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Development and Validation of a Predictive Model for Wheezing Illness Following Human Bocavirus 1 Infection in
Ri De1, Zeng Li1, Kexiang Zhang1
1Laboratory of Virology, Capital Center for Children's Health, Capital Institute of Pediatrics, Capital Medical University, Beijing 100020, China.
Microorganisms
|July 28, 2026
Summary
This study identifies key predictors for wheezing illness in children with Human Bocavirus 1 (HBoV1) infection. The findings enable early risk stratification for timely clinical intervention in pediatric patients.
Area of Science:
- Pediatric Infectious Diseases
- Respiratory Illnesses in Children
- Clinical Predictive Modeling
Background:
- Human Bocavirus 1 (HBoV1) is a significant pathogen linked to pediatric wheezing illnesses.
- Effective clinical indicators for predicting wheezing in HBoV1-infected children are currently lacking.
Purpose of the Study:
- To develop and validate a predictive model for identifying children at high risk of wheezing illness following HBoV1 infection.
- To identify key clinical predictors associated with wheezing in pediatric HBoV1 cases.
Main Methods:
- A retrospective cohort study of 330 pediatric patients with single HBoV1 infection.
- Univariate and Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression for predictor screening.
- Multivariate logistic regression model construction and validation using training (80%) and testing (20%) datasets.
Main Results:
- Abnormal NK cell percentage, preterm birth, and personal history of allergy were identified as independent predictors of wheezing illness.
- The predictive model demonstrated high performance with Area Under the Curve (AUC) values of 0.904 (training) and 0.876 (testing).
- The model accurately stratified patients into high-risk (85.3% wheezing rate) and low-risk (18.7% wheezing rate) groups in the test set.
Conclusions:
- A validated predictive model incorporating NK cell percentage, preterm birth, and allergy history effectively stratifies wheezing illness risk in children with HBoV1 infection.
- This model facilitates early clinical intervention for pediatric patients diagnosed with HBoV1.
- The findings contribute to improved management strategies for HBoV1-associated respiratory symptoms in children.
