Development and validation of asthma diagnostic scale for children
Development and validation of asthma diagnostic scale for children

Development and validation of asthma diagnostic scale for children

Pediatr Res. 2024 Sep 26. doi: 10.1038/s41390-024-03584-8. Online ahead of print.

ABSTRACT

BACKGROUND: To construct an asthma diagnostic scale for children under 6 years old.

METHODS: An electronic medical record database was used to develop the scale. Item pool was established through literature survey and expert opinion. Items were screened and optimized by using the Delphi method, t-test, reactivity analysis, Pearson correlation coefficient, factor analysis, reliability and validity test. The predictive probability of asthma was calculated using logistic regression, and receiver operating characteristic curve. Another childhood asthma database was used to validated the scale.

RESULTS: The asthma diagnostic scale for children under 6 years old included five dimensions: dimension 1 (shortness of breath, three concave sign, cyanosis, moist rale, heart rhythm, heart sound and dyspnea), dimension 2 (respiratory sound, cough, sputum), dimension 3 (frequency of wheezing, allergic rhinitis, history of allergy in one or both parents), dimension 4 (sex, wheezing, atopic dermatitis), and dimension 5 (reversible airflow, positive in vitro or in vivo allergy test). The Cronbach’s α coefficients for the five dimensions were 0.846, 0.459, 0.019, 0.202, and 0.024. The area under the ROC curve (AUC), sensitivity, and specificity were 0.737, 59.1%, and 81.2%. AUC, sensitivity, and specificity in the validation database were 0.614, 76.2%, and 46.7%.

CONCLUSION: The scale has significant diagnostic value for asthma in children under 6 years old.

IMPACT: 1. The aim of the study was to establish an asthma diagnosis scale for children younger than 6 years old. 2. Our study not only addresses the lack of diagnostic criteria of young children asthma, but also indicates the accuracy of the diagnostic scale. 3. The data may help to reduce the missed diagnosis and misdiagnosis rate of asthma, and improve the diagnostic accuracy of the disease, and thus reduces the harm of asthma to children’s physical and mental health.

PMID:39327463 | DOI:10.1038/s41390-024-03584-8