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Objective: To gain better understanding of osteoarthritis (OA) heterogeneity and its predictors for distinguishing OA phenotypes. This could provide the opportunity to tailor prevention and treatment strategies and thus improve care., Design: Ten year follow-up data from CHECK (1002 early-OA subjects with first general practitioner visit for complaints ≤6 months before inclusion) was used. Data were collected on WOMAC (pain, function, stiffness), quantitative radiographic tibiofemoral (TF) OA characteristics, and semi-quantitative radiographic patellofemoral (PF) OA characteristics. Using functional data analysis, distinctive sets of trajectories were identified for WOMAC, TF and PF characteristics, based on model fit and clinical interpretation. The probabilities of knee membership to each trajectory were used in hierarchical cluster analyses to derive knee OA phenotypes. The number and composition of potential phenotypes was selected again based on model fit (silhouette score) and clinical interpretation., Results: Five trajectories representing different constant levels or changing WOMAC scores were identified. For TF and PF OA, eight and six trajectories respectively were identified based on (changes in) joint space narrowing, osteophytes and sclerosis. Combining the probabilities of knees belonging to these different trajectories resulted in six clusters ('phenotypes') of knees with different degrees of functional (WOMAC) and radiographic (PF) parameters; TF parameters were found not to significantly contribute to clustering. Including baseline characteristics as well resulted in eight clusters of knees, dominated by sex, menopausal status and WOMAC scores, with only limited contribution of PF features., Conclusions: Several stable and progressive trajectories of OA symptoms and radiographic features were identified, resulting in phenotypes with relatively independent symptomatic and radiographic features. Sex and menopausal status may be especially important when phenotyping knee OA patients, while radiographic features contributed less. Possible phenotypes were identified that, after validation, could aid personalized treatments and patients selection., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Altamirano et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Objective: Digital symptom-checkers (SCs) have potential to improve rheumatology triage and reduce diagnostic delays. In addition to being accurate, SCs should be user friendly and meet patient's needs. Here, we examined usability and acceptance of Rheumatic? -a new and freely available online SC (currently with >44 000 users)-in a real-world setting., Methods: Study participants were recruited from an ongoing prospective study, and included people ≥18 years with musculoskeletal complaints completing Rheumatic? online. The user experience survey comprised five usability and acceptability questions (11-point rating scale), and an open-ended question regarding improvement of Rheumatic? Data were analysed in R using t-test or Wilcoxon rank test (group comparisons), or linear regression (continuous variables)., Results: A total of 12 712 people completed the user experience survey. The study population had a normal age distribution, with a peak at 50-59 years, and 78% women. A majority found Rheumatic? useful (78%), thought the questionnaire gave them an opportunity to describe their complaints well (76%), and would recommend Rheumatic? to friends and other patients (74%). Main shortcoming was that 36% thought there were too many questions. Still, 39% suggested more detailed questions, and only 2% suggested a reduction of questions., Conclusion: Based on real-world data from the largest user evaluation study of a digital SC in rheumatology, we conclude that Rheumatic? is well accepted by women and men with rheumatic complaints, in all investigated age groups. Wide-scale adoption of Rheumatic? , therefore, seems feasible, with promising scientific and clinical implications on the horizon., Competing Interests: Competing interests: RK is an editorial board member of RMD Open. She has not been involved in handling of the manuscript at RMD Open, or in communication with the journal regarding the study. LUMC and KI are research collaborators with Elsa Science AB. Elsa Science AB has contributed to the collaboration with in-kind contributions to the design, development and hosting of the digital symptom-checker Rheumatic? KL was part-time employed by Elsa Science, January 2022–February 2023. All other authors declare no commercial or financial conflict of interest in relation to the study., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Objectives: To investigate cartilage tissue turnover in response to a supervised 12-week exercise-related joint loading training program followed by a 6-month period of unsupervised training in patients with knee osteoarthritis (OA). To study the difference in cartilage tissue turnover between high- and low-resistance training., Method: Patients with knee OA were randomized into either high-intensity or low-intensity resistance supervised training (two sessions per week) for 3 months and unsupervised training for 6 months. Blood samples were collected before and after the supervised training period and after the follow-up period. Biomarkers huARGS, C2M, and PRO-C2, quantifying cartilage tissue turnover, were measured by ELISA. Changes in biomarker levels over time within and between groups were analyzed using linear mixed models with baseline values as covariates., Results: huARGS and C2M levels increased after training and at follow-up in both low- and high-intensity exercise groups. No changes were found in PRO-C2. The huARGS level in the high-intensity resistance training group increased significantly compared to the low-intensity resistance training group after resistance training (p = 0.029) and at follow-up (p = 0.003)., Conclusion: Cartilage tissue turnover and cartilage degradation appear to increase in response to a 3-month exercise-related joint loading training program and at 6-month follow-up, with no evident difference in type II collagen formation. Aggrecan remodeling increased more with high-intensity resistance training than with low-intensity exercise. These exploratory biomarker results, indicating more cartilage degeneration in the high-intensity group, in combination with no clinical outcome differences of the VIDEX study, may argue against high-intensity training., (© 2023. The Author(s).)

Objectives: To assess the associations of biomarkers in serum [highsensitivity C-reactive protein (hs-CRP), serum cartilage oligomeric protein (sCOMP), serum propeptide of type I procollagen (sPINP) and serum osteocalcin (sOC)] and urine [urinary type II collagen telopeptide (uCTX-2)] with the extent and progression of nocturnal pain, pain while walking, and fatigue in participants with hip and/or knee pain suspected to be early stage osteoarthritis (OA)., Methods: hs-CRP, uCTX-2, sCOMP, sPINP and sOC were measured at baseline in 1,002 participants of the Cohort Hip and Cohort Knee (CHECK). Nocturnal pain, pain while walking and fatigue were assessed by self-reported questionnaires at baseline and 2-year follow-up. Associations between these biomarkers and symptoms were examined using logistic and linear regression analyses., Results: hs-CRP was significantly associated with mild nocturnal pain (OR 1.18 95% CI 1.01-1.37), with mild and moderate pain while walking (OR 1.17 95% CI 1.01-1.35 and OR 1.56 95% CI 1.29-1.90, respectively) and with progression of nocturnal pain (OR 1.25 95% CI 1.07-1.46). uCTX-2 was associated with mild nocturnal pain (OR 1.40 95% CI 1.05-1.85) and with mild and severe-extreme pain while walking (OR 1.35 95% CI 1.04-1.75 and OR 2.55 95% CI 1.03-6.34, respectively). sPINP was associated with severe-extreme nocturnal pain (OR 0.45 95% CI 0.25-0.82). No significant associations were found for sCOMP and sOC, nor for any of the biomarkers and fatigue., Conclusion: This study of biomarkers in a large cohort of participants with hip and/or knee pain suspected to reflect early stage hip and/or knee OA suggests that inflammation and cartilage matrix degeneration play a role in pain, but not in fatigue., (Copyright © 2022 The Author(s). Published by Elsevier Ltd.. All rights reserved.)