Related Risk Factors That Predict Moderate to Severe Asthma Attack in Children: Analysis Based on Logistic Regression and Decision Tree.

Int J Gen Med

Pediatric Respiratory Medicine Department, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, 610000, People's Republic of China.

Published: July 2025


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Article Abstract

Purpose: To analyse the related risk factors of moderate to severe asthma attack in children by logistic regression and decision tree.

Patients And Methods: A retrospective analysis of clinical data of children diagnosed with asthma attacks in our hospital from January 2020 to August 2023 was conducted. The patients were divided into mild group (n=459, 57.02%) and moderate to severe group (n=346, 42.98%). Related risk factors of moderate to severe asthma attack in children were analyzed by univariate logistic regression, and then multivariate logistic regression and decision tree model were obtained.

Results: The results of univariate logistic regression showed that there were significant differences between the two groups in age, medical history, allergy history, family history, C-reactive protein (CRP), neutrophil percentage (NEU%), Mycoplasma pneumoniae (MP) infection, Rhinovirus (RV) infection (all p < 0.05). The results of multivariate logistic regression showed that age (≥6 years) (OR=1.636, 95% CI=1.046-2.559), medical history (OR=1.460, 95% CI=1.063-2.006), allergy history (OR=2.387, 95% CI=1.733-3.288), family history (OR=2.564, 95% CI=1.619-4.058), NEU% (OR=1.020, 95% CI=1.009-1.031), MP infection (OR=2.140, 95% CI=1.571-2.916), RV infection (OR=4.546, 95% CI=2.274-9.089) were related risk factors of moderate to severe asthma attack in children (all p<0.05). The decision tree model showed that MP infection, CRP, allergy history, NEU%, and medical history were risk factors of moderate to severe asthma attacks in children, with importance levels of 0.41, 0.29, 0.134, 0.130, and 0.061, respectively. Multivariate logistic regression (AUC=0.733, 95% CI: 0.698~0.767) and decision tree (AUC=0.694, 95% CI: 0.658~0.731) both exhibited good prediction accuracy.

Conclusion: Allergic history, medical history, MP infection, and increased NEU% were related risk factors that predict moderate to severe asthma attack in children. Multivariate logistic regression and decision tree both had a good predictive effect for analyzing the risk factors of moderate to severe asthma attack in children.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12275991PMC
http://dx.doi.org/10.2147/IJGM.S530736DOI Listing

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