Abstract

Introduction: Acute exacerbations of disease symptoms in patients with chronic obstructive pulmonary disease (COPD) often lead to hospitalization and impose a great financial burden on the health care system. Nonetheless, there is a paucity of data regarding the predictors of disease exacerbation in these patients. This study aimed to determine factors which can predict rehospitalization in COPD patients. Material and methods: A total of 157 COPD patients were selected via systematic sampling from all the patients admitted to the Chest Clinic of Baqiyataliah Hospital during the year 2006. Subjects were followed for 12 months for the occurrence of any disease exacerbation that led to hospitalization. Demographic data gender, age, marital status, monthly income (less than 200 $, and equal to or higher than 200 $), level of education (below diploma and diploma or higher), spirometric findings (percent predicted vital capacity (VC % predicted), percent predicted FVC (FVC % predicted), and percent predicted FEV1 (FEV1 % predicted), physical comorbidity (assessed by Ifuclu index), presence of anxiety or depression (evaluated by the Hospital Anxiety Depression Scale), and body mass index (BMI) were recorded for each patient. Multivariate regression was applied to find out the predicting factors of disease exacerbation. Results: Over the 12-month period, 87 (55%) experienced disease exacerbation. Significant associations were found between COPD exacerbation and monthly income (p=0.001), comorbidity score (p=0.05), anxiety (p=0.013) and depression (p=0.025). VC % predicted, FVC % predicted and FEV1 % predicted had no significant association with disease exacerbation (p>0.05). Predictors of COPD exacerbation were found to be monthly income lower than 200 $ (p=0.002), higher comorbidity score (p=0.05) and depression (p=0.05). A prediction equation was designed to help clinicians predict disease exacerbation. Conclusions: Physical comorbidity, severity of depression and tow income can be used to predict COPD exacerbation. We recommend that more attention be given to these predictors.