The role of metabolomic markers for patients with infectious diseases: implications for risk stratification and therapeutic modulation.

INTRODUCTION: Metabolomics is a rapidly growing area of research. Metabolomic markers can provide information about the interaction of different organ systems, and thereby improve the understanding of physio-pathological processes, disease risk, prognosis and therapy responsiveness in a variety of diseases. Areas covered: In this narrative review of recent clinical studies investigating metabolomic markers in adult patients presenting with acute infectious disease, we mainly focused on patients with sepsis and lower respiratory tract infections. Currently, there is a growing body of literature showing that single metabolites from distinct metabolic pathways, as well as more complex metabolomic signatures are associated with disease severity and outcome in patients with systemic infections. These pathways include, among others, metabolomic markers of oxidative stress, steroid hormone and amino acid pathways, and nutritional markers. Expert commentary: Metabolic profiling has great potential to optimize patient management, to provide new targets for individual therapy and thereby improve survival of patients. At this stage, research mainly focused on the identification of new predictive signatures and less on metabolic determinants to predict treatment response. The transition from observational studies to implementation of novel markers into clinical practice is the next crucial step to prove the usefulness of metabolomic markers in patient care.

Biological pathways underlying the association of red cell distribution width and adverse clinical outcome: Results of a prospective cohort study.

BACKGROUND: Red cell distribution width (RDW) predicts disease outcome in several patient populations, but its prognostic value in addition to other disease parameters in unselected medical inpatients remains unclear. Our aim was to investigate the association of admission RDW levels and mortality adjusted for several disease pathways in unselected medical patients from a previous multicenter study. METHODS: We included consecutive adult, medical patients at the time point of hospital admission through the emergency department into this observational, cohort study. The primary endpoint was mortality at 30-day. To study association of admission RDW and outcomes, we calculated regression analysis with step-wise inclusion of clinical and laboratory parameters from different biological pathways. RESULTS: The 30-day mortality of the 4273 included patients was 5.6% and increased from 1.4% to 14.3% from the lowest to the highest RDW quartile. There was a strong association of RDW and mortality in unadjusted analysis (OR 1.32; 95%CI 1.27-1.39, p<0.001). RDW was strongly correlated with different pathways including inflammation (coefficient of determination (R2) 0.30; p<0.001), nutrition (R2 0.20; p<0.001) and blood diseases (R2 0.30; p<0.001 The association was eliminated after including different biological pathways into the models with the fully adjusted regression model showing an OR of 1.02 (95%CI 0.93-1.12; p = 0.664) for the association of RDW and mortality. Similar effects were found for other outcomes including intensive care unit admission and hospital readmission. CONCLUSION: Our data suggests that RDW is a strong surrogate marker of mortality in unselected medical inpatients with most of the prognostic information being explained by other disease factors. The strong correlation of RDW and different biological pathways such as chronic inflammation, malnutrition and blood disease suggest that RDW may be viewed as an unspecific and general "chronic disease prognostic marker".