Observational studyPLoS medicine2015
A Molecular Host Response Assay to Discriminate Between Sepsis and Infection-Negative Systemic Inflammation in Critically Ill Patients: Discovery and Validation in Independent Cohorts.
Observational study in PLoS medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 3 registered trials, which are not on this map. Cited by 112 papers, 5 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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.
Molecular Diagnosis and Risk Stratification of Sepsis
Genotypes and Phenotypes in Pediatric SIRS and Sepsis (GAPPSS)
Clinical Study to Improve the Quality of Care in Critically Ill Patients With Suspected Sepsis Through Early Molecular Diagnosis .
Who cites it
112 citing papers in PubMed, 5 syntheses or guidelines pooled it, 217 citations in OpenAlex.
- The Diagnostic Utility of Host RNA Biosignatures in Adult Patients With Sepsis: A Systematic Review and Meta-Analysis.Critical care explorations · 2025Pooled it
- Upregulation of CRISP3 and its clinical values in adult sepsis: a comprehensive analysis based on microarrays and a two-retrospective-cohort study.Frontiers in immunology · 2024Pooled it
- Screening of core genes prognostic for sepsis and construction of a ceRNA regulatory network.BMC medical genomics · 2023Pooled it
- Emerging strategies for the noninvasive diagnosis of nosocomial pneumonia.Expert review of anti-infective therapy · 2019Pooled it
- The immunosuppressive face of sepsis early on intensive care unit-A large-scale microarray meta-analysis.PloS one · 2018Pooled it
- Clinical evaluation of the SeptiScore biomarker for the diagnosis of healthcare-associated infections in critically ill trauma patients: a multicenter derivation and validation cohort study.BMC anesthesiology · 2026Observational
- Integrating host mRNA signatures and clinical trajectories with machine learning for risk stratification and survival prediction in sepsis: an ICU-based prospective cohort study.BMC infectious diseases · 2026Article
- Diagnostic accuracy of SeptiCyte® RAPID to discriminate sepsis from non-infectious critical illness in patients meeting sepsis criteria according to sepsis-3 definition at ICU admission.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2026Observational
- Lysosome-related biomarkers in peripheral blood immune cells discriminate sepsis from SIRS.Scientific reports · 2026Article
- Likelihood of Blood Culture Positivity Using SeptiCyte RAPID.Journal of clinical medicine · 2026Article
- Blood Host-Response mRNA Assays in Adult Acute Care: Diagnostic Performance, Translational Evidence, and the Clinical Implementation Gap.Infection and drug resistance · 2026Review
- Early biomarkers for predicting sepsis-induced shock: insights from inflammatory pathways and immune response.Frontiers in pharmacology · 2026Review
- Genomic and integrative based progression biomarker discovery in adult sepsis: toward clinical stratification and precision medicine.Annals of intensive care · 2026Review
- Article
- Blood transcriptomic for the diagnosis of nosocomial infections in critically ill patients: an observational proof-of-concept study.Infection · 2025Observational
- SeptAsTERS- SeptiCyte® RAPID as assessment tool for early recognition of sepsis - a prospective observational study.Infection · 2025Observational
- A machine learning and centrifugal microfluidics platform for bedside prediction of sepsis.Nature communications · 2025Article
- Multi-omics machine learning identifies diagnostic gene signatures and functionally supports PRKACB involvement in macrophage inflammatory responses in sepsis.Frontiers in immunology · 2025Article
- Novel Identification of CD74 as a Biomarker for Diagnosing and Prognosing Sepsis Patients.Journal of inflammation research · 2025Article
- Reassessing sepsis research: new clues for old players and new players for an old symptom to improve patient outcomes.EXCLI journal · 2025Review
52 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
19 authors at 5 institutions in 2 countries.
Funding
Abstract
backgroundSystemic inflammation is a whole body reaction having an infection-positive (i.e., sepsis) or infection-negative origin. It is important to distinguish between these two etiologies early and accurately because this has significant therapeutic implications for critically ill patients. We hypothesized that a molecular classifier based on peripheral blood RNAs could be discovered that would (1) determine which patients with systemic inflammation had sepsis, (2) be robust across independent patient cohorts, (3) be insensitive to disease severity, and (4) provide diagnostic utility. The goal of this study was to identify and validate such a molecular classifier. METHODS AND
findingsWe conducted an observational, non-interventional study of adult patients recruited from tertiary intensive care units (ICUs). Biomarker discovery utilized an Australian cohort (n = 105) consisting of 74 cases (sepsis patients) and 31 controls (post-surgical patients with infection-negative systemic inflammation) recruited at five tertiary care settings in Brisbane, Australia, from June 3, 2008, to December 22, 2011. A four-gene classifier combining CEACAM4, LAMP1, PLA2G7, and PLAC8 RNA biomarkers was identified. This classifier, designated SeptiCyte Lab, was validated using reverse transcription quantitative PCR and receiver operating characteristic (ROC) curve analysis in five cohorts (n = 345) from the Netherlands. Patients for validation were selected from the Molecular Diagnosis and Risk Stratification of Sepsis study (ClinicalTrials.gov, NCT01905033), which recruited ICU patients from the Academic Medical Center in Amsterdam and the University Medical Center Utrecht. Patients recruited from November 30, 2012, to August 5, 2013, were eligible for inclusion in the present study. Validation cohort 1 (n = 59) consisted entirely of unambiguous cases and controls; SeptiCyte Lab gave an area under curve (AUC) of 0.95 (95% CI 0.91-1.00) in this cohort. ROC curve analysis of an independent, more heterogeneous group of patients (validation cohorts 2-5; 249 patients after excluding 37 patients with an infection likelihood of "possible") gave an AUC of 0.89 (95% CI 0.85-0.93). Disease severity, as measured by Sequential Organ Failure Assessment (SOFA) score or Acute Physiology and Chronic Health Evaluation (APACHE) IV score, was not a significant confounding variable. The diagnostic utility of SeptiCyte Lab was evaluated by comparison to various clinical and laboratory parameters available to a clinician within 24 h of ICU admission. SeptiCyte Lab was significantly better at differentiating cases from controls than all tested parameters, both singly and in various logistic combinations, and more than halved the diagnostic error rate compared to procalcitonin in all tested cohorts and cohort combinations. Limitations of this study relate to (1) cohort compositions that do not perfectly reflect the composition of the intended use population, (2) potential biases that could be introduced as a result of the current lack of a gold standard for diagnosing sepsis, and (3) lack of a complete, unbiased comparison to C-reactive protein.
conclusionsSeptiCyte Lab is a rapid molecular assay that may be clinically useful in managing ICU patients with systemic inflammation. Further study in population-based cohorts is needed to validate this assay for clinical use.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.