Translational pediatrics · 2026
Eosinophil-derived neurotoxin as a biomarker to predict the development of asthma after respiratory infection in infant.
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Huang Yijie, Li Guiju, Zhang Peiling, Zhang Lei, Fan Yinghong
Аннотация
BACKGROUND: Respiratory tract infection in infancy can cause symptomatic wheezing or asthma later in childhood. In recent years, eosinophil-derived neurotoxin (EDN) has been proposed to play a role in the development of asthma, however, this fact remains unclear. Therefore, this study aimed to determine whether EDN is a biomarker to predict asthma following respiratory tract infections in infants.
METHODS: From October 2021 to March 2022, we tracked children hospitalized for respiratory tract infections at the Chengdu Women's and Children's Central Hospital. All patients underwent medical history collection and EDN testing, and were followed up at 6 months, 1 year and 3 years post-discharge. Multifactor analysis was subsequently conducted using multivariate logistic regression and receiver operating characteristic (ROC) analysis.
RESULTS: A total of 183 participants were enrolled in this study. Statistical data showed that EDN levels were significantly higher in the asthma group (P<0.001). Multivariate regression analysis revealed that EDN, number of wheezing within 6 months, and allergy history were independent risk factors for asthma development following respiratory tract infections in children. Further ROC curve analysis demonstrated that EDN has predictive value for asthma occurrence, and combining it with number of wheezing within 6 months and allergy history can further enhance its predictive efficacy.
CONCLUSIONS: EDN may be a useful biomarker to predict the development of asthma following respiratory tract infections in infants and could be used as a useful screening tool for asthma in young children.
METHODS: From October 2021 to March 2022, we tracked children hospitalized for respiratory tract infections at the Chengdu Women's and Children's Central Hospital. All patients underwent medical history collection and EDN testing, and were followed up at 6 months, 1 year and 3 years post-discharge. Multifactor analysis was subsequently conducted using multivariate logistic regression and receiver operating characteristic (ROC) analysis.
RESULTS: A total of 183 participants were enrolled in this study. Statistical data showed that EDN levels were significantly higher in the asthma group (P<0.001). Multivariate regression analysis revealed that EDN, number of wheezing within 6 months, and allergy history were independent risk factors for asthma development following respiratory tract infections in children. Further ROC curve analysis demonstrated that EDN has predictive value for asthma occurrence, and combining it with number of wheezing within 6 months and allergy history can further enhance its predictive efficacy.
CONCLUSIONS: EDN may be a useful biomarker to predict the development of asthma following respiratory tract infections in infants and could be used as a useful screening tool for asthma in young children.