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

Autor: Sara M. Camp, Yves A. Lussier, Juliet Ndukum, Nancy Casanova, Christian Bime, Charles A. Downs, Joe G.N. Garcia, Ivo Abraham, Edmund J. Miller, Armand Mekontso-Dessap, Radu C. Oita, Darrick Carter, Heather Lynn
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Male
ARDS
Interleukin-1beta
Nicotinamide phosphoribosyltransferase
Vesicular Transport Proteins
Critical Care and Intensive Care Medicine
Logistic regression
law.invention
chemistry.chemical_compound
0302 clinical medicine
law
Nicotinamide Phosphoribosyltransferase
APACHE
0303 health sciences
Respiratory Distress Syndrome
lcsh:Medical emergencies. Critical care. Intensive care. First aid
Predictive analytics
Middle Aged
Intensive care unit
Latent class model
3. Good health
Intramolecular Oxidoreductases
Latent Class Analysis
Cohort
Biomarker (medicine)
Cytokines
Female
Adult
medicine.medical_specialty
Risk Assessment
03 medical and health sciences
Internal medicine
medicine
Humans
Mortality
Macrophage Migration-Inhibitory Factors
Sphingosine-1-Phosphate Receptors
030304 developmental biology
business.industry
Interleukin-6
Research
Interleukin-8
lcsh:RC86-88.9
medicine.disease
Peptide Fragments
Clinical trial
Interleukin 1 Receptor Antagonist Protein
Logistic Models
030228 respiratory system
chemistry
business
Biomarkers
Zdroj: Critical Care, Vol 23, Iss 1, Pp 1-8 (2019)
Critical Care
ISSN: 1364-8535
Popis: 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.
Databáze: OpenAIRE
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