ArticleJournal of pediatric intensive care2022
Use of Electronic Health Records to Identify Exposure-Response Relationships in Critically Ill Children: An Example of Midazolam and Delirium.
Kanecia O Zimmerman, Tracy G Spears, Marjan Cobbaert, Felix Boakye-Agyeman, Huali Wu, Michael Cohen-Wolkowiez, Kevin M Watt, Daniel K Benjamin, Mara L Becker, Chani Traube and 1 more
Open access · greenAbstract read
In one paragraphArticle in Journal of pediatric intensive care, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 96% of its field
1 · What the graph read from itWhat 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 registryThe 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 literatureWho cites it
0 citing papers in PubMed, 0 citations in OpenAlex.
No citing paper in PubMed yet.
4 · The recordCorrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what moneyAuthors and funding
11 authors at 2 institutions in 1 country.
Kanecia O ZimmermanDuke Clinical Research Institute, Duke University School of Medicine, Durham, North Carolina, United States.
Tracy G SpearsDuke Clinical Research Institute, Duke University School of Medicine, Durham, North Carolina, United States.
Marjan CobbaertDuke Clinical Research Institute, Duke University School of Medicine, Durham, North Carolina, United States.ORCID 0000-0002-3559-8909 Felix Boakye-AgyemanDuke Clinical Research Institute, Duke University School of Medicine, Durham, North Carolina, United States.ORCID 0000-0002-7333-375X Huali WuDuke Clinical Research Institute, Duke University School of Medicine, Durham, North Carolina, United States.
Michael Cohen-WolkowiezDuke Clinical Research Institute, Duke University School of Medicine, Durham, North Carolina, United States.ORCID 0000-0002-2458-2266 Kevin M WattDuke Clinical Research Institute, Duke University School of Medicine, Durham, North Carolina, United States.
Daniel K BenjaminDuke Clinical Research Institute, Duke University School of Medicine, Durham, North Carolina, United States.
Mara L BeckerDuke Clinical Research Institute, Duke University School of Medicine, Durham, North Carolina, United States.
Chani TraubeDivision of Critical Care Medicine, Weill Cornell Medical College, New York City, New York, United States.ORCID 0000-0003-1863-7950 P Brian SmithDuke Clinical Research Institute, Duke University School of Medicine, Durham, North Carolina, United States.
Duke University · USCornell University · US
Funding
Project-005U2COD023375 · OD · DUKE UNIVERSITY · PI Linda S Adair, Phillip Brian Smith · 2016 to 2026
$215.9MCOVID-19 Supplement - Center for Innovative TRIals in ChilDrEN and AdulTs (TRIDENT)U24TR001608 · NCATS · DUKE UNIVERSITY · PI BENJAMIN, DANIEL K., BERNARD, GORDON RAPHAEL · 2016 to 2022
$177.0MDuke CTSA (Composite)KL2TR001115 · NCATS · DUKE UNIVERSITY · PI BOULWARE, LEIGH E, KRAFT, MONICA · 2013 to 2017
$5.1MIdentifying Pharmacogenomic Predictors of Methotrexate Response and Metabolite Biotransformation in JIAR01HD089928 · NICHD · CINCINNATI CHILDRENS HOSP MED CTR · PI BECKER, MARA LEIGH, THOMPSON, SUSAN D · 2017 to 2021
$2.8MPhysiologically-Based Pharmacokinetic Approach to Determine Dosing on Extracorporeal Life SupportR01HD097775 · NICHD · UNIVERSITY OF UTAH · PI WATT, KEVIN M · 2019 to 2023
$2.7MPhysiologically-Based Pharmacokinetic Models for Optimal Drug Dosing in ChildrenR01HD076676 · NICHD · DUKE UNIVERSITY · PI COHEN-WOLKOWIEZ, MICHAEL · 2014 to 2017
$2.6MMentorship of early-career pediatricians in quantitiative methods and therapeuticK24HD058735 · NICHD · DUKE UNIVERSITY · PI BENJAMIN, DANIEL K. · 2009 to 2018
$1.5MPhysiologically Based Pharmacokinetics in Critically Ill ChildrenK23HD075891 · NICHD · DUKE UNIVERSITY · PI WATT, KEVIN M · 2014 to 2018
$638kInvestigating polypharmacy-related adverse events in critically ill children using electronic health records and simulated drug levelsK23HD091398 · NICHD · DUKE UNIVERSITY · PI ZIMMERMAN, KANECIA OBIE · 2017 to 2020
$629kNCATS NIH HHS KL2 TR001115NCATS NIH HHS U24 TR001608NIAID NIH HHS HHSN272201300017CNIAID NIH HHS HHSN272201300017INIAID NIH HHS HHSN272201500006CNICHD NIH HHS HHSN267200700051CNICHD NIH HHS HHSN275201000003CNICHD NIH HHS HHSN275201000003INICHD NIH HHS K23 HD075891NICHD NIH HHS K23 HD091398NICHD NIH HHS K24 HD058735NICHD NIH HHS R01 HD076676NICHD NIH HHS R01 HD089928NICHD NIH HHS R01 HD097775NIH HHS U2C OD023375
6 · The paper itselfAbstract
Adverse drug events are common in critically ill children and often result from systemic or target organ drug exposure. Methods of drug dosing and titration that consider pharmacokinetic alterations may improve our ability to optimally dose critically ill patients and reduce the risk for drug-related adverse events. To demonstrate this possibility, we explored the exposure-response relationship between midazolam and delirium in critically ill children. We retrospectively examined electronic health records (EHRs) of critically ill children <18 years of age hospitalized in the pediatric intensive care unit at Duke University; these children were administered midazolam during mechanical ventilation and had ≥1 Cornell Assessment of Pediatric Delirium (CAPD) score. We used individual-level data extracted from the EHR and a previously published population pharmacokinetic (PK) model developed in critically ill children to simulate plasma concentrations at the time of CAPD scores in 1,000 representative datasets. We used multilevel repeated measures models, with clustering at patient and simulation levels, to evaluate the associations between measures of drug exposure (e.g., concentration and area under concentration time curve) and delirium scores. We included 61 children, median age 1.5 years (range = 0.1-16.3), with 181 CAPD assessments. We identified similarities between simulated Empirical Bayesian parameter estimates from the EHR cohort and those from the PK model population. We identified a stronger association between drug concentration at the time of score and CAPD scores (coefficient 1.78; 95% confidence interval: 1.66-1.90) compared with cumulative dose per kilogram and CAPD scores (coefficient -0.01; 95% confidence interval: -0.01 to -0.01). EHR and PK models can be leveraged to investigate exposure-response relationships in critically ill children.
Indexed as
critically ill childrendeliriummidazolam
Identifiers
PMID36388077
PMCPMC9649289
OpenAlexW3137565897
What OpenQuestion holds
Textmetadata
Read underepoch 390