Tianjin Medical Journal ›› 2026, Vol. 54 ›› Issue (4): 369-373.doi: 10.11958/20251913

• Clinical Research • Previous Articles     Next Articles

The construction of a prediction model for severe pneumonia caused by mycoplasma pneumoniae mixed with adenovirus infection in children based on BP neural network

YAO Guohua1(), LIU Jie1, ZHANG Wen1, MA Cuian1(), WEI Botao1, GAO Na2   

  1. 1 Department of Infectious Diseases, Tianjin Children’s Hospital, Tianjin University, Tianjin 300134, China
    2 School of Automation and Electrical Engineering, Tianjin University of Technology and Education
  • Received:2025-05-09 Revised:2025-11-21 Published:2026-04-15 Online:2026-04-14
  • Contact: E-mail:macuian@126.com

Abstract:

Objective To construct a clinical prediction model for severe pneumonia caused by mycoplasma pneumoniae (MP) and adenovirus (ADV) in children based on the backpropagation method (BP) neural network. Methods A retrospective analysis was conducted on the clinical, laboratory and imaging data of 138 children with severe pneumonia caused by MP mixed with ADV infection. The research subjects were randomly divided into the training set and the test set (7:3), and a BP neural network prediction model was constructed. The contribution of clinical features in the training set was quantified by shapley additive explanations (SHAP). The predictors of severe pneumonia for MP mixed with ADV were screened out. It is verified through the accuracy rate, loss value and confusion matrix in the test set. Results In the severe group, the duration of fever, the highest body temperature, neutrophil percentage (N%), aspartate transaminase (AST), lactate dehydrogenase (LDH), interleukin-6 (IL-6), extensive inflammatory consolidation and length of hospital stay were higher than those in the non-severe group, while lymphocyte percentage (L%) and albumin levels were lower than those in the non-severe group(P<0.05). Further research results through BP neural network showed that the duration of fever, AST, N%, maximum body temperature, large areas of inflammatory consolidation, IL-6, L% and LDH were the key predictors of severe pneumonia caused by MP and ADV infection. In constructing the clinical prediction model of severe MP mixed with ADV in children, the test set showed an accuracy rate of 90.48% and a loss value of 0.233 2. Conclusion The prediction model for severe pneumonia caused by mixed MP-ADV infections is successfully constructed in children using a BP neural network. The eight key predictors are identified from the model that can serve as a reference for early clinical identification of severe cases.

Key words: pneumonia, mycoplasma, adenoviruses, human, coinfection, models, statistical, child, BP neural network, shapley additive explanations

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