Classification of patients with knee osteoarthritis in clinical phenotypes: data from the osteoarthritis initiative

<div><p>Objectives</p><p>The existence of phenotypes has been hypothesized to explain the large heterogeneity characterizing the knee osteoarthritis. In a previous systematic review of the literature, six main phenotypes were identified: Minimal Joint Disease (MJD), Malaligned Biomechanical (MB), Chronic Pain (CP), Inflammatory (I), Metabolic Syndrome (MS) and Bone and Cartilage Metabolism (BCM). The purpose of this study was to classify a sample of individuals with knee osteoarthritis (KOA) into pre-defined groups characterized by specific variables that can be linked to different disease mechanisms, and compare these phenotypes for demographic and health outcomes.</p><p>Methods</p><p>599 patients were selected from the OAI database FNIH at 24 months’ time to conduct the study. For each phenotype, cut offs of key variables were identified matching the results from previous studies in the field and the data available for the sample. The selection process consisted of 3 steps. At the end of each step, the subjects classified were excluded from the further classification stages. Patients meeting the criteria for more than one phenotype were classified separately into a ‘complex KOA’ group.</p><p>Results</p><p>Phenotype allocation (including complex KOA) was successful for 84% of cases with an overlap of 20%. Disease duration was shorter in the MJD while the CP phenotype included a larger number of Women (81%). A significant effect of phenotypes on WOMAC pain (F = 16.736 p <0.001) and WOMAC physical function (F = 14.676, p < 0.001) was identified after controlling for disease duration.</p><p>Conclusion</p><p>This study signifies the feasibility of a classification of KOA subjects in distinct phenotypes based on subgroup-specific characteristics.</p></div

Incidence of total knee and hip replacement for osteoarthritis in relation to the metabolic syndrome and its components: a prospective cohort study

Abstract not availableSultana Monira Hussain, Yuanyuan Wang, Flavia M. Cicuttini, Julie A. Simpson, Graham G. Giles, Stephen Graves, Anita E. Wluk

Predictors of back pain in middle-aged women: data from the Australian longitudinal study of women's health

Back pain causes greater disability worldwide than any other condition, with women more likely to experience back pain than men. Our aim was to identify modifiable risk factors for back pain in middle-aged women.Women born between 1946 and 1951 were randomly selected from the national health insurance scheme database to participate in The Australian Longitudinal Study on Women's Health. Self-reported data on back pain in the last 12 months, and on weight, physical activity, and other sociodemographic factors, were collected in 1998, 2001, 2004, 2007, 2010, and 2013. In 1998, a total of 12,338 women completed the survey and 10,011 (74%) completed the 2013 survey.At baseline, median (range) age was 49.5 years (44.6-53.5 years), and 54% reported back pain. In multivariate analysis, baseline weight and depression were positive predictors of back pain over each 3-year survey interval and over the following 15 years, whereas participation in vigorous physical activity was protective. The effects of weight on back pain were most marked in women with a body mass index of ≥25 kg/m2 .Back pain is common in middle-aged women. Increased weight, weight gain, and depression were independent predictors of back pain over 15 years, whereas participation in vigorous physical activity was protective. Targeting these lifestyle factors is an important area for future research on reducing the burden of back pain in middle-aged women.Sharmayne R. E. Brady, Sultana Monira Hussain, Wendy J. Brown, Stephane Heritier, Yuanyuan Wang, Helena Teede, Donna M. Urquhart, Flavia M. Cicuttin