Evidence map›Paper›PMID 37210541›Full record

Observational studyCritical care (London, England)2023

Biomarker-based risk model to predict persistent multiple organ dysfunctions after congenital heart surgery: a prospective observational cohort study.

Alexis L Benscoter, Jeffrey A Alten, Mihir R Atreya, David S Cooper, Jonathan W Byrnes, David P Nelson, Nicholas J Ollberding, Hector R Wong

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in Critical care (London, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.9field-weighted citation impact, top 25% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 4 institutions in 1 country.

Alexis L BenscoterDivision of Cardiology, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, 3333 Burnet Ave, MLC 2003, Cincinnati, OH, 45229, USA. alexis.benscoter@cchmc.org.
Jeffrey A AltenDivision of Cardiology, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, 3333 Burnet Ave, MLC 2003, Cincinnati, OH, 45229, USA.
Mihir R AtreyaDivision of Pediatric Critical Care Medicine, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati, Cincinnati, OH, USA.
David S CooperDivision of Cardiology, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, 3333 Burnet Ave, MLC 2003, Cincinnati, OH, 45229, USA.
Jonathan W ByrnesDivision of Cardiology, Department of Pediatrics, University of Alabama at Birmingham, Birmingham, AL, USA.
David P NelsonDivision of Pediatric Critical Care Medicine, Department of Pediatrics, University of Kentucky, Lexington, KY, USA.
Nicholas J OllberdingDivision of Biostatistics and Epidemiology, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati, Cincinnati, OH, USA.
Hector R WongDivision of Pediatric Critical Care Medicine, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati, Cincinnati, OH, USA.
Cincinnati Children's Hospital Medical Center · USUniversity of Cincinnati · USUniversity of Alabama at Birmingham · USUniversity of Kentucky · US

Funding

Supplement for MIRA award_Wong_2021R35GM126943 · NIGMS · CINCINNATI CHILDRENS HOSP MED CTR · PI ALDER, MATTHEW N · 2018 to 2022
$2.7M
National Institution of Health R35GM126943NIGMS NIH HHS R35 GM126943
6 · The paper itself

Abstract

backgroundMultiple organ dysfunction syndrome (MODS) is an important cause of post-operative morbidity and mortality for children undergoing cardiac surgery requiring cardiopulmonary bypass (CPB). Dysregulated inflammation is widely regarded as a key contributor to bypass-related MODS pathobiology, with considerable overlap of pathways associated with septic shock. The pediatric sepsis biomarker risk model (PERSEVERE) is comprised of seven protein biomarkers of inflammation and reliably predicts baseline risk of mortality and organ dysfunction among critically ill children with septic shock. We aimed to determine if PERSEVERE biomarkers and clinical data could be combined to derive a new model to assess the risk of persistent CPB-related MODS in the early post-operative period.

methodsThis study included 306 patients < 18 years old admitted to a pediatric cardiac ICU after surgery requiring cardiopulmonary bypass (CPB) for congenital heart disease. Persistent MODS, defined as dysfunction of two or more organ systems on postoperative day 5, was the primary outcome. PERSEVERE biomarkers were collected 4 and 12 h after CPB. Classification and regression tree methodology were used to derive a model to assess the risk of persistent MODS.

resultsThe optimal model containing interleukin-8 (IL-8), chemokine ligand 3 (CCL3), and age as predictor variables had an area under the receiver operating characteristic curve (AUROC) of 0.86 (0.81-0.91) for differentiating those with or without persistent MODS and a negative predictive value of 99% (95-100). Ten-fold cross-validation of the model yielded a corrected AUROC of 0.75 (0.68-0.84).

conclusionsWe present a novel risk prediction model to assess the risk for development of multiple organ dysfunction after pediatric cardiac surgery requiring CPB. Pending prospective validation, our model may facilitate identification of a high-risk cohort to direct interventions and studies aimed at improving outcomes via mitigation of post-operative organ dysfunction.

Indexed as

Cardiopulmonary BypassHeart Defects, CongenitalMultiple Organ FailureBiomarkersChild, PreschoolCohort StudiesCritical CareHumansInfantProspective StudiesShock, SepticBiomarkersBiomarkersCardiopulmonary bypassInflammationMultiple organ dysfunctionPediatric cardiac critical careRisk stratification

Identifiers

PMID37210541
PMCPMC10199562
OpenAlexW4377137872

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.