BACKGROUND: There has been no large-scale and comprehensive study of the differences between asthma in elderly asthmatics (EA) and non-elderly (i.e. young) asthmatics (NEA). METHODS: We performed principal component analysis (PCA) using 2067 asthmatics (434 EA and 1633 NEA) from the Korean Cohort for Reality and Evolution of adult Asthma (COREA). EA was defined as asthmatics with the chronological age of 65 or more and eleven clinical variables measured at enrollment were used for PCA; symptom score, symptom duration, number of exacerbation during previous one year, smoking pack year, number of controller medications, body mass index, predicted % of FEV1, predicted % FVC, post-bronchodilator FEV1/FVC ratio, atopy index and number of eosinophils in peripheral blood. RESULTS: PCA of all asthmatics showed that EA and NEA were distinctly separated by the first and second principal component on the plot of individual asthmatics according to their scores. For further analysis, we divided all asthmatics into the EA and the NEA group and performed PCA again in each group. The first four principal components with eigenvalues ≥ 1.0 were identified in both groups and they explained 55.5% of the variance in the EA group and 52.4% in the NEA group respectively. Clinical variables showed distinctly different patterns of loading on the first four principal components between the EA and the NEA group. CONCLUSION: EA and NEA have different compositional patterns underlying their clinical variables. These observations helped in understanding the differences between EA and NEA from the integrated view covering various clinical aspects.
BACKGROUND: There has been no large-scale and comprehensive study of the differences between asthma in elderly asthmatics (EA) and non-elderly (i.e. young) asthmatics (NEA). METHODS: We performed principal component analysis (PCA) using 2067 asthmatics (434 EA and 1633 NEA) from the Korean Cohort for Reality and Evolution of adult Asthma (COREA). EA was defined as asthmatics with the chronological age of 65 or more and eleven clinical variables measured at enrollment were used for PCA; symptom score, symptom duration, number of exacerbation during previous one year, smoking pack year, number of controller medications, body mass index, predicted % of FEV1, predicted % FVC, post-bronchodilator FEV1/FVC ratio, atopy index and number of eosinophils in peripheral blood. RESULTS: PCA of all asthmatics showed that EA and NEA were distinctly separated by the first and second principal component on the plot of individual asthmatics according to their scores. For further analysis, we divided all asthmatics into the EA and the NEA group and performed PCA again in each group. The first four principal components with eigenvalues ≥ 1.0 were identified in both groups and they explained 55.5% of the variance in the EA group and 52.4% in the NEA group respectively. Clinical variables showed distinctly different patterns of loading on the first four principal components between the EA and the NEA group. CONCLUSION: EA and NEA have different compositional patterns underlying their clinical variables. These observations helped in understanding the differences between EA and NEA from the integrated view covering various clinical aspects.
Authors: Barbara J Polivka; Rodney Folz; John Myers; Russell Barnett; Demetra Antimisiaris; Anna Jorayeva; Bryan Beatty Journal: Res Nurs Health Date: 2018-08 Impact factor: 2.228
Authors: Anahí Yáñez; Marcela Soria; Susana De Barayazarra; Nancy Recuero; Francisco Rovira; Edgardo Jares; Ana María Stok; Sergio Nemirovsky; Carlos Bueno Journal: Asthma Res Pract Date: 2018-04-23
Authors: Victoria S Benson; Sylvia Hartl; Neil Barnes; Nicholas Galwey; Melissa K Van Dyke; Namhee Kwon Journal: Eur Respir J Date: 2022-01-13 Impact factor: 16.671