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Critical Care
Published in: Critical Care 1/2019

Open Access 01-12-2019 | Acute Respiratory Distress-Syndrome | Research

Development of a biomarker mortality risk model in acute respiratory distress syndrome

Authors: Christian Bime, Nancy Casanova, Radu C. Oita, Juliet Ndukum, Heather Lynn, Sara M. Camp, Yves Lussier, Ivo Abraham, Darrick Carter, Edmund J. Miller, Armand Mekontso-Dessap, Charles A. Downs, Joe G. N. Garcia

Published in: Critical Care | Issue 1/2019

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Abstract

Background

There is a compelling unmet medical need for biomarker-based models to risk-stratify patients with acute respiratory distress syndrome. Effective stratification would optimize participant selection for clinical trial enrollment by focusing on those most likely to benefit from new interventions. Our objective was to develop a prognostic, biomarker-based model for predicting mortality in adult patients with acute respiratory distress syndrome.

Methods

This is a secondary analysis using a cohort of 252 mechanically ventilated subjects with the diagnosis of acute respiratory distress syndrome. Survival to day 7 with both day 0 (first day of presentation) and day 7 sample availability was required. Blood was collected for biomarker measurements at first presentation to the intensive care unit and on the seventh day. Biomarkers included cytokine-chemokines, dual-functioning cytozymes, and vascular injury markers. Logistic regression, latent class analysis, and classification and regression tree analysis were used to identify the plasma biomarkers most predictive of 28-day ARDS mortality.

Results

From eight biologically relevant biomarker candidates, six demonstrated an enhanced capacity to predict mortality at day 0. Latent-class analysis identified two biomarker-based phenotypes. Phenotype A exhibited significantly higher plasma levels of angiopoietin-2, macrophage migration inhibitory factor, interleukin-8, interleukin-1 receptor antagonist, interleukin-6, and extracellular nicotinamide phosphoribosyltransferase (eNAMPT) compared to phenotype B. Mortality at 28 days was significantly higher for phenotype A compared to phenotype B (32% vs 19%, p = 0.04).

Conclusions

An adult biomarker-based risk model reliably identifies ARDS subjects at risk of death within 28 days of hospitalization.
Appendix
Available only for authorised users
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Metadata
Title
Development of a biomarker mortality risk model in acute respiratory distress syndrome
Authors
Christian Bime
Nancy Casanova
Radu C. Oita
Juliet Ndukum
Heather Lynn
Sara M. Camp
Yves Lussier
Ivo Abraham
Darrick Carter
Edmund J. Miller
Armand Mekontso-Dessap
Charles A. Downs
Joe G. N. Garcia
Publication date
01-12-2019
Publisher
BioMed Central
Published in
Critical Care / Issue 1/2019
Electronic ISSN: 1364-8535
DOI
https://doi.org/10.1186/s13054-019-2697-x

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