Russell P Bowler1, Victor Kim2, Elizabeth Regan3, André A A Williams3, Stephanie A Santorico4, Barry J Make3, David A Lynch3, John E Hokanson5, George R Washko6, Peter Bercz2, Xavier Soler7, Nathaniel Marchetti2, Gerard J Criner2, Joe Ramsdell7, MeiLan K Han8, Dawn Demeo6, Antonio Anzueto9, Alejandro Comellas10, James D Crapo3, Mark Dransfield11, J Michael Wells11, Craig P Hersh6, Neil MacIntyre12, Fernando Martinez8, Hrudaya P Nath11, Dennis Niewoehner13, Frank Sciurba14, Amir Sharafkhaneh15, Edwin K Silverman6, Edwin J R van Beek16, Carla Wilson17, Christine Wendt13, Robert A Wise18. 1. Department of Medicine, National Jewish Health, Denver, CO. Electronic address: Bowlerr@njhealth.org. 2. Department of Medicine, Section of Pulmonary and Critical Care Medicine, Temple University, Philadelphia PA. 3. Department of Medicine, National Jewish Health, Denver, CO. 4. Department of Mathematical and Statistical Sciences, University of Colorado Denver, Denver, CO. 5. Department of Medicine and the Department of Epidemiology, University of Colorado Anschutz Medical Campus, Aurora, CO. 6. Channing Division of Network Medicine, Division of Pulmonary and Critical Care, Department of Medicine, Brigham and Women's Hospital, Boston, MA. 7. Department of Medicine, Division of Pulmonary and Critical Care Medicine, University of California at San Diego, La Jolla, CA. 8. Department of Internal Medicine, University of Michigan, Ann Arbor, MI. 9. Department of Medicine, Division of Pulmonary and Critical Care Medicine, University of Texas Health Science Center, and South Texas Veterans Health Care System, San Antonio, TX. 10. University of Iowa, Iowa City, IA. 11. University of Alabama at Birmingham, Birmingham, AL. 12. Duke University Medical Center, Durham, NC. 13. University of Minnesota, Minneapolis, MN. 14. University of Pittsburgh Medical Center, Pittsburgh, PA. 15. Baylor College of Medicine, Houston, TX. 16. Clinical Research Imaging Centre, University of Edinburgh, Edinburgh, Scotland. 17. Division of Biostatistics and Bioinformatics, National Jewish Health, Denver, CO. 18. Johns Hopkins University, Baltimore, MD.
Abstract
BACKGROUND: The risk factors for acute episodes of respiratory disease in current and former smokers who do not have COPD are unknown. METHODS: Eight thousand two hundred forty-six non-Hispanic white and black current and former smokers in the Genetic Epidemiology of COPD (COPDGene) cohort had longitudinal follow-up (LFU) every 6 months to determine acute respiratory episodes requiring antibiotics or systemic corticosteroids, an ED visit, or hospitalization. Negative binomial regression was used to determine the factors associated with acute respiratory episodes. A Cox proportional hazards model was used to determine adjusted hazard ratios (HRs) for time to first episode and an acute episode of respiratory disease risk score. RESULTS: At enrollment, 4,442 subjects did not have COPD, 658 had mild COPD, and 3,146 had moderate or worse COPD. Nine thousand three hundred three acute episodes of respiratory disease and 2,707 hospitalizations were reported in LFU (3,044 acute episodes of respiratory disease and 827 hospitalizations in those without COPD). Major predictors included acute episodes of respiratory disease in year prior to enrollment (HR, 1.20; 95% CI, 1.15-1.24 per exacerbation), airflow obstruction (HR, 0.94; 95% CI, 0.91-0.96 per 10% change in % predicted FEV1), and poor health-related quality of life (HR, 1.07; 95% CI, 1.06-1.08 for each 4-unit increase in St. George's Respiratory Questionnaire score). Risks were similar for those with and without COPD. CONCLUSIONS: Although acute episode of respiratory disease rates are higher in subjects with COPD, risk factors are similar, and at a population level, there are more episodes in smokers without COPD.
BACKGROUND: The risk factors for acute episodes of respiratory disease in current and former smokers who do not have COPD are unknown. METHODS: Eight thousand two hundred forty-six non-Hispanic white and black current and former smokers in the Genetic Epidemiology of COPD (COPDGene) cohort had longitudinal follow-up (LFU) every 6 months to determine acute respiratory episodes requiring antibiotics or systemic corticosteroids, an ED visit, or hospitalization. Negative binomial regression was used to determine the factors associated with acute respiratory episodes. A Cox proportional hazards model was used to determine adjusted hazard ratios (HRs) for time to first episode and an acute episode of respiratory disease risk score. RESULTS: At enrollment, 4,442 subjects did not have COPD, 658 had mild COPD, and 3,146 had moderate or worse COPD. Nine thousand three hundred three acute episodes of respiratory disease and 2,707 hospitalizations were reported in LFU (3,044 acute episodes of respiratory disease and 827 hospitalizations in those without COPD). Major predictors included acute episodes of respiratory disease in year prior to enrollment (HR, 1.20; 95% CI, 1.15-1.24 per exacerbation), airflow obstruction (HR, 0.94; 95% CI, 0.91-0.96 per 10% change in % predicted FEV1), and poor health-related quality of life (HR, 1.07; 95% CI, 1.06-1.08 for each 4-unit increase in St. George's Respiratory Questionnaire score). Risks were similar for those with and without COPD. CONCLUSIONS: Although acute episode of respiratory disease rates are higher in subjects with COPD, risk factors are similar, and at a population level, there are more episodes in smokers without COPD.
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