The role of small airway function parameters in preschool asthmatic children.

BACKGROUND: Small airways are the major sites of inflammation and airway remodeling in all severities of asthma patients. However, whether small airway function parameters could reflect the airway dysfunction feature in preschool asthmatic children remain unclear. We aim to investigate the role of small airway function parameters in evaluating airway dysfunction, airflow limitation and airway hyperresponsiveness (AHR). METHODS: Eight hundred and fifty-one preschool children diagnosed with asthma were enrolled retrospectively to investigate the characteristics of small airway function parameters. Curve estimation analysis was applied to clarify the correlation between small and large airway dysfunction. Spearman's correlation and receiver-operating characteristic (ROC) curves were employed to evaluate the relationship between small airway dysfunction (SAD) and AHR. RESULTS: The prevalence of SAD was 19.5% (166 of 851) in this cross-sectional cohort study. Small airway function parameters (FEF25-75%, FEF50%, FEF75%) showed strong correlations with FEV1% (r = 0.670, 0.658, 0.609, p<0.001, respectively), FEV1/FVC% (r = 0.812, 0.751, 0.871, p<0.001, respectively) and PEF% (r = 0.626, 0.635, 0.530, p<0.01, respectively). Moreover, small airway function parameters and large airway function parameters (FEV1%, FEV1/FVC%, PEF%) were curve-associated rather than linear-related (p<0.001). FEF25-75%, FEF50%, FEF75% and FEV1% demonstrated a positive correlation with PC20 (r = 0.282, 0.291, 0.251, 0.224, p<0.001, respectively). Interestingly, FEF25-75% and FEF50% exhibited a higher correlation coefficient with PC20 than FEV1% (0.282 vs. 0.224, p = 0.031 and 0.291 vs. 0.224, p = 0.014, respectively). ROC curve analysis for predicting moderate to severe AHR showed that the area under the curve (AUC) was 0.796, 0.783, 0.738, and 0.802 for FEF25-75%, FEF50%, FEF75%, and the combination of FEF25-75% and FEF75%, respectively. When Compared to children with normal lung function, patients with SAD were slightly older, more likely to have a family history of asthma and airflow obstruction with lower FEV1% and FEV1/FVC%, lower PEF% and more severe AHR with lower PC20 ( all p<0.05). CONCLUSION: Small airway dysfunction is highly correlated with large airway function impairment, severe airflow obstruction and AHR in preschool asthmatic children. Small airway function parameters should be utilized in the management of preschool asthma.

Development and validation of a prediction model to predict school-age asthma in preschool children.

OBJECTIVE: To develop and validate a clinical prediction model to identify school-age asthma in preschool asthmatic children. STUDY DESIGN: In this retrospective prognosis cohort study, asthmatic children aged 3-5 years were enrolled with at least 2 years of follow-up, and their potential variables at baseline and the prognosis of school-age asthma were collected from medical records. A clinical prediction model was developed using Logistic regression. The performance of prediction model was assessed and quantified by discrimination of the area under the receiver operating characteristic curve (AUC) and calibration of Brier score. The model was validated by the temporal-validation method. RESULTS: In the development dataset, 2748 preschool asthmatic children were included for model development, and 883 (32.13%) children were translated to school-age asthma. The independent prognostic variables with an increased risk for school-age asthma were used to develop the prediction model, including: age, parental asthma, early frequent wheezing, allergic rhinitis, eczema, allergic conjunctivitis, obesity, and aeroallergen of dust mite. While assessing model performance, the discrimination power of AUC was moderate [0.788 (0.770-0.805)] with sensitivity (81.5%) and specificity (60.9%), and the calibration of Brier score was 0.169, supporting the calibration ability. In the temporal-validation dataset of 583 preschool asthmatic children, our model showed satisfactory discrimination (AUC 0.818) and calibration (Brier score 0.150). The prediction model was presented by the web-based calculator (https://casthma.shinyapps.io/dynnomapp/) and a nomogram for clinical application. CONCLUSION: In preschool asthmatic children, our prediction model could be used to predict the risk of school-age asthma.