Salta al contenuto principale
Passa alla visualizzazione normale.

YURI ANTONACCI

Preliminary development of a questionnaire to measure the extra-pulmonary symptoms of severe asthma

  • Autori: de Felice, Giulio; Hyland, Michael E.; Lanario, Joseph W.; Antonacci, Yuri; Jones, Rupert C.; Masoli, Matthew
  • Anno di pubblicazione: 2021
  • Tipologia: Articolo in rivista
  • OA Link: http://hdl.handle.net/10447/524825

Abstract

Background: Research into the effects of asthma treatments on the extra-pulmonary symptoms of severe asthma is limited by the absence of a suitable questionnaire. The aim was to create a questionnaire suitable for intervention studies by selecting symptoms that are statistically associated with asthma pathology and therefore may improve when pathology is reduced. Methods: Patients attending a specialist asthma clinic completed the 65-item General Symptom Questionnaire (GSQ-65), a questionnaire validated for assessing symptoms of people with multiple medically unexplained symptoms. Lung function (FEV1%) and cumulative oral corticosteroids (OCS) calculated from maintenance dose plus exacerbations were obtained from clinic records. Pathology was represented by the two components of a principal component analysis (PCA) of FEV1% and OCS. LASSO regression was used to select symptoms that had high coefficients with these two principal components and occurred frequently in severe asthma. Results:100 patients provided data. PCA revealed two components, one where FEV1% and OCS were inversely related and another where they were directly related. LASSO regression revealed 39 symptoms with non-zero coefficients on one or more of the two principal components from which 16 symptoms were selected for the GSQ-A on the basis of magnitude of coefficient and frequency. Asthma symptoms measured by asthma control questionnaires were excluded. The GSQ-A correlated 0.33 and − 0.34 (p = 0.001) with the two principal components. Conclusion: The GSQ-A assesses the frequency of 16 heterogenous non-respiratory symptoms that are associated with asthma severity using the statistical combination of FEV1% and OCS.