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The occurrence of sepsis and its relevant multiple organ dysfunction remain a major problem in intensive care units with high morbidity and mortality. The differentiation between non-infectious and infectious etiologies, severity and organ function evaluation, and prognostic assessment are all challenging in routine clinical practice. Many biomarkers have been suggested for these purpose; however sensitivity and specificity even of high-ranking biomarkers still remain insufficient. Recently, metabolic profiling has attracted interest for biomarker discovery. In this study, LC-MS/MS will be perform to identify serum metabolic biomarkers for differentiation of SIRS/sepsis, severity and organ function evaluation, and prognostic assessment among 65 patients. The investigators enrolled 35 patients who were diagnosed with sepsis, 15 patients who were diagnosed with SIRS, and 15 normal patients. Moreover, the sepsis were further divided into sepsis, severe sepsis, and sepsis patients before death. Small metabolites that were present in patient serum samples were measured by LC-MS/MS techniques and analyzed using multivariate statistical methods, such as Principal Component Analysis (PCA), Partial Least Squares-Discriminant Analysis (PLS-DA), and Orthogonal Partial Least Squares Discriminant Analysis. Based on the multivariate statistical analysis above, the investigators could distinguish sepsis from normal and SIRS; distinguish the difference among sepsis, severe sepsis and death. We hypothesis that some metabolites as identified in this study are promising biomarker candidates in the field of sepsis diagnosis and treatment.
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65 participants in 5 patient groups
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Data sourced from clinicaltrials.gov
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