BackgroundLow muscle mass occurs in patients with rheumatoid arthritis without weight loss; this condition is referred as rheumatoid cachexia. The aim of the current study was to perform a systematic review with meta‐analysis to determine the rheumatoid cachexia prevalence.MethodsA systematic review with meta‐analysis of observational studies published in English, between 1994 and 2016, was conducted using MEDLINE (via PubMed) and other relevant sources. Search strategies were based on pre‐defined keywords and medical subject headings. The methodological quality of included studies was assessed using the Newcastle‐Ottawa Scale. Meta‐analysis was used to estimate the prevalence, and because studies reported different methods and criteria to estimate body composition and prevalence of rheumatoid cachexia, subgroup analyses were performed. Meta‐regression adjusted for the 28‐joint disease activity score and disease duration (years) was performed (significance level at P ≤ 0.05).ResultsOf 136 full articles (one duplicate publication) screened for inclusion in the study, eight were included. The estimated overall prevalence of rheumatoid cachexia was 19% [95% confidence interval (CI) 07–33%]. This prevalence was 29% (95% CI 15–46%) when body composition was measured by dual‐energy X‐ray absorptiometry. When the diagnostic criteria were fat‐free mass index below the 10th percentile and fat mass index above the 25th percentile, rheumatoid cachexia prevalence was 32% (95% CI 14–52%). The 28‐joint disease activity score and disease duration had no influence on the estimated prevalence of rheumatoid cachexia (P > 0.05). Most studies were rated as having moderate methodological quality.ConclusionsMeta‐analysis showed a prevalence of rheumatoid cachexia of 15‐32%, according to different criteria, demonstrating that this condition is a frequent comorbidity of rheumatoid arthritis. To better understand its clinical impact, more studies using standardized definitions and prospective evaluations are urgently needed.

BackgroundRheumatoid arthritis is characterized by chronic polyarticular synovitis and presents systemic changes that impact quality of life, such as impaired muscle function, seen in up to 66% of the patients. This can progress to severely debilitating state known as rheumatoid cachexia—without loss of fat mass and body weight—for which there is little consensus in terms of diagnosis or treatment. This study aims to evaluate whether the collagen‐induced arthritis (CIA) animal model also develops clinical and functional features characteristic of rheumatoid cachexia.MethodsMale DBA1/J mice were randomly divided into 2 groups: healthy animals (CO, n = 11) and CIA animals (n = 13). The clinical score and edema size, animal weight and food intake, free exploratory locomotion, grip strength, and endurance exercise performance were tested 0, 18, 35, 45, 55, and 65 days after disease induction. After euthanasia, several organs, visceral and brown fat, and muscles were dissected and weighed. Muscles were used to assess myofiber diameter. Ankle joint was used to assess arthritis severity by histological score. Statistical analysis were performed using one‐way and two‐way analyses of variance followed by Tukey's and Bonferroni's test or t‐test of Pearson and statistical difference were assumed for a P value under 0.05.ResultsThe CIA had significantly higher arthritis scores and larger hind paw edema volumes than CO. The CIA had decreased endurance exercise performance total time (fatigue; 23, 22, 24, and 21% at 35, 45, 55, and 65 days, respectively), grip strength (27, 55, 63, 60, and 66% at 25, 35, 45, 55, and 65 days, respectively), free locomotion (43, 57, 59, and 66% at 35, 45, 55, and 65 days, respectively), and tibialis anterior and gastrocnemius muscle weight (25 and 24%, respectively) compared with CO. Sarcoplasmic ratios were also reduced in CIA (TA: 23 and GA: 22% less sarcoplasmic ratio), confirming the atrophy of skeletal muscle mass in these animals than in CO. Myofiber diameter was also reduced 45% in TA and 41% in GA in CIA when compared with the CO. Visceral and brown fat were lighter in CIA (54 and 39%, respectively) than CO group.ConclusionsThe CIA model is a valid experimental model for rheumatoid cachexia given that the clinical changes observed were similar to those described in patients with rheumatoid arthritis.

Introduction In view of the method of diagnosing sarcopenia being complex and considered to be difficult to introduce into routine practice, the European Working Group on Sarcopenia in Older People (EWGSOP) recommends the use of the SARC-F questionnaire as a way to introduce assessment and treatment of sarcopenia into clinical practice. Only recently, some studies have turned their attention to the presence of sarcopenia in systemic sclerosis (SSc).There is no data about performance of SARC-F and other screening tests for sarcopenia in this population. Objective To compare the accuracy of SARC-F, SARC-CalF, SARC-F+EBM, and Ishii test as screening tools for sarcopenia in patients with SSc. Methods Cross-sectional study of 94 patients with SSc assessed by clinical and physical evaluation. Sarcopenia was defined according to the revised 2019 EWGSOP diagnostic criteria (EWGSOP2) with assessments of dual-energy X-ray absorptiometry, handgrip strength, and short physical performance battery (SPPB). As case finding tools, SARC-F, SARC-CalF, SARC-F+EBM and Ishii test were applied, including data on calf circumference, body mass index, limitations in strength, walking ability, rising from a chair, stair climbing, and self reported number of falls in the last year. The screening tests were evaluated through receiver operating characteristic (ROC) curves. Standard measures of diagnostic accuracy were computed using the EWGSOP2 criteria as the gold standard for diagnosis of sarcopenia. Results Sarcopenia was identified in 15 (15.9%) patients with SSc by the EWGSOP2 criteria. Area under the ROC curve of SARC-F screening for sarcopenia was 0.588 (95% confidence interval (CI) 0.420–0.756, p = 0.283). The results of sensitivity, specificity, positive likelihood ratio (+LR), negative likelihood ratio (-LR) and diagnostic Odds Ratio (DOR) with the EWGSOP2 criteria as the gold standard were 40.0% (95% CI, 19.8–64.2), 81.0% (95% CI, 71.0–88.1), 2.11 (95% CI, 0.98–4.55), 0.74 (95% CI, 0.48–1.13) and 2.84 (95% CI, 0.88–9.22), respectively. SARC-CalF and SARC-F+EBM showed better sensitivity (53.3%, 95% CI 30.1–75.2 and 60.0%, 95% CI 35.7–80.2, respectively) and specificity (84.8%, 95% CI 75.3–91.1 and 86.1%, 95% CI 76.8–92.0, respectively) compared with SARC-F. The best sensitivity was obtained with the Ishii test (86.7%, 95% CI 62.1–96.3), at the expense of a small loss of specificity (73.4%, 95% CI 62.7–81.9). Comparing the ROC curves, SARC-F performed worse than SARC-CalF, SARC-F+EBM and Ishii test as a sarcopenia screening tool in this population (AUCs 0.588 vs. 0.718, 0.832, and 0.862, respectively). Direct comparisons between tests revealed differences only between SARC-F and Ishii test for sensitivity (p = 0.013) and AUC (p = 0.031). Conclusion SARC-CalF, SARC-F+EBM, and Ishii test performed better than SARC-F alone as screening tools for sarcopenia in patients with SSc. Considering diagnostic accuracy and feasibility aspects, SARC-F+EBM seems to be the most suitable screening tool to be adopted in routine care of patients with SSc.

Introduction Rheumatoid arthritis(RA) and osteoarthritis(OA) patients showed systemic manifestations that may lead to a reduction in muscle strength, muscle mass and, consequently, to a reduction in functionality. On the other hand, moderate intensity resistance training(MIRT) and high intensity resistance training(HIRT) are able to improve muscle strength and muscle mass in RA and OA without affecting the disease course. However, due to the articular manifestations caused by these diseases, these patients may present intolerance to MIRT or HIRT. Thus, the low intensity resistance training combined with blood flow restriction(LIRTBFR) may be a new training strategy for these populations. Objective To perform a systematic review with meta-analysis to verify the effects of LIRTBFR on muscle strength, muscle mass and functionality in RA and OA patients. Materials and methods A systematic review with meta-analysis of randomized clinical trials(RCTs), published in English, between 1957–2021, was conducted using MEDLINE(PubMed), Embase and Cochrane Library. The methodological quality was assessed using Physiotherapy Evidence Database scale. The risk of bias was assessed using RoB2.0. Mean difference(MD) or standardized mean difference(SMD) and 95% confidence intervals(CI) were pooled using a random-effects model. A P<0.05 was considered statistically significant. Results Five RCTs were included. We found no significant differences in the effects between LIRTBFR, MIRT and HIRT on muscle strength, which was assessed by tests of quadriceps strength(SMD = -0.01[-0.57, 0.54], P = 0.96; I² = 58%) and functionality measured by tests with patterns similar to walking(SMD = -0.04[-0.39, 0.31], P = 0.82; I² = 0%). Compared to HIRT, muscle mass gain after LIRTBFR was reported to be similar. When comparing LIRTBFR with low intensity resistance training without blood flow restriction(LIRT), the effect LIRTBFR was reported to be higher on muscle strength, which was evaluated by the knee extension test. Conclusion LIRTBFR appears to be a promising strategy for gains in muscle strength, muscle mass and functionality in a predominant sample of RA and OA women.

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To assess electromyographic parameters of neuromuscular fatigue in knee extensors and their association with clinical, functional and emotional features in patients with rheumatoid arthritis (RA). Thirty-eight female patients with RA participated. Electromyography parameters (changes in signal amplitude, represented by the root mean square, and frequency content, represented by median frequency-MDF) were assessed during a submaximal (60%) isometric contraction of the knee extensors, sustained for 60 s. Clinical characteristics; the 28-joint Disease Activity Score (DAS-28) in which includes count of swollen joints (out of the 28) and tender joints (out of the 28), the erythrocyte sedimentation rate and global disease activity measured on a visual analogue scale; serum C reactive protein (CRP); information on treatment; the Health Assessment Questionnaire; the Functional Assessment of Chronic Illness Therapy fatigue scale (FACIT-F); the Short Form Health Survey (SF-36) and the International Physical Activity Questionnaire (IPAQ), were also assessed. The mean patient age was 51.0 ± 8.2 years, mean disease activity score was 11.5 ± 7.1, and mean CRP level was 8.0 ± 7.8 mg/dL. There was a moderate correlation between MDF and age (r = 0.5), as well as weak correlations of MDF with FACIT-F (r = 0.3), physical functioning (r = - 0.3) and vitality domains (r = - 0.3) of the SF-36, and IPAQ (r = - 0.3) (p ≤ 0.05 for all). No association was observed between electromyography measurements and clinical or treatment features. The electromyographic parameter MDF was correlated with perception of fatigue, age, physical functioning and vitality domains of SF-36, and physical activity level in this sample. These results indicate that primary muscle factors should also be considered when managing perceived fatigue in patients with RA.

BackgroundRheumatoid arthritis (RA) patients have loss of muscle mass. The balance between muscle protein synthesis and degradation is regulated by cytokines and growth factors, named myokines, such as irisin and myostatin. Myokines are mainly expressed by skeletal muscle and exert systemic effects promoting crosstalk among different tissues. Irisin increases cortical bone mass and its low levels are related to muscle atrophy and obesity[,1, 2 while myostatin is a negative regulator of muscle growth and regeneration and has a direct role in osteoclastogenesis of inflammatory bone destruction[.3, 4 ObjectivesTo evaluate serum levels of irisin and myostatin and body composition of RA patients and controls.Methods122 female patients with RA, mean age 53 years, mean disease activity score (DAS28) 4.09, mean disease duration 11.2 years and mean body mass index 27.33 kg/m2 were included. 69 age and sex-matched healthy subjects were enrolled as control group. Irisin (Phoenix Pharmaceuticals) and myostatin (R and D Systems) serum levels were evaluated by ELISA. Fat mass index (FMI;Kg/m2) and appendicular lean mass index (ALMI;Kg/m2) were assessed by total body dual-energy x-ray absorptiometry. Student’s t test and Spearman correlation were performed. Significance was set at p<0.05.Table 1Irisin and myostatin serum levels of RA patients and controlsnIrisin (mean±SD)Myostatin (mean±SD) RA patients treated with biologics1331,71±7,69#2448,64±1114,90*#RA patients non-treated with biologics2725,93±6,893261,66±1156,28+Controls3030,36±10,954049,08±1610,01*p<0,05 RA patients treated with biologics vs controls; #p<0,05 RA patients treated with biologics vs RA patients non-treated with biologics;+p<0,05 RA patients non-treated with biologics vs controls.ResultsRA patients had decreased serum levels of irisin (25,61±8,25 vs 30,36±10,95 ng/ml; p<0.05) and myostatin (3011,28±1271,11 vs 4049,08±1610,01 pg/ml; p<0.05), decreased ALMI (6,09±0,88 vs 6,50±1,10; p<0.05) and increased FMI (11,26±3,30 vs 9,44±2,65; p<0.05), compared to controls. No correlations were observed among irisin and myostatin levels and ALMI and FMI. Of the 122 RA patients, 40 were analysed for the use of biologic medication. Serum levels of irisin and myostatin were different between RA patients treated and non-treated with biologics (table 1).ConclusionsRA patients presented loss of lean mass and gain of fat mass, as well as lower irisin and myostatin serum levels, in comparison with controls. Additionally, the use of biologic medication by patients impacted on myokines serum levels. Further analyses are needed for a better comprehension of irisin and myostatin roles in RA, and to verify their correlation to other RA features.References[1] Colaianni G, et al. Proc Natl Acad Sci2015;112(39):12157–62.[2] Chang J, et al. Geriatr Gerontol Int. 2017;17(11):2266–2273.[3] Huang Z, et al. Cell Signal2011;23(9):1441–6.[4] Dankbar B, et al. Nat Med2015;21(9):1085–90.Disclosure of InterestNone declared

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