Cytokine-based nomogram for discriminating viral pneumonia from Mycoplasma pneumoniae pneumonia in children
Year: 2024
Type: article
Study design: Observational Study
Abstract: • A user-friendly predictive model was established. • This model discriminated viral from MP infection in children with pneumonia. • It incorporated age, interleukin-8, procalcitonin, and tumor necrosis factor-α/IL-10. For children with pneumonia, differential diagnosis between viral infection and Mycoplasma pneumoniae (MP) infection is difficult. We retrospectively enrolled 336 hospitalized children who were diagnosed with community-acquired pneumonia and whose infection was exclusively viral or MP. We analyzed hematological indicators, biochemical markers, and cytokines. Least absolute shrinkage and selection operator (LASSO) regression analysis and logistic regression analysis were performed to identify and validate the factors that predicted the pathogenic diagnosis. The final predictive model incorporated four factors: tumor necrosis factor-α/interleukin (IL)-10, age, IL-8 and procalcitonin. This predictive model was visualized with a nomogram and had good performance. Using logistic regression analysis, the C-index of this predictive model was 0.878. Using receiver operating characteristic plot, the area under the curve was 0.8785. We established a model with a nomogram to discriminate viral infection from MP infection in hospitalized children with community-acquired pneumonia.
Authors: Xiaoliang Lin, Enhui Xu, Tan Zhang, Qiguo Zhu, Yan Liu, Qiao Tian
Language: English
Subfield: Epidemiology
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $3,190
OpenAlex ID: W4404412399