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The systemic associations with knee osteoarthritis (KOA) are incompletely understood. This study explores aortic disease, musculoskeletal and organ findings in patients with KOA in relation to their symptoms or radiographic abnormalities. Full body computed tomography (CT) scans of 255 IMI-APPROACH participants were investigated using an automated analysis of multislice CT (Voronoi Health Analytics) that extracts aortic size and calcifications, and volumes and densities of bones, muscles, fat compartments and thoracic and abdominal organs. The CT measurements were primarily related to KOA as measured with Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), visual scores and automated knee radiograph analysis of osteophytes, bone sclerosis and joint space width. The median age was 67 years, body mass index (BMI) 26.8 kg/m 2 and 78% were female. About half had Kellgren-Lawrence grade ≥ 2. Larger knee osteophyte area was associated with a larger aortic volume (R Spearman =0.21,P = 0.001), which can be due to elongation or dilatation. We observed an association between more symptoms and increased psoas (R Spearman =-0.23,P < 0.001) and lower leg (R Spearman =-0.23,P < 0.001) muscle density, suggesting less microscopic muscle fat. Symptomatic KOA was associated with substantially lower lung volume (771 ml difference between 50% worst and 50% best WOMAC), but not with visible lung disease. Lung volume and density were significantly associated with the physical functioning WOMAC component. These associations remained significant after adjustment for age, sex and BMI. KOA is associated with significant systemic changes, including altered aortic and organ volumes. These correlations suggest that KOA's impact may extend beyond the joints. Future research should explore the causal relationships and therapeutic implications associations., Competing Interests: Declarations. Ethical approval: The study was approved by the regional ethics committees and Institutional Review Boards. Informed consent: Informed consent was taken from all individual participants. Disclaimer: This manuscript has not been previously archived. No part of this manuscript, including text and graphics, is copied or published elsewhere in whole or in part. Generative AI and AI-assisted technologies were not used in the preparation of this work. Note on congress abstracts and publication: This work was not previously presented and/or submitted as conference abstract. Conflict of interest: PdJ; The department of Radiology of the UMC Utrecht receives research support from Philips Healthcare, outside of the submitted work. For the present study software was provided in kind by Voronoi Health Analytics. WF: research grants from NovoNordisk and Pfizer (payments to the institution), and consultancy activities for Pfizer, all outside the scope of the submitted work. MK: consulting fees from Pfizer, CHDR, Novartis, GSK, all paid to institution. Lecture fee from Novartis. Royalties from Wolters Kluwer and Springer Verlag, paid to institution. FJB: funding from Gedeon Richter Plc., Bristol-Myers Squibb International Corporation (BMSIC), Sun Pharma Global FZE, Celgene Corporation, Janssen Cilag International N.V, Janssen Research & Development, Viela Bio, Inc., Astrazeneca AB, UCB BIOSCIENCES GMBH, UCB BIOPHARMA SPRL, AbbVie Deutschland GmbH & Co.KG, Merck KGaA, Amgen, Inc., Novartis Farmacéutica, S.A., Boehringer Ingelheim España, S.A, CSL Behring, LLC, Glaxosmithkline Research & Development Limited, Pfizer Inc, Lilly S.A., Corbus Pharmaceuticals Inc., Biohope Scientific Solutions for Human Health S.L., Centrexion Therapeutics Corp., Sanofi, TEDEC-MEIJI FARMA S.A., KiniksaPharmaceuticals, Ltd. Grunenthal. IKH: Research grant (ADVANCE) from Pfizer (payment to institution) and consulting fees from Novartis, Grünenthal and GSK, outside of the submitted work. FB: Institutional grants from TRB Chemedica. Consulting fees from AstraZeneca, Grunenthal, GSK, Novartis, 4P Pharma. Honoraria for lectures from Pfizer. Travel support from Nordic Pharma. Stock owner of 4Moving Biotech. MFB: developed the software through Voronoi Health Analytics, Inc. that was used for this study. KP: developed the software through Voronoi Health Analytics, Inc. that was used for this study. NIH: no disclosures to report. EB: no disclosures to report SB: no disclosures to report SCM: no disclosures to report ADM: no disclosures to report MV: no disclosures to report MPJ: no disclosures to report., (© 2025. The Author(s).)

Background: Cognitive failure is associated with memory and concentration problems. Previously, a prevalence of one third was found in a general sarcoidosis population. The aim of this study was to assess if neurosarcoidosis patients are at higher risk for developing everyday cognitive failure using the Cognitive Failure Questionnaire (CFQ) and to determine what factors were associated with cognitive failure., Methods: A cross-sectional web-based survey was conducted from April to May 2017 in a national sample of neurosarcoidosis patients. The survey asked about complaints and included 3 questionnaires (Fatigue Assessment Scale [FAS], Small Fiber Neuropathy Screening List [SFNSL] and CFQ. Data were compared to a general sarcoidosis population., Results: Of the 152 patients who completed the survey, 131 had neurosarcoidosis. The mean CFQ score was significantly higher in the neurosarcoidosis (45.6±20.7) compared to the general sarcoidosis population (36.2±15.9; p< 0.0001). High CFQ scores (≥43) were found in 55.7% and 33.9%, respectively (p<0.0001). The FAS score (OR 21.4) and SFNSL score (OR 4.3) were the strongest positive predictors of a high CFQ score., Conclusion: Cognitive failure is a significant problem in neurosarcoidosis. More than half of the patients reported cognitive deficits, compared to one third of a general sarcoidosis population. Fatigue and small fiber neuropathy play a role in cognitive failure., (Copyright: © 2019.)

Background: Previous studies found that 40-60% of the sarcoidosis patients suffer from small fiber neuropathy (SFN), substantially affecting quality of life. SFN is difficult to diagnose, as a gold standard is still lacking. The need for an easily administered screening instrument to identify sarcoidosis-associated SFN symptoms led to the development of the SFN Screening List (SFNSL). The usefulness of any questionnaire in clinical management and research trials depends on its interpretability. Obtaining a clinically relevant change score on a questionnaire requires that the smallest detectable change (SDC) and minimal important difference (MID) are known. Objectives: The aim of this study was to determine the SDC and MID for the SFNSL in patients with sarcoidosis. Methods : Patients with neurosarcoidosis and/or sarcoidosis-associated SFN symptoms (N=138) included in the online Dutch Neurosarcoidosis Registry participated in a prospective, longitudinal study. Anchor-based and distribution-based methods were used to estimate the MID and SDC, respectively. Results: The SFNSL was completed both at baseline and at 6-months' follow-up by 89/138 patients. A marginal ROC curve (0.6) indicated cut-off values of 3.5 points, with 73% sensitivity and 49% specificity for change. The SDC was 11.8 points. Conclusions: The MID on the SFNSL is 3.5 points for a clinically relevant change over a 6-month period. The MID can be used in the follow-up and management of SFN-associated symptoms in patients with sarcoidosis, though with some caution as the SDC was found to be higher. (Sarcoidosis Vasc Diffuse Lung Dis 2018; 35: 333-341) ., (Copyright: © 2018 SARCOIDOSIS VASCULITIS AND DIFFUSE LUNG DISEASES.)