Early risk identification for recurrent wheezing in children with respiratory syncytial virus infections

Ying Wang1, Yalin Shi2, Lijuan Wang2

  • 1Department of Pediatric Cardiovascular and Respiratory Medicine, Xianyang Rainbow Hospital Xianyang 712000, Shaanxi, China.

Insights

Peripheral blood eosinophil (EOS) counts and specific bacteria in the nasopharynx can predict recurrent wheezing in children after respiratory syncytial virus (RSV) lower respiratory tract infections. This helps in early risk assessment for better intervention.

Area of Science:

  • Pediatric Pulmonology
  • Microbiome Research
  • Infectious Diseases

Background:

  • Recurrent wheezing post-respiratory syncytial virus (RSV) infection poses a significant challenge in pediatric respiratory health.
  • Identifying reliable predictors for recurrent wheezing is crucial for timely intervention and management.

Purpose of the Study:

  • To assess the predictive capability of peripheral blood eosinophil (EOS) counts and nasopharyngeal microbiota for recurrent wheezing in children following RSV lower respiratory tract infections.
  • To develop and validate a predictive model for recurrent wheezing.

Main Methods:

  • Retrospective analysis of 614 children with RSV infection, with external validation on 164 children.
  • Collection of clinical data, hematological parameters, and nasopharyngeal microbiota profiles.
  • Logistic regression and receiver operating characteristic (ROC) curve analysis for model development and validation.

Main Results:

  • Peripheral blood EOS count, serum 25(OH)D and IgM levels, and specific nasopharyngeal bacteria (Streptococcus pneumoniae, Haemophilus influenzae) were significantly associated with recurrent wheezing.
  • The developed predictive model demonstrated moderate-to-good diagnostic performance (AUC = 0.747), validated externally (AUC = 0.741).

Conclusions:

  • Peripheral blood EOS count and nasopharyngeal microbiota composition are key predictors of recurrent wheezing after RSV infection.
  • The predictive model offers potential for early risk stratification and personalized interventions to prevent recurrent wheezing in pediatric patients.
Abstract

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