OBJECTIVE: To define a biomarker panel to predict organ dysfunction, shock, and in-hospital mortality in emergency department (ED) patients with suspected sepsis. DESIGN: Prospective observational study. SETTING: EDs of ten academic medical centers. PATIENTS: There were 971 patients enrolled. INCLUSION CRITERIA: 1) ED patients age > 18; 2) suspected infection or a serum lactate level > 2.5 mmol/L; and 3) two or more systemic inflammatory response syndrome criteria. EXCLUSION CRITERIA: pregnancy, do-not-resuscitate status, or cardiac arrest. MEASUREMENTS AND MAIN RESULTS: Nine biomarkers were assayed from blood draws obtained on ED presentation. Multivariable logistic regression was used to identify an optimal combination of biomarkers to create a panel. The derived formula for weighting biomarker values was used to calculate a "sepsis score," which was the predicted probability of the primary outcome of severe sepsis (sepsis plus organ dysfunction) within 72 hrs. We also assessed the ability of the sepsis score to predict secondary outcome measures of septic shock within 72 hrs and in-hospital mortality. The overall rates of each outcome were severe sepsis, 52%; septic shock, 39%; and in-hospital mortality 7%. Among the nine biomarkers tested, the optimal 3-marker panel was neutrophil gelatinase-associated lipocalin, protein C, and interleukin-1 receptor antagonist. The area under the curve for the accuracy of the sepsis score derived from these three biomarkers was 0.80 for severe sepsis, 0.77 for septic shock, and 0.79 for death. When included in multivariate models with clinical variables, the sepsis score remained highly significant (p < 0.001) for all the three outcomes. CONCLUSIONS: A biomarker panel of neutrophil gelatinase-associated lipocalin, interleukin-1ra, and Protein C was predictive of severe sepsis, septic shock, and death in ED patients with suspected sepsis. Further study is warranted to prospectively validate the clinical utility of these biomarkers and the sepsis score in risk-stratifying patients with suspected sepsis.
OBJECTIVE: To define a biomarker panel to predict organ dysfunction, shock, and in-hospital mortality in emergency department (ED) patients with suspected sepsis. DESIGN: Prospective observational study. SETTING: EDs of ten academic medical centers. PATIENTS: There were 971 patients enrolled. INCLUSION CRITERIA: 1) ED patients age > 18; 2) suspected infection or a serum lactate level > 2.5 mmol/L; and 3) two or more systemic inflammatory response syndrome criteria. EXCLUSION CRITERIA: pregnancy, do-not-resuscitate status, or cardiac arrest. MEASUREMENTS AND MAIN RESULTS: Nine biomarkers were assayed from blood draws obtained on ED presentation. Multivariable logistic regression was used to identify an optimal combination of biomarkers to create a panel. The derived formula for weighting biomarker values was used to calculate a "sepsis score," which was the predicted probability of the primary outcome of severe sepsis (sepsis plus organ dysfunction) within 72 hrs. We also assessed the ability of the sepsis score to predict secondary outcome measures of septic shock within 72 hrs and in-hospital mortality. The overall rates of each outcome were severe sepsis, 52%; septic shock, 39%; and in-hospital mortality 7%. Among the nine biomarkers tested, the optimal 3-marker panel was neutrophil gelatinase-associated lipocalin, protein C, and interleukin-1 receptor antagonist. The area under the curve for the accuracy of the sepsis score derived from these three biomarkers was 0.80 for severe sepsis, 0.77 for septic shock, and 0.79 for death. When included in multivariate models with clinical variables, the sepsis score remained highly significant (p < 0.001) for all the three outcomes. CONCLUSIONS: A biomarker panel of neutrophil gelatinase-associated lipocalin, interleukin-1ra, and Protein C was predictive of severe sepsis, septic shock, and death in ED patients with suspected sepsis. Further study is warranted to prospectively validate the clinical utility of these biomarkers and the sepsis score in risk-stratifying patients with suspected sepsis.
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