Classification of pulmonary-function tests by principal component analysis

Abstract

The structure of pulmonary-function data obtained from 468 randomly selected subjects was analyzed. The subjects included patients with chronic bronchitis, bronchial asthma, chronic pulmonary emphysema, diffuse panbronchiolitis, and idiopathic interstitial pneumonitis, and normal health adults. From among the many possible indices of pulmonary function, 19 were chosen and were used as variables in principal component analysis. Six significant principal components (PCs) were extracted. The first three PCs accounted for 70% of the total information and were termed "ventilation," "volume," and "diffusion." The second three PCs accounted for 17% of the information and were termed "small airway," "lower airway," and "shape." Indices of ventilatory unevenness were not separated from indices of airway obstruction, and were included in the first PC. No other, unknown PC was detected with these pulmonary-function indices. The relationship among indices is displayed in a factor loading matrix, and pulmonary-function tests are classified statistically.