ArticleCritical care (London, England)2019
Nuclear magnetic resonance-based serum metabolomic analysis reveals different disease evolution profiles between septic shock survivors and non-survivors.
Article in Critical care (London, England), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
31 citing papers in PubMed, 1 synthesis or guideline pooled it, 47 citations in OpenAlex.
- Prediction of sepsis mortality using metabolite biomarkers in the blood: a meta-analysis of death-related pathways and prospective validation.BMC medicine · 2020Pooled it
- Metabolic footprint of sepsis and septic shock: A narrative review.World journal of critical care medicine · 2026Review
- Genetic and Multi-Omics Insights Into Monocyte Pantothenate-Mediated Protection in Acute Respiratory Distress Syndrome.Journal of cellular and molecular medicine · 2025Article
- Multi-Omics and -Organ Insights into Energy Metabolic Adaptations in Early Sepsis Onset.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Impact of Venous CONgestion on Organ Function and Outcomes in Sepsis (ICON-Sepsis): a prospective observational cohort study protocol.BMJ open · 2025Article
- Advances in metabolomics in critically ill patients with sepsis and septic shock.Clinical and experimental emergency medicine · 2025Article
- Sepsis subphenotypes: bridging the gaps in sepsis treatment strategies.Frontiers in immunology · 2025Review
- Nonlinear Association Between Calculated Globulin Levels and 28-Day Mortality in Patients with Sepsis: A Retrospective Cohort Study.Risk management and healthcare policy · 2025Article
- Article
- Sepsis, Management & Advances in Metabolomics.Nanotheranostics · 2024Review
- Article
- Small molecule metabolites: discovery of biomarkers and therapeutic targets.Signal transduction and targeted therapy · 2023Review
- Longitudinal NMR Based Serum Metabolomics to Track the Potential Serum Biomarkers of Septic Shock.Nanotheranostics · 2023Article
- Review
- Machine learning approaches to the human metabolome in sepsis identify metabolic links with survival.Intensive care medicine experimental · 2022Article
- Patient Stratification in Sepsis: Using Metabolomics to Detect Clinical Phenotypes, Sub-Phenotypes and Therapeutic Response.Metabolites · 2022Review
- Serum Levels of Acylcarnitines and Amino Acids Are Associated with Liberation from Organ Support in Patients with Septic Shock.Journal of clinical medicine · 2022Article
- Identifying potential biomarkers and therapeutic targets for dogs with sepsis using metabolomics and lipidomics analyses.PloS one · 2022Observational
- Observational
- Metabonomic Analysis of Metabolites Produced byInfection and drug resistance · 2022Article
Corrections and comments
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Authors and funding
8 authors at 4 institutions in 2 countries.
Funding
Abstract
backgroundSeptic shock is the most severe phase of sepsis and is associated with high rates of mortality. However, early stage prediction of septic shock outcomes remains difficult. Metabolomic techniques have emerged as a promising tool for improving prognosis.
methodsOrthogonal projections to latent structures-discriminant analysis (OPLS-DA) models separating the serum metabolomes of survivors from those of non-survivors were established with samples obtained at the intensive care unit (ICU) admission (H0) and 24 h later (H24). For 51 patients with available H0 and H24 samples, multi-level modeling was performed to provide insight into different metabolic evolutions that occurred between H0 and H24 in the surviving and non-surviving patients. Relative quantification and receiver operational characteristic curves (ROC) were applied to estimate the predictability of key discriminatory metabolites for septic shock mortality.
resultsMetabolites that were involved in energy supply and protein breakdown were primarily responsible for differentiating survivors from non-survivors. This was not only seen in the H0 and H24 discriminatory models, but also in the H0-H24 paired models. Reanalysis of extra H0-H24 paired samples in the established multi-level model demonstrated good performance of the model for the classification of samplings. According to the ROC results, nine discriminatory metabolites defined consistently from the unpaired model and the H0-H24 time-trend change (Δ
conclusionsDysregulation of the metabolites identified by this study is associated with poor outcomes for septic shock. Evaluation of these compounds during the first 24 h after ICU admission in the septic shock patient may be helpful for estimating the severity of cases and for predicting outcomes.
trial registrationAll human serum samples were collected and stored, provided by the "center of biologic resources for liver disease", in Jean Verdier Hospital, Bondy, France (BB-0033-00027).
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