ArticleImmunity, inflammation and disease2024
Development and validation of a nomogram to predict severe influenza.
Article in Immunity, inflammation and disease, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Neutrophil Extracellular Trap-Related Gene Signatures and Molecular Clusters in Severe Influenza: Identification Through Integrative Transcriptome Analysis.Journal of immunology research · 2026Article
- Development and validation of a nomogram to predict severe influenza.Immunity, inflammation and disease · 2024Article
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Authors and funding
4 authors.
Funding
Abstract
backgroundInfluenza is an acute respiratory disease posing significant harm to human health. Early prediction and intervention in patients at risk of developing severe influenza can significantly decrease mortality.
methodA comprehensive analysis of 146 patients with influenza was conducted using the Gene Expression Omnibus (GEO) database. We assessed the relationship between severe influenza and patients' clinical information and molecular characteristics. First, the variables of differentially expressed genes were selected using R software. Least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression analysis were performed to investigate the association between clinical information and molecular characteristics and severe influenza. A nomogram was developed to predict the presence of severe influenza. At the same time, the concordance index (C-index) is adopted area under the receiver operating characteristic (ROC), area under the curve (AUC), decision curve analysis (DCA), and calibration curve to evaluate the predictive ability of the model and its clinical application.
resultsSevere influenza was identified in 47 of 146 patients (32.20%) and was significantly related to age and duration of illness. Multivariate logistic regression demonstrated significant correlations between severe influenza and myloperoxidase (MPO) level, haptoglobin (HP) level, and duration of illness. A nomogram was formulated based on MPO level, HP level, and duration of illness. This model produced a C-index of 0.904 and AUC of 0.904.
conclusionsA nomogram based on the expression levels of MPO, HP, and duration of illness is an efficient model for the early identification of patients with severe influenza. These results will be useful in guiding prevention and treatment for severe influenza disease.
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