ArticleIntensive care medicine2025
Metabolic septic shock sub-phenotypes, stability over time and association with clinical outcome.
Article in Intensive care medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Pathophysiology of distributive shock in sepsis: beyond vasoplegia.Intensive care medicine · 2026Article
- Update on sepsis treatment.Journal of intensive care · 2026Review
- Unsupervised Clinical Phenotyping Identifies Distinct Risk Profiles in Incisional Hernia Repair.Medicina (Kaunas, Lithuania) · 2026Article
- Review
- Identification of a robust metabolic signature associated with hospital-acquired pneumonia and response to interferon-gamma treatment in critically ill patients.Critical care (London, England) · 2026Observational
- Update on sepsis and septic shock: from bundles to precision medicine.Intensive care medicine · 2026Article
- AI-Based Prediction of Gene Expression in Single-Cell and Multiscale Genomics and Transcriptomics.International journal of molecular sciences · 2026Review
- Artificial Intelligence- and Machine Learning-Assisted Subphenotyping for Personalized Immunotherapy in Sepsis.Journal of personalized medicine · 2026Review
- Data-driven spatial-temporal framework for exploring the heterogeneity and temporality of sepsis.Chinese medical journal · 2026Review
- Beyond antimicrobials: a host-directed precision pharmacotherapy framework for septic shock.Frontiers in medicine · 2026Article
- Evidence of immune-metabolic imbalance prior to sepsis: a prospective study in the UK Biobank.Frontiers in nutrition · 2026Article
- Linking Metabolic and Mitochondrial Stress to Regulated Cell Death and Inflammatory Organ Injury in Sepsis.Journal of inflammation research · 2026Review
- Early biomarkers for predicting sepsis-induced shock: insights from inflammatory pathways and immune response.Frontiers in pharmacology · 2026Review
- Clinical subphenotypes and molecular endotypes in sepsis: toward an integrated and dynamic framework.Annals of intensive care · 2026Review
- Derivation and external validation of community-acquired pneumonia subphenotypes in Southeast Asia: a secondary analysis of prospective cohort studies.EClinicalMedicine · 2025Article
- Metabolomics for the Diagnosis of Secondary Infections in Critically Ill Patients With COVID-19.Critical care explorations · 2025Article
- The 15th Anniversary ofLife (Basel, Switzerland) · 2025Review
- Metabolomic stratification of shock: pathophysiological insights for personalized critical care.Annals of intensive care · 2025Article
Corrections and comments
- Erratum issued
Authors and funding
6 authors.
Funding
Abstract
purposeMachine learning has shown promise to detect useful subgroups of patients with sepsis from gene expression and protein data. This approach has rarely been deployed in metabolomic datasets. Metabolomic data are of interest as they capture effects from the genome, proteome, and environmental. We aimed to discover metabolic sub-phenotypes of septic shock, examine their temporal stability and association with clinical outcome.
methodsAnalysis was performed in two double-blind randomized trials in septic shock (LeoPARDS (1402 samples from 470 patients) and VANISH (493 samples from 173 patients)). Patients were included soon after the onset of shock and had serum collected at up to four time points. Metabolic clusters were identified from 474 metabolites using k-means clustering in LeoPARDS and predicted in VANISH with an elastic net classifier.
resultsThree sub-phenotypes were found. The main determinants of cluster membership were lipid species, especially lysophospholipids. Low lysophospholipid sub-phenotypes were associated with higher circulating cytokine levels. Persistence of low lysophospholipid sub-phenotypes was associated with higher mortality compared to the high lysophospholipid sub-phenotype (LeoPARDS: cluster 2 odds ratio 3.66 (95% CI 1.88-7.20), p = 0.0001, cluster 3 2.49 (1.29-4.81), p = 0.006; VANISH: cluster 2 4.13 (1.17-15.61), p = 0.03), cluster 3 3.22 (1.09-9.92), p = 0.04, vs cluster 1). We found no heterogeneity of treatment effect for any of the trial interventions by baseline metabolic sub-phenotype.
conclusionThree metabolic subgroups exist in septic shock which evolve over time. Persistence of low lysophospholipid sub-phenotypes is associated with mortality. Monitoring these subgroups could help identify patients at risk of poor outcome and direct novel therapies such as lysophospholipid supplementation. REGISTRATION: Clinicaltirals.gov Identifiers, VANISH: ISRCTN 20769191, LeoPARDS: ISRCTN12776039.
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