25 February 2015
Patients with chronic obstructive pulmonary disease (COPD) frequently suffer from comorbidities. COPD severity may be evaluated by the Global initiative for chronic Obstructive Lung Disease (GOLD) combined risk assessment score (GOLD score). Spirometry, body plethysmography, diffusing capacity of the lung for carbon monoxide (DLCO), and high-resolution computed tomography (HR-CT) measure lung function and elucidate pulmonary pathology. This study assesses associations between GOLD score and measurements of lung function in COPD patients with and without (≤1) comorbidities. It evaluates whether the presence of comorbidities influences evaluation by GOLD score of COPD severity, and questions whether GOLD score describes morbidity rather than COPD severity.
In this prospective study, 106 patients with stable COPD were included. Patients treated for lung cancer were excluded. Demographics, oxygen saturation (SpO 2), modified Medical Research Council Dyspnea Scale, COPD exacerbations, and comorbidities were recorded. Body plethysmography and DLCO were measured, and HR-CT performed and evaluated for emphysema and airways disease. COPD severity was stratified by the GOLD score. Correlation analyses: 1) GOLD score, 2) emphysema grade, and 3) airways disease and lung function parameters, described by: forced expiratory volume in the first second in percent of expected value (FEV 1%), inspiratory capacity (IC%), total lung volume (TLC%), IC/TLC, and SpO 2. Correlation analyses between subgroups and hierarchical cluster analysis were performed.
Significant associations were found between GOLD score and both emphysema grade (correlation coefficients [cc]: −0.2, P=0.03) and lung function parameters (cc: −0.5 to −0.7, P-values all <0.001) weakened in patients with >1 comorbidity (cc: −0.4 to −0.5, P-values all 0.001). Significant differences between subgroups were found in GOLD score and both FEV 1% (cc: −0.2, P=0.02) and IC/TLC (cc: −0.2, P=0.02). Comorbidities were associated with GOLD score and composite measures in hierarchical cluster analysis.