alexa Metabolomics as a novel approach for early diagnosis of pediatric septic shock and its mortality.
Bioinformatics & Systems Biology

Bioinformatics & Systems Biology

Metabolomics:Open Access

Author(s): Mickiewicz B, Vogel HJ, Wong HR, Winston BW

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Abstract RATIONALE: Septic shock is a significant cause of morbidity and mortality in the pediatric population. Early recognition of septic shock and appropriate treatment increase survival rate; thus, developing new diagnostic tools may improve patients' outcomes. OBJECTIVES: To determine whether a metabolomics approach could be useful in the diagnosis and prognosis of septic shock in pediatric intensive care unit (PICUs). METHODS: Serum samples were collected from 60 patients with septic shock, 40 PICU patients with systemic inflammatory response syndrome (not suspected of having an infection), and 40 healthy children. Proton nuclear magnetic resonance spectroscopy spectra were analyzed and quantified using targeted profiling methodology. MEASUREMENTS AND MAIN RESULTS: Multivariate statistical analysis was applied to detect specific patterns in metabolic profiles and to highlight differences between patient samples. Supervised analysis afforded good predictive models and managed to separate patient populations. Some of the metabolite concentrations identified in serum samples changed markedly, indicating their influence on the separation between patient groups. These metabolites represent a composite biopattern of the pediatric metabolic response to septic shock and might be considered as the basis for a biomarker panel for the diagnosis of septic shock and its mortality in PICU. CONCLUSIONS: Our results indicate that nuclear magnetic resonance metabolite profiling might serve as a promising approach for the diagnosis and prediction of mortality in septic shock in a pediatric population and that quantitative metabolomics methods can be applied in the clinical evaluations of pediatric septic shock.
This article was published in Am J Respir Crit Care Med and referenced in Metabolomics:Open Access

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