Predictors of fatigue in patients with hip and knee osteoarthritis

Abstract

s / Osteoarthritis and Cartilage 21 (2013) S63–S312 S250 Conclusions: Knees that were replaced (KRs) had lower baseline cartilage thickness and greater longitudinal (1 year) cartilage loss than nonKRs, the differences being strongest in both tibiae. Cartilage loss in the weight-bearing femur (a region commonly showing the greatest rate and sensitivity to change), in contrast showed less discrimination. The ability to discriminate between KRs and non-KRs was greater for “earlier” KRs (within 2 years after measurement of cartilage loss) than for those who received KR “later” (year 2-4 after measuring cartilage loss). 474 PREDICTORS OF FATIGUE IN PATIENTS WITH HIP AND KNEE OSTEOARTHRITIS K.D. Allen y,z, H.B. Bosworth y,z, C.J. Coffman y,z, A.S. Jeffreys y, E.Z. Oddone y,z, W.S. Yancy, Jr. y,z. yDurham VA Med. Ctr., Durham, NC, USA; zDuke Univ. Med. Ctr., Durham, NC, USA Purpose: Fatigue is emerging as an important outcome for patients with osteoarthritis (OA), but little is known about factors that predict fatigue severity. This study examined associations of demographic and clinical factors with fatigue in a cohort of patients with hip and / or knee OA. Methods: Participants were n1⁄4291 patients enrolled in a clinical trial of a combined patient and provider intervention for managing OA at the Durham Veterans Affairs Medical Center (mean age 1⁄4 61, SD1⁄49, 90% male, 53% non-white primarily African American). All measures were from baseline assessments. Fatigue was assessed with a 10cm visual analog scale (range 0-10) that asked participants to report how much fatigue has been a problem for them during the past week; anchors were “Fatigue is no problem” and “Fatigue is a major problem.” Potential predictors included participant age, race (white vs. nonwhite), gender, education (some vs. no college), self-rated health (excellent, very good, or good vs. fair or poor), pain severity (Western Ontario and McMasters University Osteoarthritis Index pain subscale), insomnia (Insomnia Severity Index), and depressive symptoms (Patient Health Questionnaire-8). Simple linear regression models examined associations of each individual predictor variable with fatigue, then a multivariable model was fit including all predictors that were significantly associated (p<0.01) with fatigue in simple regression models. Results: The mean fatigue score was 4.8 (SD1⁄43.1). In simple regression models, older age was associated with slightly lower fatigue (b1⁄4 0.07, 95%CI 1⁄4 -0.1, -0.04; p<0.001), and the following were associate with more fatigue: fair / poor self-rated health (b1⁄42.2, 95%CI 1⁄4 1.3, 3.1; p<0.001), greater insomnia severity (b 1⁄4 0.21, 95%CI 1⁄4 0.2, 0.3, p<0.001), greater pain severity (b1⁄4 0.4, 95%CI1⁄4 0.3, 0.5; p<0.001), and greater depressive symptoms (b 1⁄4 0.35, 95%CI 1⁄4 0.3, 0.4; p<0.001). In the multivariable model, variables that remained associated with fatigue were insomnia severity (b 1⁄4 0.06, 95%CI 1⁄4 0.01, 0.1; p1⁄40.0), pain severity (b 1⁄4 0.20, 95%CI 1⁄4 0.1, 0.3; p<0.001), depressive symptoms (b 1⁄4 0.21, 95%CI 1⁄4 0.1, 0.3; p<0.001). Conclusions: Fatigue severity was relatively high in this cohort of patients with OA; mean values on the fatigue visual analog scale were comparable to those seen in patients with rheumatoid arthritis. Demographic factors including age, as well as general health, were not associated with fatigue in the multivariable model. However, key clinical variables related to OA pain, depressive symptoms, and insomnia were associated with more fatigue. These results highlight that fatigue is part of a cluster of OA-related symptoms that generally worsen with greater disease severity. Because of its impact on daily activities and quality of life, fatigue is an important issue to address among patients