ArticleFrontiers in cellular and infection microbiology2021
Establishment of a Risk Score Model for Early Prediction of Severe H1N1 Influenza.
Article in Frontiers in cellular and infection microbiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 9 citations in OpenAlex.
- Neutrophil Extracellular Trap-Related Gene Signatures and Molecular Clusters in Severe Influenza: Identification Through Integrative Transcriptome Analysis.Journal of immunology research · 2026Article
- Multiomics analysis unveils key biomarkers during dynamic progress of IAV infection in mice.Frontiers in immunology · 2025Article
- Development and validation of a nomogram to predict severe influenza.Immunity, inflammation and disease · 2024Article
- Alterations in CX3CL1 Levels and Its Role in Viral Pathogenesis.International journal of molecular sciences · 2024Review
- Comprehensive immune landscape of lung-resident memory CD8Frontiers in microbiology · 2023Article
- Development of lab score system for predicting COVID-19 patient severity: A retrospective analysis.PloS one · 2022Article
Corrections and comments
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Authors and funding
8 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
H1N1 is the most common subtype of influenza virus circulating worldwide and can cause severe disease in some populations. Early prediction and intervention for patients who develop severe influenza will greatly reduce their mortality. In this study, we conducted a comprehensive analysis of 180 PBMC samples from three published datasets from the GEO DataSets. Differentially expressed gene (DEG) analysis and weighted correlation network analysis (WGCNA) were performed to provide candidate DEGs for model building. Functional enrichment and CIBERSORT analyses were also performed to evaluate the differences in composition and function of PBMCs between patients with severe and mild disease. Finally, a risk score model was built using lasso regression analysis, with six genes (
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