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Abstract Background In light of the aging population, increasingly suffering from the metabolic syndrome (MS), strategies need to be developed to address global public health challenges known to be associated with MS such as arthritis. As physical activity (PA) may play a crucial role in tackling those challenges, this study aimed to determine the association between the number of MS risk factors, PA and arthritis in people ≥ 50 years old. Methods Data from the Survey of Health, Ageing, and Retirement in Europe (SHARE) were used to estimate the prevalence of arthritis and MS risk factors in the European population ≥ 50 years and to evaluate the associations between MS risk factors, PA and arthritis. Binary logistic regression was performed to calculate the odds ratio of different factors. Results 73,125 participants were included in the analysis. 55.75% of patients stated at least one of the three MS risk factors. The prevalence of rheumatoid arthritis (RA) and osteoarthritis (OA)/other rheumatism among ≥ 50 years population was 10.19% and 19.32% respectively. Females showed a higher prevalence of arthritis than males. Prevalence did not differ between groups with different levels of PA. Arthritis prevalence was positively correlated with the number of MS risk factors (P 0.05). Conclusion Middle-aged and older Europeans with multiple comorbidities suffered from RA, OA or other rheumatism more frequently than participants with fewer comorbidities, while the level of physical activity was not associated with the number of metabolic risk factors in patients with RA and OA/other rheumatism.

Inertial measurement units (IMUs) have proven to be valuable tools in measuring the range of motion (RoM) of human upper limb joints. Although several studies have reported on the validity of IMUs compared to the gold standard (optical motion capture system, OMC), a quantitative summary of the accuracy of IMUs in measuring RoM of upper limb joints is still lacking. Thus, the primary objective of this systematic review and meta-analysis was to determine the concurrent validity of IMUs for measuring RoM of the upper extremity in adults. Fifty-one articles were included in the systematic review, and data from 16 were pooled for meta-analysis. Concurrent validity is excellent for shoulder flexion–extension (Pearson’s r = 0.969 [0.935, 0.986], ICC = 0.935 [0.749, 0.984], mean difference = −3.19 (p = 0.55)), elbow flexion–extension (Pearson’s r = 0.954 [0.929, 0.970], ICC = 0.929 [0.814, 0.974], mean difference = 10.61 (p = 0.36)), wrist flexion–extension (Pearson’s r = 0.974 [0.945, 0.988], mean difference = −4.20 (p = 0.58)), good to excellent for shoulder abduction–adduction (Pearson’s r = 0.919 [0.848, 0.957], ICC = 0.840 [0.430, 0.963], mean difference = −7.10 (p = 0.50)), and elbow pronation–supination (Pearson’s r = 0.966 [0.939, 0.981], ICC = 0.821 [0.696, 0.900]). There are some inconsistent results for shoulder internal–external rotation (Pearson’s r = 0.939 [0.894, 0.965], mean difference = −9.13 (p

Abstract To determine the current evidence on artificial neural network (ANN) in prognostic studies of musculoskeletal diseases (MSD) and to assess the accuracy of ANN in predicting the prognosis of patients with MSD. The scoping review was reported under the Preferred Items for Systematic Reviews and the Meta-Analyses extension for Scope Reviews (PRISMA-ScR). Cochrane Library, Embase, Pubmed, and Web of science core collection were searched from inception to January 2023. Studies were eligible if they used ANN to make predictions about MSD prognosis. Variables, model prediction accuracy, and disease type used in the ANN model were extracted and charted, then presented as a table along with narrative synthesis. Eighteen Studies were included in this scoping review, with 16 different types of musculoskeletal diseases. The accuracy of the ANN model predictions ranged from 0.542 to 0.947. ANN models were more accurate compared to traditional logistic regression models. This scoping review suggests that ANN can predict the prognosis of musculoskeletal diseases, which has the potential to be applied to different types of MSD.

Abstract Background Ankle joint functional assessment tool (AJFAT) is gradually becoming a popular tool for diagnosing functional ankle instability (FAI). However, due to the lack of standard Chinese versions of AJFAT and reliability and validity tests, the use of AJFAT in the Chinese population is limited. This study aimed to translate and cross‐culturally adapt the AJFAT from English into Chinese, and evaluate the reliability and validity of the Chinese version of AJFAT and to investigate its psychometric properties. Methods The translation and cross‐cultural adaptation of AJFAT was performed according to guidelines for cross‐cultural adaptation of self‐report measures. 126 participants with a history of ankle sprain completed the AJFAT‐C twice within 14 days and completed the Cumberland ankle instability tool (CAIT‐C) once. Test–retest reliability, internal consistency, ceiling and floor effects, convergent and structure validity and discriminative ability were investigated. Results The test–retest reliability (ICC = 0.91, 95%CI = 0.87–0.94) and internal consistency (Cronbach's alpha = 0.87) of the AJFAT‐C were excellent. No ceiling or floor effects were detected. A moderate correlation between the AJFAT‐C and the CAIT‐C suggested a moderate convergent validity. The AJFAT‐C had a two‐factor structure: 1. function of the unstable side of the ankle joint (9 items) and 2. symptoms of the unstable side of the ankle (2 items). The ideal cut‐off point of the AJFAT‐C was calculated as 26 points. Conclusion The Chinese version of AJFAT can be considered as a valid and reliable ankle joint function evaluation tool that can be applied in clinical and research work.