ArticleFrontiers in immunology2022
Integrated Analysis of Gene Co-Expression Network and Prediction Model Indicates Immune-Related Roles of the Identified Biomarkers in Sepsis and Sepsis-Induced Acute Respiratory Distress Syndrome.
Article in Frontiers in immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.
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Who cites it
15 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.
- Application of machine learning for the diagnosis and prognosis of sepsis-induced acute respiratory distress syndrome: a systematic review and meta-analysis.BMC medical informatics and decision making · 2026Pooled it
- Exploring the mechanism of polymorphonuclear neutrophils against sepsis based on immune model.Annals of medicine · 2026Review
- Host gene expression analysis in the detection of bacterial and viral etiology in children hospitalized with a suspected severe infection.Communications medicine · 2026Article
- Development of Machine Learning-Based Models to Predict Mortality in Intensive Care Unit Patients with Sepsis.Journal of inflammation research · 2026Article
- Predicting mortality and risk factors of sepsis related ARDS using machine learning models.Scientific reports · 2025Article
- Identification of CD19Journal of inflammation research · 2025Article
- Identification of Potential Therapeutic Targets for Sepsis Using Mendelian Randomization and Integrated eQTL/pQTL Analysis.International journal of general medicine · 2025Article
- Identification of Biomarkers for Sepsis-Induced Acute Lung Injury Through Bioinformatics and Machine Learning Approaches, with Experimental Validation.Journal of inflammation research · 2025Article
- Comprehensive analysis of sialylation-related genes and construct the prognostic model in sepsis.Scientific reports · 2024Article
- Article
- Role of Cellular Senescence Genes and Immune Infiltration in Sepsis and Sepsis-Induced ARDS Based on Bioinformatics Analysis.Journal of inflammation research · 2024Article
- Association and predictive value of soluble thrombomodulin with mortality in patients with acute respiratory distress syndrome: systematic review and meta-analysis.Annals of translational medicine · 2023Article
- Classification of subtypes and identification of dysregulated genes in sepsis.Frontiers in cellular and infection microbiology · 2023Article
- Single-Cell RNA Sequencing and Transcriptome Analysis Revealed the Immune Microenvironment and Gene Markers of Acute Respiratory Distress Syndrome.Journal of inflammation research · 2023Article
- Combination of transcriptional biomarkers and clinical parameters for early prediction of sepsis indued acute respiratory distress syndrome.Frontiers in immunology · 2022Article
Corrections and comments
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Authors and funding
9 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Sepsis is a series of clinical syndromes caused by immunological response to severe infection. As the most important and common complication of sepsis, acute respiratory distress syndrome (ARDS) is associated with poor outcomes and high medical expenses. However, well-described studies of analysis-based researches, especially related bioinformatics analysis on revealing specific targets and underlying molecular mechanisms of sepsis and sepsis-induced ARDS (sepsis/se-ARDS), still remain limited and delayed despite the era of data-driven medicine. In this report, weight gene co-expression network based on data from a public database was constructed to identify the key modules and screen the hub genes. Functional annotation by enrichment analysis of the modular genes also demonstrated the key biological processes and signaling pathway; among which, extensive immune-involved enrichment was remarkably associated with sepsis/se-ARDS. Based on the differential expression analysis, least absolute shrink and selection operator, and multivariable logistic regression analysis of the screened hub genes,
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