A Two-Biomarker Model Predicts Mortality in the Critically Ill with Sepsis
Improving the prospective identification of patients with systemic inflammatory response syndrome (SIRS) and sepsis at low risk for organ dysfunction and death is a major clinical challenge. To develop and validate a multibiomarker-based prediction model for 28-day mortality in critically ill patien...
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Published in | American journal of respiratory and critical care medicine Vol. 196; no. 8; pp. 1004 - 1011 |
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Main Authors | , , , , , , , , , , , |
Format | Journal Article |
Language | English |
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United States
American Thoracic Society
15.10.2017
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Abstract | Improving the prospective identification of patients with systemic inflammatory response syndrome (SIRS) and sepsis at low risk for organ dysfunction and death is a major clinical challenge.
To develop and validate a multibiomarker-based prediction model for 28-day mortality in critically ill patients with SIRS and sepsis.
A derivation cohort (n = 888) and internal test cohort (n = 278) were taken from a prospective study of critically ill intensive care unit (ICU) patients meeting two of four SIRS criteria at an academic medical center for whom plasma was obtained within 24 hours. The validation cohort (n = 759) was taken from a prospective cohort enrolled at another academic medical center ICU for whom plasma was obtained within 48 hours. We measured concentrations of angiopoietin-1, angiopoietin-2, IL-6, IL-8, soluble tumor necrosis factor receptor-1, soluble vascular cell adhesion molecule-1, granulocyte colony-stimulating factor, and soluble Fas.
We identified a two-biomarker model in the derivation cohort that predicted mortality (area under the receiver operator characteristic curve [AUC], 0.79; 95% confidence interval [CI], 0.74-0.83). It performed well in the internal test cohort (AUC, 0.75; 95% CI, 0.65-0.85) and the external validation cohort (AUC, 0.77; 95% CI, 0.72-0.83). We determined a model score threshold demonstrating high negative predictive value (0.95) for death. In addition to a low risk of death, patients below this threshold had shorter ICU length of stay, lower incidence of acute kidney injury, acute respiratory distress syndrome, and need for vasopressors.
We have developed a simple, robust biomarker-based model that identifies patients with SIRS/sepsis at low risk for death and organ dysfunction. |
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AbstractList | Rationale:
Improving the prospective identification of patients with systemic inflammatory response syndrome (SIRS) and sepsis at low risk for organ dysfunction and death is a major clinical challenge.
Objectives:
To develop and validate a multibiomarker-based prediction model for 28-day mortality in critically ill patients with SIRS and sepsis.
Methods:
A derivation cohort (n = 888) and internal test cohort (n = 278) were taken from a prospective study of critically ill intensive care unit (ICU) patients meeting two of four SIRS criteria at an academic medical center for whom plasma was obtained within 24 hours. The validation cohort (n = 759) was taken from a prospective cohort enrolled at another academic medical center ICU for whom plasma was obtained within 48 hours. We measured concentrations of angiopoietin-1, angiopoietin-2, IL-6, IL-8, soluble tumor necrosis factor receptor-1, soluble vascular cell adhesion molecule-1, granulocyte colony–stimulating factor, and soluble Fas.
Measurements and Main Results:
We identified a two-biomarker model in the derivation cohort that predicted mortality (area under the receiver operator characteristic curve [AUC], 0.79; 95% confidence interval [CI], 0.74–0.83). It performed well in the internal test cohort (AUC, 0.75; 95% CI, 0.65–0.85) and the external validation cohort (AUC, 0.77; 95% CI, 0.72–0.83). We determined a model score threshold demonstrating high negative predictive value (0.95) for death. In addition to a low risk of death, patients below this threshold had shorter ICU length of stay, lower incidence of acute kidney injury, acute respiratory distress syndrome, and need for vasopressors.
Conclusions:
We have developed a simple, robust biomarker-based model that identifies patients with SIRS/sepsis at low risk for death and organ dysfunction. Improving the prospective identification of patients with systemic inflammatory response syndrome (SIRS) and sepsis at low risk for organ dysfunction and death is a major clinical challenge. To develop and validate a multibiomarker-based prediction model for 28-day mortality in critically ill patients with SIRS and sepsis. A derivation cohort (n = 888) and internal test cohort (n = 278) were taken from a prospective study of critically ill intensive care unit (ICU) patients meeting two of four SIRS criteria at an academic medical center for whom plasma was obtained within 24 hours. The validation cohort (n = 759) was taken from a prospective cohort enrolled at another academic medical center ICU for whom plasma was obtained within 48 hours. We measured concentrations of angiopoietin-1, angiopoietin-2, IL-6, IL-8, soluble tumor necrosis factor receptor-1, soluble vascular cell adhesion molecule-1, granulocyte colony-stimulating factor, and soluble Fas. We identified a two-biomarker model in the derivation cohort that predicted mortality (area under the receiver operator characteristic curve [AUC], 0.79; 95% confidence interval [CI], 0.74-0.83). It performed well in the internal test cohort (AUC, 0.75; 95% CI, 0.65-0.85) and the external validation cohort (AUC, 0.77; 95% CI, 0.72-0.83). We determined a model score threshold demonstrating high negative predictive value (0.95) for death. In addition to a low risk of death, patients below this threshold had shorter ICU length of stay, lower incidence of acute kidney injury, acute respiratory distress syndrome, and need for vasopressors. We have developed a simple, robust biomarker-based model that identifies patients with SIRS/sepsis at low risk for death and organ dysfunction. Notably, the APACHE III score requires measurement of multiple variables over a 24-hour time period, limiting its utility for early clinical decision-making. [...]our simple model may represent a good alternative for early mortality prediction in this patient population. [...]we did not include several clinical measurements commonly used for assessment of severity including arterial lactate, procalcitonin, or C-reactive protein (42-46). [...]our external validation cohort was recruited over an extended period of time. [...]although in this study we aimed for a parsimonious and easily clinically applicable model, other biomarkers (IL-6, Ang-1, Ang-2, sVCAM-1) did have some, albeit limited, incremental prognostic value. Improving the prospective identification of patients with systemic inflammatory response syndrome (SIRS) and sepsis at low risk for organ dysfunction and death is a major clinical challenge.RATIONALEImproving the prospective identification of patients with systemic inflammatory response syndrome (SIRS) and sepsis at low risk for organ dysfunction and death is a major clinical challenge.To develop and validate a multibiomarker-based prediction model for 28-day mortality in critically ill patients with SIRS and sepsis.OBJECTIVESTo develop and validate a multibiomarker-based prediction model for 28-day mortality in critically ill patients with SIRS and sepsis.A derivation cohort (n = 888) and internal test cohort (n = 278) were taken from a prospective study of critically ill intensive care unit (ICU) patients meeting two of four SIRS criteria at an academic medical center for whom plasma was obtained within 24 hours. The validation cohort (n = 759) was taken from a prospective cohort enrolled at another academic medical center ICU for whom plasma was obtained within 48 hours. We measured concentrations of angiopoietin-1, angiopoietin-2, IL-6, IL-8, soluble tumor necrosis factor receptor-1, soluble vascular cell adhesion molecule-1, granulocyte colony-stimulating factor, and soluble Fas.METHODSA derivation cohort (n = 888) and internal test cohort (n = 278) were taken from a prospective study of critically ill intensive care unit (ICU) patients meeting two of four SIRS criteria at an academic medical center for whom plasma was obtained within 24 hours. The validation cohort (n = 759) was taken from a prospective cohort enrolled at another academic medical center ICU for whom plasma was obtained within 48 hours. We measured concentrations of angiopoietin-1, angiopoietin-2, IL-6, IL-8, soluble tumor necrosis factor receptor-1, soluble vascular cell adhesion molecule-1, granulocyte colony-stimulating factor, and soluble Fas.We identified a two-biomarker model in the derivation cohort that predicted mortality (area under the receiver operator characteristic curve [AUC], 0.79; 95% confidence interval [CI], 0.74-0.83). It performed well in the internal test cohort (AUC, 0.75; 95% CI, 0.65-0.85) and the external validation cohort (AUC, 0.77; 95% CI, 0.72-0.83). We determined a model score threshold demonstrating high negative predictive value (0.95) for death. In addition to a low risk of death, patients below this threshold had shorter ICU length of stay, lower incidence of acute kidney injury, acute respiratory distress syndrome, and need for vasopressors.MEASUREMENTS AND MAIN RESULTSWe identified a two-biomarker model in the derivation cohort that predicted mortality (area under the receiver operator characteristic curve [AUC], 0.79; 95% confidence interval [CI], 0.74-0.83). It performed well in the internal test cohort (AUC, 0.75; 95% CI, 0.65-0.85) and the external validation cohort (AUC, 0.77; 95% CI, 0.72-0.83). We determined a model score threshold demonstrating high negative predictive value (0.95) for death. In addition to a low risk of death, patients below this threshold had shorter ICU length of stay, lower incidence of acute kidney injury, acute respiratory distress syndrome, and need for vasopressors.We have developed a simple, robust biomarker-based model that identifies patients with SIRS/sepsis at low risk for death and organ dysfunction.CONCLUSIONSWe have developed a simple, robust biomarker-based model that identifies patients with SIRS/sepsis at low risk for death and organ dysfunction. |
Author | Hahn, William O. Radella, Frank Katz, Ronit Liles, W. Conrad Robinson-Cohen, Cassianne Harju-Baker, Susanna Christiani, David C. Mikacenic, Carmen Himmelfarb, Jonathan Price, Brenda L. Wurfel, Mark M. O’Mahony, D. Shane |
Author_xml | – sequence: 1 givenname: Carmen surname: Mikacenic fullname: Mikacenic, Carmen organization: Division of Pulmonary and Critical Care Medicine, Department of Medicine – sequence: 2 givenname: Brenda L. surname: Price fullname: Price, Brenda L. organization: Department of Biostatistics – sequence: 3 givenname: Susanna surname: Harju-Baker fullname: Harju-Baker, Susanna organization: Division of Pulmonary and Critical Care Medicine, Department of Medicine – sequence: 4 givenname: D. Shane surname: O’Mahony fullname: O’Mahony, D. Shane organization: Department of Pulmonary and Critical Care Medicine, Swedish Medical Center, Seattle, Washington – sequence: 5 givenname: Cassianne surname: Robinson-Cohen fullname: Robinson-Cohen, Cassianne organization: Kidney Research Institute, and – sequence: 6 givenname: Frank surname: Radella fullname: Radella, Frank organization: Division of Pulmonary and Critical Care Medicine, Department of Medicine – sequence: 7 givenname: William O. surname: Hahn fullname: Hahn, William O. organization: Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle, Washington – sequence: 8 givenname: Ronit surname: Katz fullname: Katz, Ronit organization: Kidney Research Institute, and – sequence: 9 givenname: David C. surname: Christiani fullname: Christiani, David C. organization: Division of Pulmonary and Critical Care Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts; and, Department of Environmental Health, Harvard School of Public Health, Boston, Massachusetts – sequence: 10 givenname: Jonathan surname: Himmelfarb fullname: Himmelfarb, Jonathan organization: Kidney Research Institute, and – sequence: 11 givenname: W. Conrad surname: Liles fullname: Liles, W. Conrad organization: Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle, Washington – sequence: 12 givenname: Mark M. surname: Wurfel fullname: Wurfel, Mark M. organization: Division of Pulmonary and Critical Care Medicine, Department of Medicine |
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Keywords | tumor necrosis factor receptor systemic inflammatory response syndrome IL-8 biomarkers sepsis |
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Snippet | Improving the prospective identification of patients with systemic inflammatory response syndrome (SIRS) and sepsis at low risk for organ dysfunction and death... Notably, the APACHE III score requires measurement of multiple variables over a 24-hour time period, limiting its utility for early clinical decision-making.... Rationale: Improving the prospective identification of patients with systemic inflammatory response syndrome (SIRS) and sepsis at low risk for organ... |
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SubjectTerms | Adult Aged Aged, 80 and over Angiopoietins - blood Apoptosis Biomarkers Biomarkers - blood Cell adhesion & migration Cohort Studies Critical Illness - mortality Female Granulocyte Colony-Stimulating Factor - blood Granulocytes Hospitals Human subjects Humans Intensive care Male Middle Aged Mortality Original Patients Plasma Predictive Value of Tests Prospective Studies Respiratory distress syndrome Sepsis Sepsis - blood Sepsis - mortality Systemic Inflammatory Response Syndrome - blood Tumor Necrosis Factor-alpha - blood Tumor necrosis factor-TNF Variables Vascular Cell Adhesion Molecule-1 - blood |
Title | A Two-Biomarker Model Predicts Mortality in the Critically Ill with Sepsis |
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