TY - JOUR T1 - Predictive Model of Hospital Admission for COPD Exacerbation JF - Respiratory Care DO - 10.4187/respcare.04005 SP - respcare.04005 AU - Josep Montserrat-Capdevila AU - Pere Godoy AU - Josep Ramon Marsal AU - Ferran Barbé Y1 - 2015/08/18 UR - http://rc.rcjournal.com/content/early/2015/08/18/respcare.04005.abstract N2 - BACKGROUND: The objective of this work was to determine predictive factors of hospital admission for exacerbation during primary care visits in patients with COPD.METHODS: A retrospective cohort study was undertaken to assess risk of hospital admission for COPD exacerbation in primary care patients from November 1, 2010 to October 31, 2013. Data sources were primary care electronic medical records and the hospital discharge minimum data set. A total of 2,501 subjects >40 y of age with a spirometry-based COPD diagnosis were included and followed up for 3 y. The dependent variable was hospital admission for exacerbation; independent variables were: clinical parameters, spirometry results, and severity of disease (according to Global Initiative for Chronic Obstructive Lung Disease criteria). The association of these variables with hospital admission was analyzed with the adjusted odds ratio using a logistic regression model.RESULTS: Mean age of subjects at the beginning of the study was 68.4 y (SD = 11.6), and 75% were men. Severity was mild in 50.8% of subjects, moderate in 35.3%, severe in 9.4%, and very severe in 4.4%. After 3y, 32.5% of subjects had been admitted for exacerbation. Predictive values for hospital admission were: age, sex, previous exacerbations, number of visits to the primary care center, comorbidities, smoking, severity (Global Initiative for Chronic Obstructive Lung Disease), and influenza immunization. The area under the receiving operator characteristic curve was 0.72.CONCLUSIONS: This model can identify patients at high risk of hospital admission for COPD exacerbation in our setting. Further studies are needed to validate the model in different populations and settings. ER -