Analysis of risk factors for severe disease in elderly influenza patients based on immunophenotypic characteristics

LIU Xiaofeng; LU Yihan; ZHU Geqin

doi:10.3969/j.issn.1007-8134.2025.06.011

Abstract：Objective To explore the changes in immunophenotypic indicators during the severe process of elderly influenza patients,to identify relevant independent risk factors,and to construct predictive models to assess their discriminative efficacy.Methods This study retrospectively enrolled120 elderly hospitalized patients diagnosed with influenza at Jiangsu Provincial Hospital of Traditional Chinese Medicine from January 2019 to December 2023.Demographic information,underlying diseases,clinical characteristics,laboratory indicators,and immune phenotype detection data within 24 hours of admission were collected.Univariate and multivariate logistic regression analyses were used to identify independent factors influencing severity.Receiver operating characteristic curves,calibration curves,and decision curves were plotted to evaluate model performance.Results The multiple factor analysis showed that the number of underlying diseases,the proportion of CD4+T cells,the ratio of CD4/CD8,the proportion of natural killer cells and the level of interleukin-6 were independent influencing factors for the severe disease in elderly influenza patients(P<0.05).The multivariate logistic regression model constructed based on these factors showed good discrimination,with an area under the curve of 0.872,sensitivity of 81.3%,and specificity of 78.5%.Conclusion Multiple immunophenotypic features and inflammatory factors have important early warning value in the process of severe influenza in the elderly.The constructed prediction model has high performance and can provide decision support for early identification and intervention of high-risk groups of influenza in the elderly.