A growing amount of evidence suggests that gut microbiota plays an important role in human health, including a possible role in the pathogenesis of rheumatic and musculoskeletal diseases (RMD). We analysed the current evidence about the role of microbiota in rheumatoid arthritis (RA), spondyloarthritis (SpA), systemic lupus erythematosus (SLE) and systemic sclerosis (SSc). In RA, we found a general consensus regarding a reduction of diversity and a specific bacterial signature, with consistent changes according to the different ethnic and geographical areas. The major pathogenetic role in RA is recognised for P. copri, L. salivarius and Collinsella, even if findings become more heterogeneous when considering established disease. In SpA, we found a relative gut abundance of Akkermansia, Coprococcus, Ruminoccocus and a relative reduction in Bacterioides and Firmicutes spp. Human and preclinical data suggest loss of mucosal barrier, increased permeability and Th1- and Th17-mediated inflammation. Additionally, HLA-B27 seems to play a role in shaping the intestinal microbiota and the consequent inflammation. In SLE, the typical gut microbiota signature was characterised by a reduction in the Firmicutes/Bacteroidetes ratio and by enrichment of Rhodococcus, Eggerthella, Klebsiella, Prevotella, Eubacterium and Flavonifractor, even if their real pathogenic impact remains unclear. In SSc, gastrointestinal dysbiosis is well documented with an increase of pro-inflammatory species (Fusobacterium, Prevotella, Ruminococcus, Akkermansia, γ-Proteobacteria, Erwinia, Trabsulsiella, Bifidobacterium, Lactobacillus, Firmicutes and Actinobacteria) and a reduction of species as Faecalibacterium, Clostridium, Bacteroidetes and Rikenella. In conclusion, seems possible to recognise a distinct gut microbiota profile for each RMD, even if significant differences in bacterial species do exist between different studies and there is a high risk of bias due to the cross-sectional nature of such studies. Therefore longitudinal studies are needed, especially on patients with preclinical and early disease, to investigate the real role of gut microbiota in the pathogenesis of RMD.

Rheumatic and musculoskeletal diseases (RMDs) cause significant burden to the individual and society, requiring lifelong management and specialist healthcare resource use. Costing over 200 billion euros per year in Europe, RMDs are the most expensive of all diseases for European healthcare systems. The incidence and burden of RMDs are projected to rise with the ageing global population and increase in sedentary, obesogenic lifestyles. In parallel, there is a global crisis in the rheumatology workforce, whereby capacity to deliver specialist care is being exceeded by demand. Pervasive, scalable mobile health technologies, such as apps, are being developed to support the self-management of RMDs and reduce pressure on healthcare services. However, it is unknown whether these apps are informed by theory or their use supported by an appropriate evidence base. The purpose of this review is therefore to provide a comprehensive overview of the development strategies, interventional components and theoretical underpinnings of existing smartphone apps, designed to support the self-management of RMDs.
Searches will be conducted within PubMed, Scopus, Web of Science, Embase, MEDLINE and PsycINFO. Reference lists and citing articles of the included studies will be searched. Identified publications will be screened for eligibility by two independent reviewers. Any discrepancies between reviewers will be resolved by consensus, with input from a third reviewer if required. Data will be extracted on study designs, methods, populations, setting, utilised theoretical frameworks, intervention components, behaviour change techniques, methods to evaluate effectiveness and barriers/facilitators to intervention engagement. Exploratory outcomes include reported effectiveness, acceptability and usability. A systematic, narrative synthesis of evidence will be presented. If appropriate (depending on quality and pool of evidence identified), qualitative meta-summary techniques will be used to combine and summarise qualitative findings regarding barriers/facilitators to intervention engagement.
The results of this systematic literature review will provide insights for healthcare professionals, researchers, app designers and policy makers, to inform future development and implementation of smartphone apps to support self-management of RMDs. Evidence gaps for future research will be identified. Findings will be disseminated through a final manuscript/publication of results and via a conference abstract, patient organisations and social media.
PROSPERO CRD42022359704.

The major and upward trend in the number of published research related to rheumatic and musculoskeletal diseases, in which artificial intelligence plays a key role, has exhibited the interest of rheumatology researchers in using these techniques to answer their research questions. In this review, we analyse the original research articles that combine both worlds in a five- year period (2017-2021). In contrast to other published papers on the same topic, we first studied the review and recommendation articles that were published during that period, including up to October 2022, as well as the publication trends. Secondly, we review the published research articles and classify them into one of the following categories: disease identification and prediction, disease classification, patient stratification and disease subtype identification, disease progression and activity, treatment response, and predictors of outcomes. Thirdly, we provide a table with illustrative studies in which artificial intelligence techniques have played a central role in more than twenty rheumatic and musculoskeletal diseases. Finally, the findings of the research articles, in terms of disease and/or data science techniques employed, are highlighted in a discussion. Therefore, the present review aims to characterise how researchers are applying data science techniques in the rheumatology medical field. The most immediate conclusions that can be drawn from this work are: multiple and novel data science techniques have been used in a wide range of rheumatic and musculoskeletal diseases including rare diseases; the sample size and the data type used are heterogeneous, and new technical approaches are expected to arrive in the short-middle term.

Investigating unmet needs and identifying the necessary interventions for patients affected by rheumatic and musculoskeletal diseases (RMDs) may help significantly to ensure the continuity and quality of the chronic care pathway. To this aim, the contribution of rheumatology nurses requires further evidence. The aim of our systematic literature review (SLR) was to identify the nursing interventions directed towards patients with RMDs undergoing biological therapy. To retrieve data, a search was carried out in the MEDLINE database, the Cumulative Index to Nursing and Allied Health Literature (CINAHL database), the APA PsycINFO database and the Excerpta Medica Database (EMBASE) from 1990 to 2022. The systematic review was carried out in accordance with the relevant PRISMA guidelines. Inclusion criteria were as follows: (I) adult patients with RMDs, (II) undergoing therapy with Biological Disease-Modifying Anti-Rheumatic Drugs (bDMARDs), (III) original and quantitative research papers in English with available abstract, (IV) specific to nursing interventions and/or outcomes. Two independent reviewers screened the identified records for eligibility according to their title and abstract, full texts were subsequently assessed and, finally, data was extracted. Critical Appraisal Skills Programme (CASP) tools were used to evaluate the quality of the studies included. Among the 2348 records retrieved, 13 articles met the inclusion criteria. These consisted of six randomised controlled trials (RCTs), one pilot study and six observational studies on RMDs. In a total population of 2004 patients, 43% (862/2004) of the cases concerned rheumatoid arthritis (RA) and 56% (1122/2004) of the cases concerned spondyloarthritis (SpA). Three major nursing interventions were identified, namely education, patient-centred care and data collection/nurse monitoring, which were correlated with high satisfaction rates regarding care, increased self-care capacity and treatment adherence among patients. All interventions followed a protocol defined in collaboration with rheumatologists. The large degree of heterogeneity in the interventions did not allow the performance of a meta-analysis. Rheumatology nurses are part of a multidisciplinary team caring for patients with RMDs. Following an accurate initial nursing evaluation, rheumatology nurses can plan and standardise their interventions focusing primarily on patient education and personalised care based on actual needs, such as psychological well-being and disease control. However, the training for rheumatology nurses should define and standardise, as much as possible, the competencies required for the detection of disease parameters. Key Points • This SLR provides an overview of nursing interventions for patients with RMDs. • This SLR considers the specific population of patients on biological therapies. • Training for rheumatology nurses should standardise, as much as possible, the knowledge and methods required for detecting disease parameters. • This SLR highlights the various competencies of rheumatology nurses.