Evidence map›Paper›PMID 35451072›Full record

ArticleClinical pharmacology and therapeutics2022

Use of Real-World Data and Physiologically-Based Pharmacokinetic Modeling to Characterize Enoxaparin Disposition in Children With Obesity.

Jacqueline G Gerhart, Fernando O Carreño, Matthew Shane Loop, Craig R Lee, Andrea N Edginton, Jaydeep Sinha, Karan R Kumar, Carl M Kirkpatrick, Christoph P Hornik, Daniel Gonzalez and 1 more

Open access · hybridAbstract read
In one paragraph

Article in Clinical pharmacology and therapeutics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 2 pooled it
5.4field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

20 citing papers in PubMed, 2 syntheses or guidelines pooled it, 26 citations in OpenAlex.

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  18. Perioperative Acetaminophen Dosing in Obese Children.Children (Basel, Switzerland) · 2023
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 4 institutions in 3 countries.

Jacqueline G GerhartDivision of Pharmacotherapy and Experimental Therapeutics, University of North Carolina Eshelman School of Pharmacy, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.ORCID 0000-0003-4679-4638
Fernando O CarreñoDivision of Pharmacotherapy and Experimental Therapeutics, University of North Carolina Eshelman School of Pharmacy, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.ORCID 0000-0002-4921-5235
Matthew Shane LoopDivision of Pharmacotherapy and Experimental Therapeutics, University of North Carolina Eshelman School of Pharmacy, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.ORCID 0000-0001-9442-4573
Craig R LeeDivision of Pharmacotherapy and Experimental Therapeutics, University of North Carolina Eshelman School of Pharmacy, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.ORCID 0000-0003-3595-5301
Andrea N EdgintonSchool of Pharmacy, University of Waterloo, Waterloo, Ontario, Canada.ORCID 0000-0002-9014-1653
Jaydeep SinhaDivision of Pharmacotherapy and Experimental Therapeutics, University of North Carolina Eshelman School of Pharmacy, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.ORCID 0000-0002-2110-3370
Karan R KumarDuke Clinical Research Institute, Durham, North Carolina, USA.ORCID 0000-0001-9196-6350
Carl M KirkpatrickCentre for Medicine Use and Safety, Monash University, Melbourne, Victoria, Australia.ORCID 0000-0002-5715-1534
Christoph P HornikDuke Clinical Research Institute, Durham, North Carolina, USA.ORCID 0000-0001-7056-8759
Daniel GonzalezDivision of Pharmacotherapy and Experimental Therapeutics, University of North Carolina Eshelman School of Pharmacy, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.ORCID 0000-0001-5522-5686
Best Pharmaceuticals for Children Act - Pediatric Trials Network Steering Committee
University of North Carolina at Chapel Hill · USDuke University · USMonash University · AUUniversity of Waterloo · CA

Funding

Safety of Sildenafil in Premature Infants with Severe Bronchopulmonary DysplasiaR33HL147833 · NHLBI · DUKE UNIVERSITY · PI HORNIK, CHRISTOPH, LAUGHON, MATTHEW · 2021 to 2023
$6.8M
Application of Physiologically-Based Pharmacokinetic Modeling to Characterize Drug-Drug Interactions in InfantsR01HD102949 · NICHD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Daniel Gonzalez · 2021 to 2026
$3.0M
Physiologically-Based Pharmacokinetic Modeling to Guide Drug Dosing in Children with ObesityR01HD096435 · NICHD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI DUMOND, JULIE BRUMER · 2018 to 2022
$2.0M
CPCCRNRL1HD107784 · NICHD · DUKE UNIVERSITY · PI Christoph Hornik · 2021 to 2026
$952k
Enhancement Training for the Next Generation of Translational Ph.D. ScientistsT32GM122741 · NIGMS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI WOLBERG, ALISA S., YEH, JEN JEN · 2018 to 2022
$898k
Safety of Sildenafil in Premature Infants with Severe Bronchopulmonary DysplasiaR61HL147833 · NHLBI · DUKE UNIVERSITY · PI HORNIK, CHRISTOPH, LAUGHON, MATTHEW · 2019 to 2020
$775k
Pediatric Critical Care Research Landscape - A National Expert ConferenceR13HD102136 · NICHD · DUKE UNIVERSITY · PI HORNIK, CHRISTOPH, ZIMMERMAN, KANECIA OBIE · 2020 to 2020
$60k
FDA HHS R01 FD006099FDA HHS U18 FD006298NHLBI NIH HHS R33 HL147833NHLBI NIH HHS R61 HL147833NICHD NIH HHS R01 HD096435NICHD NIH HHS R01 HD102949NICHD NIH HHS R13 HD102136NICHD NIH HHS RL1 HD107784NIGMS NIH HHS T32 GM122741
6 · The paper itself

Abstract

Dosing guidance for children with obesity is often unknown despite the fact that nearly 20% of US children are classified as obese. Enoxaparin, a commonly prescribed low-molecular-weight heparin, is dosed based on body weight irrespective of obesity status to achieve maximum concentration within a narrow therapeutic or prophylactic target range. However, whether children with and without obesity experience equivalent enoxaparin exposure remains unclear. To address this clinical question, 2,825 anti-activated factor X (anti-Xa) surrogate concentrations were collected from the electronic health records of 596 children, including those with obesity. Using linear mixed-effects regression models, we observed that 4-hour anti-Xa concentrations were statistically significantly different in children with and without obesity, even for children with the same absolute dose (P = 0.004). To further mechanistically explore obesity-associated differences in anti-Xa concentration, a pediatric physiologically-based pharmacokinetic (PBPK) model was developed in adults, and then scaled to children with and without obesity. This PBPK model incorporated binding of enoxaparin to antithrombin to form anti-Xa and elimination via heparinase-mediated metabolism and glomerular filtration. Following scaling, the PBPK model predicted real-world pediatric concentrations well, with an average fold error (standard deviation of the fold error) of 0.82 (0.23) and 0.87 (0.26) in children with and without obesity, respectively. PBPK model simulations revealed that children with obesity have at most 20% higher 4-hour anti-Xa concentrations under recommended, total body weight-based dosing compared to children without obesity owing to reduced weight-normalized clearance. Enoxaparin exposure was better matched across age groups and obesity status using fat-free mass weight-based dosing.

Indexed as

EnoxaparinVenous ThromboembolismAdultAnticoagulantsChildHeparin, Low-Molecular-WeightHumansObesityAnticoagulantsEnoxaparinHeparin, Low-Molecular-Weight

Identifiers

PMID35451072
PMCPMC9504927
OpenAlexW4224291920

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.