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 |
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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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