Mortality prediction in patients with severe septic shock: a pilot study using a target metabolomics approach

Ferrario, Manuela; Cambiaghi, Alice; Brunelli, Laura; Giordano, Silvia; Caironi, Pietro; Guatteri, Luca; Raimondi, Ferdinando; Gattinoni, Luciano; Latini, Roberto; Masson, Serge; Ristagno, Giuseppe; Pastorelli, Roberta

doi:10.1038/srep20391

Cited by 132 publications

(153 citation statements)

References 40 publications

(62 reference statements)

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“…This study integrated metabolic profiles of septic shock patients with the clinical manifestations of septic shock to detect early biomarkers of the condition. The discoveries made in this study support the idea that lipid homeostasis may play a role in septic shock mortality 76 .…”

Section: Metabolomicssupporting

confidence: 79%

Mass spectrometry for the discovery of biomarkers of sepsis

Ludwig

Hummon

2017

Mol. BioSyst.

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Sepsis is a serious medical condition that occurs in 30% of patients in intensive care units (ICUs). Early detection of sepsis is key to prevent its progression to severe sepsis and septic shock, which can cause organ failure and death. Diagnostic criteria for sepsis are nonspecific and hinder a timely diagnosis in patients. Therefore, there is currently a large effort to detect biomarkers that can aid physicians in the diagnosis and prognosis of sepsis. Mass spectrometry is often the method of choice to detect metabolomic and proteomic changes that occur during sepsis progression. These “omics” strategies allow for untargeted profiling of thousands of metabolites and proteins from human biological samples obtained from septic patients. Differential expression of or modifications to these metabolites and proteins can provide a more reliable source of diagnostic biomarkers for sepsis. Here, we focus on the current knowledge of biomarkers of sepsis and discuss the various mass spectrometric technologies used in their detection. We consider studies of the metabolome and proteome and summarize information regarding potential biomarkers in both general and neonatal sepsis.

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Section: Metabolomicssupporting

confidence: 79%

Mass spectrometry for the discovery of biomarkers of sepsis

Ludwig

Hummon

2017

Mol. BioSyst.

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“…Our analyses demonstrate that in late preterm and term infants, acyl-carnitines, enzyme markers, and amino acids are the newborn screening analytes most strongly associated with neonatal sepsis. Associations between acyl-carnitines and sepsis have been previously documented, with heightened analyte levels occurring among septic infants 35,36 and positive correlations being reported between certain acyl-carnitine levels and 28-day mortality 37 . High acyl-carnitine levels have also been reported in other cases of injury 35 and catabolic stress, which is likely the mechanism of their association with neonatal sepsis 38–40 .…”

Section: Discussionmentioning

confidence: 87%

Using newborn screening analytes to identify cases of neonatal sepsis

Fell

Hawken

Wong

et al. 2017

Sci Rep

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Neonatal sepsis is associated with high mortality and morbidity, yet challenges with available diagnostic approaches can lead to delays in therapy. Our study assessed whether newborn screening analytes could be utilized to identify associations with neonatal sepsis. We linked a newborn screening registry with health databases to identify cases of sepsis among infants born in Ontario from 2010–2015. Correlations between sepsis and screening analytes were examined within three gestational age groups (early preterm: <34 weeks; late preterm: 34–36 weeks; term: ≥37 weeks), using multivariable logistic regression models. We started with a model containing only clinical factors, then added groups of screening analytes. Among 793,128 infants, 4,794 were diagnosed with sepsis during the neonatal period. Clinical variables alone or in combination with hemoglobin values were not strongly predictive of neonatal sepsis among infants born at term or late preterm. However, model fit improved considerably after adding markers of thyroid and adrenal function, acyl-carnitines, and amino acids. Among infants born at early preterm gestation, neither clinical variables alone nor models incorporating screening analytes adequately predicted neonatal sepsis. The combination of clinical variables and newborn screening analytes may have utility in identifying term or late preterm infants at risk for neonatal sepsis.

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“…Using predictive modeling approaches, the metabolites could predict sepsis patient outcomes in the ED and ICU better than lactate, SOFA and APACHEII [76, 36, 37]. Many of these metabolites have been independently identified in a number of recent clinical ICU studies pointing to a common mechanism of metabolic dysfunction [77, 40, 78, 79]. …”

Section: Metabolomic Changes In Sepsis Suggest An Energy Crisis In Nomentioning

confidence: 99%

Early Diagnosis of Sepsis: Is an Integrated Omics Approach the Way Forward?

Wong

2017

Mol Diagn Ther

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Sepsis remains one of the leading causes of death in the United States and it is expected to get worse as the population ages. Moreover, the standard of care, which recommends aggressive treatment with appropriate antibiotics, has led to an increase in multiple drug resistant organisms (MDROs). There is a dire need for the development of new antibiotics, improved antibiotic stewardship and therapies that treat the host response. Development of new sepsis therapeutics has been a disappointment as no drugs are currently approved to treat the various complications from sepsis. Much of the failure has been blamed on animal models that do not accurately reflect the course of the disease. However, recent improvements in metabolomic, transcriptomic, genomic and proteomic platforms have allowed for a broad spectrum look at molecular changes in the host response using clinical samples. Integration of these multi-omic data sets allows researchers to perform systems biology approaches to identify novel pathophysiology of the disease. In this review, we will highlight what is currently known about sepsis and how integrative omics has identified new diagnostic and predictive models of sepsis as well as novel mechanisms. These changes may improve patient care as well as guide future preclinical analysis of sepsis.

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Mortality prediction in patients with severe septic shock: a pilot study using a target metabolomics approach

Cited by 132 publications

References 40 publications

Mass spectrometry for the discovery of biomarkers of sepsis

Mass spectrometry for the discovery of biomarkers of sepsis

Using newborn screening analytes to identify cases of neonatal sepsis

Early Diagnosis of Sepsis: Is an Integrated Omics Approach the Way Forward?

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