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Metabolites in Blood for Prediction of Bacteremic Sepsis in the Emergency Room
Department of Clinical Microbiology, Clinical Bacteriology, the Laboratory for Molecular Infection Medicine Sweden (MIMS), Umeå University, Umeå, Sweden; Umeå Centre for Microbial Research, Umeå University, Umeå, Sweden.
Department of Clinical Microbiology, Clinical Bacteriology, the Laboratory for Molecular Infection Medicine Sweden (MIMS), Umeå University, Umeå, Sweden; Umeå Centre for Microbial Research, Umeå University, Umeå, Sweden.
Department of Infectious Diseases, Örebro University Hospital, Örebro, Sweden.
Department of Laboratory Medicine, Faculty of Medicine and Health, Örebro University, Örebro, Sweden.
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2016 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 11, no 1, article id e0147670Article in journal (Refereed) Published
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Abstract [en]

A metabolomics approach for prediction of bacteremic sepsis in patients in the emergency room (ER) was investigated. In a prospective study, whole blood samples from 65 patients with bacteremic sepsis and 49 ER controls were compared. The blood samples were analyzed using gas chromatography coupled to time-of-flight mass spectrometry. Multivariate and logistic regression modeling using metabolites identified by chromatography or using conventional laboratory parameters and clinical scores of infection were employed. A predictive model of bacteremic sepsis with 107 metabolites was developed and validated. The number of metabolites was reduced stepwise until identifying a set of 6 predictive metabolites. A 6-metabolite predictive logistic regression model showed a sensitivity of 0.91(95% CI 0.69-0.99) and a specificity 0.84 (95% CI 0.58-0.94) with an AUC of 0.93 (95% CI 0.89-1.01). Myristic acid was the single most predictive metabolite, with a sensitivity of 1.00 (95% CI 0.85-1.00) and specificity of 0.95 (95% CI 0.74-0.99), and performed better than various combinations of conventional laboratory and clinical parameters. We found that a metabolomics approach for analysis of acute blood samples was useful for identification of patients with bacteremic sepsis. Metabolomics should be further evaluated as a new tool for infection diagnostics.

Place, publisher, year, edition, pages
Public Library Science , 2016. Vol. 11, no 1, article id e0147670
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Infectious Medicine
Research subject
Infectious Diseases
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URN: urn:nbn:se:oru:diva-48479DOI: 10.1371/journal.pone.0147670ISI: 000368655300138PubMedID: 26800189OAI: oai:DiVA.org:oru-48479DiVA, id: diva2:906050
Note

Funding Agencies:

Umeå University

Västerbotten County Council VLL-151871  VLL-495291  VLL-495361

Available from: 2016-02-23 Created: 2016-02-23 Last updated: 2018-09-11Bibliographically approved

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