Use of a Combination Biomarker Algorithm To Identify Medical Intensive Care Unit Patients with Suspected Sepsis at Very Low Likelihood of Bacterial Infection.

TitleUse of a Combination Biomarker Algorithm To Identify Medical Intensive Care Unit Patients with Suspected Sepsis at Very Low Likelihood of Bacterial Infection.
Publication TypeJournal Article
Year of Publication2015
AuthorsHan JH, Nachamkin I, Coffin SE, Gerber JS, Fuchs B, Garrigan C, Han X, Bilker WB, Wise JA, Tolomeo P, Lautenbach E
Corporate AuthorsPrevention Epicenters Program of the Centers for Disease Control and Prevention
JournalAntimicrob Agents Chemother
Volume59
Issue10
Pagination6494-500
Date Published2015 Oct
ISSN1098-6596
Abstract

Sepsis remains a diagnostic challenge in the intensive care unit (ICU), and the use of biomarkers may help in differentiating bacterial sepsis from other causes of systemic inflammatory syndrome (SIRS). The goal of this study was to assess test characteristics of a number of biomarkers for identifying ICU patients with a very low likelihood of bacterial sepsis. A prospective cohort study was conducted in a medical ICU of a university hospital. Immunocompetent patients with presumed bacterial sepsis were consecutively enrolled from January 2012 to May 2013. Concentrations of nine biomarkers (α-2 macroglobulin, C-reactive protein [CRP], ferritin, fibrinogen, haptoglobin, procalcitonin [PCT], serum amyloid A, serum amyloid P, and tissue plasminogen activator) were determined at baseline and at 24 h, 48 h, and 72 h after enrollment. Performance characteristics were calculated for various combinations of biomarkers for discrimination of bacterial sepsis from other causes of SIRS. Seventy patients were included during the study period; 31 (44%) had bacterial sepsis, and 39 (56%) had other causes of SIRS. PCT and CRP values were significantly higher at all measured time points in patients with bacterial sepsis. A number of combinations of PCT and CRP, using various cutoff values and measurement time points, demonstrated high negative predictive values (81.1% to 85.7%) and specificities (63.2% to 79.5%) for diagnosing bacterial sepsis. Combinations of PCT and CRP demonstrated a high ability to discriminate bacterial sepsis from other causes of SIRS in medical ICU patients. Future studies should focus on the use of these algorithms to improve antibiotic use in the ICU setting.

DOI10.1128/AAC.00958-15
Alternate JournalAntimicrob. Agents Chemother.
PubMed ID26239984
PubMed Central IDPMC4576082
Grant ListFOA CK11-001 / CK / NCEZID CDC HHS / United States
K01-AI103028 / AI / NIAID NIH HHS / United States