Introduction

1. Fatigue and decreased health can predict mortality in COPD Caroline Stridsman, RN, PhD-student1,2, Lisa Skär, RN, PhD1, Linnea Hedman, PhD2 and Anne Lindberg, MD, PhD2,3 1. Department of Health Science, Division of Nursing, Luleå University of Technology, Sweden. 2. The OLIN studies, Norrbotten County Council, Luleå, Sweden. 3. Department of Public Health and Clinical Medicine, Division of Medicine, Umeå University, Sweden. Results Characteristics of the study population are shown in Table 1. Mortality rate was 7.1% in COPD 6.0% in non-COPD. Each of the FACIT-F, SF-36 PCS and MCS scores were analysed as risk factors for mortality in separate multivariate models (Models A, B and C), including the covariates sex, age, BMI and heart disease. When stratified by non-COPD and COPD different patterns emerged. In non-COPD, male sex and increased age significantly increased the risk for mortality in all three models, while in COPD lower FACIT-F score (OR 1.06, CI 1.02-1.10), PCS score (OR 1.04, CI 1.01-1.08) and MCS score (OR 1.06, CI 1.02-1.10) were independent risk factors for mortality in Model A, B and C, respectively (Table 2). Introduction Chronic obstructive pulmonary disease (COPD) is related to increased fatigue, decreased health status, and increased mortality. Studies with selected study populations have shown that decreased health status predicts mortality in subjects with COPD.1,2,3 However, corresponding conditions have hardly been evaluated in population-based studies. Aim The aim was to investigate if fatigue, physical and/or mental health status can predict mortality in subjects with and without COPD in a population-based study. Table 1. Characteristics of study population. Definitions: Heart disease as a self-reported history of at least one of; angina pectoris, myocardial infarction, cardiac insufficiency, coronary artery bypass or Percutaneous Coronary Intervention (PCI) procedure. Respiratory symptoms as a self-reported history of at least one of; mMRC-dyspnea >2, chronic cough, chronic productive cough or recurrent wheeze. Methods Data were collected from the Obstructive Lung Disease in Northern Sweden (OLIN) COPD study (993 subjects with COPD together with 993 gender- and age matched subjects without obstructive lung function impairment were identified in the years 2002-04 from population based cohorts).4COPD was defined according to the the Global Initiative for Chronic Obstructive Lung Disease (GOLD) spirometric criteria, FEVı/FVC<0.70. In 2007, Subjects with (n=434) and without (n=655) COPD answered the Functional Assessment of Chronic Illness Therapy (FACIT)- Fatigue scale and the Short Form 36 (SF-36). In FACIT-F, lower scores represent increased fatigue.5 In the generic health status questionnaire, SF-36, two summary scores were combined; Physical (PCS) and Mental (MCS) dimensions of health, and lower score indicates decreased health status.6 Mortality data were collected from the date of examination in 2007 until February 2012. Table 2. Multiple logistics regression model analysing risk factors for mortality in separate models (A-C) for FACIT-Fatigue, SF-36 PCS and MCS scores, respectively. Covariates in the models; sex, age, BMI and heart disease. BMI and heart disease were non-significant, data not shown. Odds Ratio (OR) and 95% confidence interval (CI). *Entered as continuous variables. Amongsubjects with COPD the median score of each the FACIT-F, the SF-36 PCS and MCS in 2007 was significant lower among those who died during follow-up compared to among the survivors (Figure 1). Conclusions In this population based study increased fatigue, lower physical and mental health status was independently associated with mortality, in COPD but not in non-COPD. Our study highlights the importance to identify fatigue and decreased health status as predictors of mortality among subjects with COPD. Figure 1. Median FACIT-Fatigue, SF-36 physical (PCS) and mental (MCS) components score, comparing survivors and deceased in non-COPD and COPD, respectively. References 1. Esteban et al. J Gen Intern Med 2008. 4. Lindberg, Lundbäck. ClinRespir J 2008. 2. Domingo Salvany et al. Am J RespCrit Care 2002. 5. Cella et al. Cancer2002. 3. Sundhet al. Int J Chron Obstruct Pulmon Dis 2012. 6. Sullivan et al. SocSci Med 1995. Acknowledgements/fundingThe authors thank Professor Bo Lundbäck the initiator and scientific advisor of the OLIN studies, and Professor Eva Rönmark the present head of the OLIN studies for their support.Ann-Christine Jonsson and Sigrid Sundberg are acknowledged for data collection. The authors also thank Ola Bernhoff and Helena Backman for work with creating the data base of the study, and Viktor Johansson for computerising the data. The Swedish Heart-Lung Foundation, the Swedish Research Council, the Norrbotten County Council and Visare Norr are acknowledged for financial support. Caroline Stridsman, MSc, PhD-student The OLIN Studies Norrbotten County Council S-971 89 Luleå, Sweden E-mail: caroline.stridsman@nll.se