Fast differentiation of SIRS and sepsis from blood plasma of ICU patients using Raman spectroscopy

Authors

  • Ute Neugebauer,

    Corresponding author
    1. Center for Sepsis Control and Care, Jena University Hospital, Jena, Germany
    2. Leibniz Institute of Photonic Technology, Jena, Germany
    • Phone: +49 3641 9 32 33 64, Fax: +49 3641 9 32 33 81

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  • Sabine Trenkmann,

    1. Center for Sepsis Control and Care, Jena University Hospital, Jena, Germany
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  • Thomas Bocklitz,

    1. Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Jena, Germany
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  • Diana Schmerler,

    1. Institute of Clinical Chemistry and Laboratory Diagnostics, Jena University Hospital, Jena, Germany
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  • Michael Kiehntopf,

    1. Center for Sepsis Control and Care, Jena University Hospital, Jena, Germany
    2. Institute of Clinical Chemistry and Laboratory Diagnostics, Jena University Hospital, Jena, Germany
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    • MK and JP share the senior authorship.

  • Jürgen Popp

    1. Center for Sepsis Control and Care, Jena University Hospital, Jena, Germany
    2. Leibniz Institute of Photonic Technology, Jena, Germany
    3. Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Jena, Germany
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    • MK and JP share the senior authorship.


Abstract

Currently, there is no biomarker that can reliable distinguish between infectious and non-infectious systemic inflammatory response syndrome (SIRS). However, such a biomarker would be of utmost importance for early identification and stratification of patients at risk to initiate timely and appropriate antibiotic treatment.

Within this proof of principle study, the high potential of Raman spectroscopy for the fast differentiation of non-infectious SIRS and sepsis is demonstrated. Blood plasma collected from 70 patients from the intensive care unit (31 patients with sepsis and 39 patients classified with SIRS without infection) was analyzed by means of Raman spectroscopy. A PCA-LDA based classification model was trained with Raman spectra from test samples and yielded for sepsis a sensitivity of 1.0 and specificity of 0.82. These results have been confirmed with an independent dataset (prediction accuracy 80%). (© 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)

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