ArticleEBioMedicine2022
Predicting sepsis severity at first clinical presentation: The role of endotypes and mechanistic signatures.
Article in EBioMedicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 126 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
126 citing papers in PubMed, 2 syntheses or guidelines pooled it, 206 citations in OpenAlex.
- A multi-omics approach uncovers causality of IL6R on endotypes of subclinical carotid atherosclerosis and the possible role of the IL6R/OSMR pathway.Cardiovascular research · 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
- Super learner model for predicting carotid plaque regression in type 2 diabetes on PCSK9 inhibitors.Acta diabetologica · 2026Article
- Plasma mitochondrial-associated proteins scale with illness severity and predict outcome in suspected sepsis.Critical care (London, England) · 2026Article
- A whole-blood cryopreservation method streamlines clinical sample collection for multimodal single-cell immune profiling in sepsis.JCI insight · 2026Article
- Targeting the NR1D1-IGF2BP2-V-ATPase Axis With Hybrid Nanovesicles Restores Macrophage Rhythms to Reverse Sepsis-Induced Immunosuppression.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Multiomics Profiling Identifies Blood-Based Diagnostic Markers for Sepsis.Journal of cellular physiology · 2026Article
- Inflammation-driven mitochondrial dysfunction and ROS accumulation orchestrate pulmonary fibrotic remodeling in sepsis.Redox biology · 2026Article
- Community-Acquired Pneumonia: Disease Course Prediction With a 5-Gene Signature.CHEST pulmonary · 2026Article
- Inter-Organ Communication Networks in Systemic Physiology: Glucocorticoid Receptor α as a Central Integrator of Homeostasis.International journal of molecular sciences · 2026Review
- Longitudinal blood transcriptome profiling reveals immune dynamics in sepsis.BMC infectious diseases · 2026Article
- Article
- Pathway-level profiling of the sepsis proteome reveals immune and transcriptional dysregulation.Molecular medicine (Cambridge, Mass.) · 2026Article
- Dynamic inflammatory trajectories and 28-day mortality in patients in the intensive care unit: An exploratory observational study.Journal of intensive medicine · 2026Article
- Mechanism of Gzma-mediated GEF-H1 activation in intestinal epithelial cells leading to intestinal barrier dysfunction in sepsis.Clinical and translational medicine · 2026Article
- Article
- The relationship between urinary tract infections and sepsis: results from Mendelian randomization and MIMIC data study.World journal of urology · 2026Article
- A Deep Representation Learning Method for Quantitative Immune Defense Function Evaluation and Its Clinical Applications.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- An 11-gene blood transcriptomic signature reflects a sepsis-associated host-response pattern across public cohorts.Frontiers in medicine · 2026Article
- Article
66 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 8 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundInter-individual variability during sepsis limits appropriate triage of patients. Identifying, at first clinical presentation, gene expression signatures that predict subsequent severity will allow clinicians to identify the most at-risk groups of patients and enable appropriate antibiotic use.
methodsBlood RNA-Seq and clinical data were collected from 348 patients in four emergency rooms (ER) and one intensive-care-unit (ICU), and 44 healthy controls. Gene expression profiles were analyzed using machine learning and data mining to identify clinically relevant gene signatures reflecting disease severity, organ dysfunction, mortality, and specific endotypes/mechanisms.
findingsGene expression signatures were obtained that predicted severity/organ dysfunction and mortality in both ER and ICU patients with accuracy/AUC of 77-80%. Network analysis revealed these signatures formed a coherent biological program, with specific but overlapping mechanisms/pathways. Given the heterogeneity of sepsis, we asked if patients could be assorted into discrete groups with distinct mechanisms (endotypes) and varying severity. Patients with early sepsis could be stratified into five distinct and novel mechanistic endotypes, named Neutrophilic-Suppressive/NPS, Inflammatory/INF, Innate-Host-Defense/IHD, Interferon/IFN, and Adaptive/ADA, each based on ∼200 unique gene expression differences, and distinct pathways/mechanisms (e.g., IL6/STAT3 in NPS). Endotypes had varying overall severity with two severe (NPS/INF) and one relatively benign (ADA) groupings, consistent with reanalysis of previous endotype studies. A 40 gene-classification tool (accuracy=96%) and several gene-pairs (accuracy=89-97%) accurately predicted endotype status in both ER and ICU validation cohorts.
interpretationThe severity and endotype signatures indicate that distinct immune signatures precede the onset of severe sepsis and lethality, providing a method to triage early sepsis patients.
Indexed as
Identifiers
What OpenQuestion holds
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.