biomarkers. METHODS: We conducted a prospective observational study of critically ill children prescribed VAN for a suspected infection in the CHOP pediatric ICU. Children < 1 year of age and those receiving ECMO or CRRT were excluded. Five VAN samples were collected from a single dosing interval for each subject. Plasma biomarkers (creatinine [Cr], cystatin C [CysC], NGAL) and urinary biomarkers (CysC, NGAL, KIM-1, osteopontin) were collected the morning of PK sampling; urinary biomarkers were corrected for urine creatinine. Nonparametric popPK modeling was performed using Pmetrics. The impact of renal function (GFR) on VAN clearance (CL) was estimated first, comparing model performance with each biomarker (Cr and plasma CysC). The influence of age, sex, additional biomarkers, PIM3 score, and receipt of vasopressors as covariates was then assessed for relevant PK parameters. RESULTS: 30 subjects completed the study. Median age was 10 years (range 1-17); 76% were male. The majority (90%) of children received VAN for suspected sepsis. PK sampling occurred at a median of 37.7 hours (range 24.6-94.8) into VAN treatment; 136 VAN samples were included. A 2-compartment model with fixed allometric scaling of 0.75 on clearances and 1 on volumes best described the data. CysC-based GFR as a covariate on VAN CL using the HOEK formula (GFR = -4.32 + (80.35/CysC)) resulted in the best model fit. Age and plasma NGAL were also informative on VAN CL in the final model (Figure 1). During model building, urinary NGAL was also associated with VAN CL (comparable to plasma NGAL) and outperformed Cr, although it was not retained in the final model. Figure 1. Final population PK model and parameter estimates. [Image: see text] CONCLUSION: Plasma CysC is a better renal function estimate than Cr to inform VAN clearance in critically ill children. Urinary and plasma NGAL also improved estimation of VAN CL during popPK modeling. Novel biomarkers can better describe VAN exposures in critically ill children than reliance on Cr alone. DISCLOSURES: Kevin J. Downes, MD, Merck (Individual(s) Involved: Self): Grant/Research Support Stuart L. Goldstein, MD, Bioporto (Consultant, Grant/Research Support)
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spelling pubmed-86438862021-12-06 64. Novel Biomarkers Improve Estimation of Vancomycin Clearance in Critically Ill Children Downes, Kevin J Zuppa, Athena F Sharova, Anna Gianchetti, Lauren Duffey, Emily Goldstein, Stuart L Neely, Michael Open Forum Infect Dis Oral Abstracts BACKGROUND: There are a paucity of robust population PK (popPK) models to inform vancomycin (VAN) dosing in critically ill children. The majority of published models incorporate peak/trough data and rely on flawed estimates of renal function. We sought to develop a popPK model for IV VAN in critically ill children utilizing novel plasma and urinary biomarkers. METHODS: We conducted a prospective observational study of critically ill children prescribed VAN for a suspected infection in the CHOP pediatric ICU. Children < 1 year of age and those receiving ECMO or CRRT were excluded. Five VAN samples were collected from a single dosing interval for each subject. Plasma biomarkers (creatinine [Cr], cystatin C [CysC], NGAL) and urinary biomarkers (CysC, NGAL, KIM-1, osteopontin) were collected the morning of PK sampling; urinary biomarkers were corrected for urine creatinine. Nonparametric popPK modeling was performed using Pmetrics. The impact of renal function (GFR) on VAN clearance (CL) was estimated first, comparing model performance with each biomarker (Cr and plasma CysC). The influence of age, sex, additional biomarkers, PIM3 score, and receipt of vasopressors as covariates was then assessed for relevant PK parameters. RESULTS: 30 subjects completed the study. Median age was 10 years (range 1-17); 76% were male. The majority (90%) of children received VAN for suspected sepsis. PK sampling occurred at a median of 37.7 hours (range 24.6-94.8) into VAN treatment; 136 VAN samples were included. A 2-compartment model with fixed allometric scaling of 0.75 on clearances and 1 on volumes best described the data. CysC-based GFR as a covariate on VAN CL using the HOEK formula (GFR = -4.32 + (80.35/CysC)) resulted in the best model fit. Age and plasma NGAL were also informative on VAN CL in the final model (Figure 1). During model building, urinary NGAL was also associated with VAN CL (comparable to plasma NGAL) and outperformed Cr, although it was not retained in the final model. Figure 1. Final population PK model and parameter estimates. [Image: see text] CONCLUSION: Plasma CysC is a better renal function estimate than Cr to inform VAN clearance in critically ill children. Urinary and plasma NGAL also improved estimation of VAN CL during popPK modeling. Novel biomarkers can better describe VAN exposures in critically ill children than reliance on Cr alone. DISCLOSURES: Kevin J. Downes, MD, Merck (Individual(s) Involved: Self): Grant/Research Support Stuart L. Goldstein, MD, Bioporto (Consultant, Grant/Research Support) Oxford University Press 2021-12-04 /pmc/articles/PMC8643886/ http://dx.doi.org/10.1093/ofid/ofab466.064 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of Infectious Diseases Society of America. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Oral Abstracts
Downes, Kevin J
Zuppa, Athena F
Sharova, Anna
Gianchetti, Lauren
Duffey, Emily
Goldstein, Stuart L
Neely, Michael
64. Novel Biomarkers Improve Estimation of Vancomycin Clearance in Critically Ill Children
title 64. Novel Biomarkers Improve Estimation of Vancomycin Clearance in Critically Ill Children
title_full 64. Novel Biomarkers Improve Estimation of Vancomycin Clearance in Critically Ill Children
title_fullStr 64. Novel Biomarkers Improve Estimation of Vancomycin Clearance in Critically Ill Children
title_full_unstemmed 64. Novel Biomarkers Improve Estimation of Vancomycin Clearance in Critically Ill Children
title_short 64. Novel Biomarkers Improve Estimation of Vancomycin Clearance in Critically Ill Children
title_sort 64. novel biomarkers improve estimation of vancomycin clearance in critically ill children
topic Oral Abstracts
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8643886/
http://dx.doi.org/10.1093/ofid/ofab466.064
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