Background and Objectives: Asthma control in preschool children faces major challenges. Single biomarkers such as eosinophil count or fractional exhaled nitric oxide (FeNO) provide incomplete information. This study aimed to evaluate the predictive value of a combined model incorporating eosinophil count, FeNO, alveolar nitric oxide (CaNO), and impulse oscillometry (IOS) parameters for assessing asthma control in preschool children. Methods: In this retrospective study, 136 asthmatic preschool children (study group) and 50 healthy controls underwent measurement of eosinophil count, FeNO, CaNO, and IOS parameters. Asthma control status was determined using the Test for Respiratory and Asthma Control in Kids (TRACK) questionnaire. Statistical analysis included correlation, regression, and receiver operating characteristic (ROC) curve analysis to identify predictive biomarkers. Results: The levels of EOS, FeNO, CaNO, and IOS were all higher in the uncontrolled group than in the controlled group, which in turn was higher than in the healthy group ( P<0.05). These biomarkers inversely correlated with TRACK scores. A combined model integrating FeNO, CaNO, R5–R20, and AX demonstrated superior diagnostic accuracy (AUC: 0.898; sensitivity: 74.6%; specificity: 93.2%). The predictive performance of this model is superior to that of each individual indicator ( P<0.05). Conclusion: The integration of eosinophil count, FeNO, CaNO, and IOS provides a clinically reliable tool for predicting asthma control in preschool children, enabling objective severity assessment and personalized treatment.
Li et al. (Mon,) studied this question.