Evidence map›Paper›PMID 37577648›Full record

ArticleResearch square2023

External validation and biomarker assessment of a high-risk, data-driven pediatric sepsis phenotype characterized by persistent hypoxemia, encephalopathy, and shock.

Mihir R Atreya, Tellen D Bennett, Alon Geva, E Vincent S Faustino, Colin M Rogerson, Riad Lutfi, Natalie Z Cvijanovich, Michael T Bigham, Jeffrey Nowak, Adam J Schwarz and 6 more

Open access · greenAbstract readPreprint
In one paragraph

Article in Research square, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

16 authors at 13 institutions in 1 country.

Mihir R AtreyaDivision of Critical Care Medicine, Cincinnati Children's Hospital Medical Center and Cincinnati Children's Research Foundation, Cincinnati, 45229, OH, USA.
Tellen D BennettDepartments of Pediatrics and Biomedical Informatics, University of Colorado School of Medicine, Aurora, CO.
Alon GevaDepartment of Anesthesiology, Critical Care, and Pain Medicine, Boston Children's Hospital, Boston, MA; Computational Health Informatics Program, Boston Children's Hospital, Boston, MA.
E Vincent S FaustinoDepartment of Pediatrics, Yale School of Medicine, New Haven, CT.
Colin M RogersonDepartment of Pediatrics, Riley Hospital for Children, Indianapolis, IN 46202, USA.
Riad LutfiDepartment of Pediatrics, Riley Hospital for Children, Indianapolis, IN 46202, USA.
Natalie Z CvijanovichDepartment of Pediatrics, UCSF Benioff Children's Hospital Oakland, Oakland, CA 94609, USA.
Michael T BighamDepartment of Pediatrics, Akron Children's Hospital, Akron, OH 44308, USA.
Jeffrey NowakDepartment of Pediatrics, Children's Hospital and Clinics of Minnesota, Minneapolis, MN 55404, USA.
Adam J SchwarzChildren's Hospital of Orange County, Orange, CA 92868, USA.
Torrey BainesUniversity of Florida Health Shands Children's Hospital, Gainesville, FL 32610, USA.
Bereketeab HaileselassieDepartment of Pediatrics, Lucile Packard Children's Hospital Stanford, Palo Alto, CA 94304, USA.
Neal J ThomasDepartment of Pediatrics, Penn State Hershey Children's Hospital, Hershey, PA 17033, USA.
Yuan LuoDepartment of Pediatrics, Northwestern University Feinberg School of Medicine, Chicago, 60611, IL, USA.
L Nelson Sanchez-PintoDepartment of Pediatrics, Northwestern University Feinberg School of Medicine, Chicago, 60611, IL, USA.
Novel Data-Driven Sepsis Phenotypes in Children Study and the Genomics of Pediatric Septic Shock Investigators.
Northwestern University · USRiley Hospital for Children · USAkron Children's Hospital · USBoston Children's Hospital · USChildren's Hospital of Orange County · USChildren’s Minnesota - St. Paul Hospital · USCincinnati Children's Hospital Medical Center · USLucile Packard Children's Hospital · USPenn State Milton S. Hershey Medical Center · USUCSF Benioff Children's Hospital · USUF Health Shands Hospital · USUniversity of Colorado Denver · USYale University · US

Funding

A Data-Driven Analysis of Pediatric Organ Dysfunction Patterns To Discover Sepsis PhenotypesR21HD096402 · NICHD · LURIE CHILDREN'S HOSPITAL OF CHICAGO · PI SANCHEZ-PINTO, LAZARO NELSON · 2019 to 2020
$541k
NICHD NIH HHS R21 HD096402
6 · The paper itself

Abstract

Objective: Identification of children with sepsis-associated multiple organ dysfunction syndrome (MODS) at risk for poor outcomes remains a challenge. Data-driven phenotyping approaches that leverage electronic health record (EHR) data hold promise given the widespread availability of EHRs. We sought to externally validate the data-driven 'persistent hypoxemia, encephalopathy, and shock' (PHES) phenotype and determine its association with inflammatory and endothelial biomarkers, as well as biomarker-based pediatric risk-strata. Design: We trained and validated a random forest classifier using organ dysfunction subscores in the EHR dataset used to derive the PHES phenotype. We used the classifier to assign phenotype membership in a test set consisting of prospectively enrolled pediatric septic shock patients. We compared biomarker profiles of those with and without the PHES phenotype and determined the association with established biomarker-based mortality and MODS risk-strata. Setting: 25 pediatric intensive care units (PICU) across the U.S. Patients: EHR data from 15,246 critically ill patients sepsis-associated MODS and 1,270 pediatric septic shock patients in the test cohort of whom 615 had biomarker data. Interventions: None. Measurements and Main Results: The area under the receiver operator characteristic curve (AUROC) of the new classifier to predict PHES phenotype membership was 0.91(95%CI, 0.90-0.92) in the EHR validation set. In the test set, patients with the PHES phenotype were independently associated with both increased odds of complicated course (adjusted odds ratio [aOR] of 4.1, 95%CI: 3.2-5.4) and 28-day mortality (aOR of 4.8, 95%CI: 3.11-7.25) after controlling for age, severity of illness, and immuno-compromised status. Patients belonging to the PHES phenotype were characterized by greater degree of systemic inflammation and endothelial activation, and overlapped with high risk-strata based on PERSEVERE biomarkers predictive of death and persistent MODS. Conclusions: The PHES trajectory-based phenotype is reproducible, independently associated with poor clinical outcomes, and overlap with higher risk-strata based on validated biomarker approaches.

Indexed as

BiomarkersCritical CareEndothelial DysfunctionMultiple Organ Dysfunction SyndromePediatricsPrecision MedicineSepsisSystemic Inflammation

Identifiers

PMID37577648
PMCPMC10418531
OpenAlexW4385483407

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.