Biomarkers for predicting disease severity in emergency department patients with suspected infection

Risk stratification on the broad patient population visiting the emergency department (ED) is
challenging. To differentiate between the patients with severe infections, who need immediate
antibiotic treatment, and patients with a mild infection, who might be treated at home, physicians
use a combination of vital signs and laboratory results. A combination of novel biomarkers with
clinical parameters might help identify patients at risk for developing sepsis at an early stage on the
ED. Patients with a high risk might be treated earlier or more intensively. Patients with a low risk
might be sent home, reducing antibiotics use and preventing hospital admission, thus reducing
health care cost. The aim of this study is to create a clinical prediction and decision-making model
for disease severity and mortality in patients with a suspected infection on the ED using a
combination of biomarkers and clinical parameters.

Novel biomarkers can aid in the early identification of sepsis, and can be useful for risk stratification at the ED in patients with a suspected infection.

March 2019 start inclusion
Quarter 3 2020 inclusion finished