| Literature DB >> 31342731 |
William W Stringer1, Janos Porszasz1, Surya P Bhatt2, Meredith C McCormack3, Barry J Make4, Richard Casaburi1.
Abstract
COPD Genetic Epidemiology Study (COPDGene®) manuscripts have provided important insights into chronic obstructive pulmonary disease (COPD) pathophysiology and outcomes, including a better understanding of COPD phenotypes relating computed tomography (CT) anatomic data to spirometric and patient-reported outcomes. Spirometry significantly underdiagnoses smoking-induced lung disease, and there is a marked improvement in sensitivity and specificity with CT scanning. This review also highlights the COPDGene® exploration of specific spirometry phenotypes (e.g.,PRISm), contributors to spirometric decline, composite physiologic measures, asthma-COPD overlap (ACO) syndrome, consequences of bronchodilator responsiveness, newer methods to assess small airway dysfunction, and spirometric correlates of comorbid diseases such as obesity and diabetes. JCOPDFEntities:
Keywords: COPD Genetic Epidemiology; COPDGene; PRISm; Preserved Ratio Impaired Spirometry; asthma-COPD overlap; chronic obstructive pulmonary disease; copd
Year: 2019 PMID: 31342731 PMCID: PMC6872216 DOI: 10.15326/jcopdf.6.3.2019.0128
Source DB: PubMed Journal: Chronic Obstr Pulm Dis ISSN: 2372-952X