ArticleJournal of critical care2018
Six subphenotypes in septic shock: Latent class analysis of the PROWESS Shock study.
Article in Journal of critical care, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05311046 (Biomarker-enhanced Artificial Intelligence Based Pediatric Sepsis Screening Tool Towards Early Recognition and Personalized Therapeutics), which is not on this map. Cited by 47 papers.
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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.
Biomarker-enhanced Artificial Intelligence Based Pediatric Sepsis Screening Tool Towards Early Recognition and Personalized Therapeutics
Who cites it
47 citing papers in PubMed.
- Identification of a hyperinflammatory sepsis phenotype using protein biomarker and clinical data in the ProCESS randomized trial.Scientific reports · 2024Trial
- Early Restrictive or Liberal Fluid Management for Sepsis-Induced Hypotension.The New England journal of medicine · 2023Trial
- Development and validation of novel sepsis subphenotypes using trajectories of vital signs.Intensive care medicine · 2022Trial
- A neutrophil subset defined by intracellular olfactomedin 4 is associated with mortality in sepsis.American journal of physiology. Lung cellular and molecular physiology · 2021Trial
- Perfectionism Profiles Among Hospital Nurses: A Cross-Sectional Validation Study of a Multidimensional Scale.International nursing review · 2026Article
- Noradrenaline-trajectory phenotypes in septic shock: derivation and external validation in two independent cohorts.Intensive care medicine experimental · 2026Article
- Landmark-based early perfusion phenotyping for prognostic stratification in septic shock: derivation in MIMIC-IV and fixed-parameter external transportability assessment in eICU.Frontiers in medicine · 2026Article
- Dynamic biomarker profiling and phenotyping in burn sepsis: a retrospective cohort study using growth mixture modeling.Frontiers in cellular and infection microbiology · 2026Article
- The immunology of sepsis: translating new insights into clinical practice.Nature reviews. Nephrology · 2026Review
- Subphenotyping sepsis based on organ interaction trajectory using a deep temporal graph clustering model: a retrospective cohort study.EClinicalMedicine · 2025Article
- Syndromic Analysis of Sepsis Cohorts Using Large Language Models.JAMA network open · 2025Article
- Plasma proteomics identifies molecular subtypes in sepsis.Critical care (London, England) · 2025Article
- Pediatric Sepsis Phenotype in a Single-Center Cohort Covering 2010-2020: Evolution in Day 1-Day 3 Trajectory and Potential Prognostic Value.Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies · 2025Article
- Using machine learning techniques for early prediction of tracheal intubation in patients with septic shock: a multi-center study in South Korea.Acute and critical care · 2025Article
- Sepsis subphenotypes, theragnostics and personalized sepsis care.Intensive care medicine · 2025Review
- Unsupervised clustering for sepsis identification in large-scale patient data: a model development and validation study.Intensive care medicine experimental · 2025Article
- Septic Cardiomyopathy: Difficult Definition, Challenging Diagnosis, Unclear Treatment.Journal of clinical medicine · 2025Review
- Biological subphenotypes in patients hospitalized with suspected infection in Thailand: a secondary analysis of a prospective observational study.The Lancet regional health. Southeast Asia · 2025Article
- Aiming for precision: personalized medicine through sepsis subtyping.Burns & trauma · 2025Review
- The Precision Resuscitation With Crystalloids in Sepsis (PRECISE) Trial: A Trial Protocol.JAMA network open · 2024Article
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6 authors.
Funding
Abstract
purposeSeptic shock is a highly heterogeneous condition which is part of the challenge in its diagnosis and treatment. In this study we aim to identify clinically relevant subphenotypes of septic shock using a novel statistic al approach.
methodsBaseline patient data from a large global clinical trial of septic shock (n = 1696) was analysed using latent class analysis (LCA). This approach allowed investigators to identify subgroups in a heterogeneous population by estimating a categorical latent variable that detects relatively homogeneous subgroups within a complex phenomenon.
resultsLCA identified six different, clinically meaningful subphenotypes of septic shock each with a typical profile: (1) "Uncomplicated Septic Shock, (2) "Pneumonia with adult respiratory distress syndrome (ARDS)", (3) "Postoperative Abdominal", (4) "Severe Septic Shock", (5): "Pneumonia with ARDS and multiple organ dysfunction syndrome (MODS)", (6) "Late Septic Shock". The 6-class solution showed high entropy approaching 1 (i.e., 0.92), indicating there was excellent separation between estimated classes.
conclusionsLCA appears to be an applicable statistical tool in analysing a heterogenous clinical cohort of septic shock. The results may lead to a better understanding of septic shock complexity and form a basis for considering targeted therapies and selecting patients for future clinical trials.
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