The reported prevalence of coeliac disease (CD) in patients with rheumatoid arthritis (RA) and juvenile idiopathic arthritis (JIA) varies in previous studies. We aimed to examine the prevalence of CD in patients with RA and JIA.
We searched Medline, Embase, Cochrane and Web of Science Core Collection between 1 January 1990 and 31 October 2022. In our primary analysis, the prevalence of biopsy-confirmed CD in RA and JIA patients was investigated. In secondary analyses, the prevalence of serological markers for CD was examined. Pooled weighted prevalences of CD and serological markers with 95% confidence intervals (95%CI) were calculated and quality of included studies was assessed. Meta-regression analysis was performed on publication year, sample size, CD prevalence in the general population, proportion of females, and quality assessment score.
In this systematic review, 14 publications were deemed relevant for RA and 22 for JIA, with nine and 18 included in the primary analyses of CD prevalence, respectively. Among a total of 754 RA patients and 2077 patients with JIA, the weighted pooled prevalence estimates of biopsy-confirmed CD were 0.4% (95%CI=0.0-1.2) and 1.4% (95%CI=0.7-2.2), respectively. The pooled prevalence estimates of positive CD serology were 0.9% (95%CI=0.3-1.9) in RA and 5.4% (95%CI=2.5-9.2) in JIA.
In this meta-analysis, we found a pooled prevalence of biopsy-confirmed CD in patients with RA and JIA comparable to that in the general population. Routine screening for CD is not warranted in RA but could be considered in JIA patients with additional risk factors for CD.

Prevalence of coeliac disease in patients with rheumatoid arthritis and juvenile idiopathic arthritis: a systematic review and meta-analysis.

To evaluate efficacy and safety of total glucosides of paeony in the treatment of 5 types of inflammatory arthritis METHODS: Databases such as Pubmed, Cochran Library, Embase were searched to collect RCTs about TGP in the treatment of inflammatory arthritis. Then, the RCTs were assessed for risk of bias and RCT data were extracted. Finally, RevMan 5.4 was used for the meta-analysis.
A total of 63 RCTs were finally included, involving 5293 participants and 5 types of types of inflammatory arthritis: rheumatoid arthritis (RA), ankylosing spondylitis (AS), osteoarthritis (OA), juvenile idiopathic arthritis (JIA), psoriatic arthritis. For AS, TGP may improve AS disease activity score (ASDAS), decrease erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), tumor necrosis factor (TNF)- α and interleukin (IL)- 6; for RA, TGP may improve disease activity of 28 joints (DAS28), decrease ESR, CRP, rheumatoid factor (RF), TNF-α and IL-6; for psoriatic arthritis, TGP may improve psoriasis area and severity index (PASI) and decrease ESR; for OA, TGP may improve visual analogue scale (VAS) and decrease nitric oxide (NO); for JIA, TGP may increase total efficiency rate, decrease ESR, CRP and TNF-α. For safety, RCTs showed that the addition of TGP did not increase adverse events, and may even reduce adverse events.
TGP may improve symptoms and inflammation levels in patients with inflammatory arthritis. However, due to the low quality and small number of RCTs, large-sample, multi-center clinical trials are still needed for revision or validation.

Efficacy and safety of total glucosides of paeony in the treatment of 5 types of inflammatory arthritis: A systematic review and meta-analysis.

To evaluate the effectiveness of Janus kinase (JAK) inhibitors for the treatment of patients with autoimmune disease and associated inflammatory ocular diseases.
We identified relevant literature by screening the MEDLINE, PubMed, and Cochrane databases for randomized controlled trials, cohort studies, case controls, and case reports.
Seven studies, including 11 patients, were included in the final systematic analysis. Of the 11 patients, there were 5 cases of juvenile idiopathic arthritis- (JIA-) associated uveitis, 1 case of rheumatoid arthritis- (RA-) associated keratitis, 1 case of RA-associated scleritis, 1 case of psoriasis-associated conjunctivitis, 2 cases of noninfectious scleritis, and 1 case of uveitis with suspected autoimmune disease. None of these 11 patients responded adequately to conventional treatments, including biological agents; these were all refractory cases and switched to JAK inhibitor therapy. Irrespective of whether they were suffering from uveitis, scleritis, or other types of ocular inflammation, all 11 patients showed an improvement to JAK inhibitors without significant side effects. Different types of JAK inhibitors might be associated with different responses when used to treat ocular inflammation.
JAK inhibitors may represent an alternative treatment option for patients with autoimmune ocular inflammation.

Role of Janus Kinase (JAK) Inhibitor in Autoimmune Ocular Inflammation: A Systematic Review.

The variations in outcome and frequent occurrence of kidney allograft failure continue to pose important clinical and research challenges despite recent advances in kidney transplantation. The aim of this systematic review was to examine the current application of machine learning models in kidney transplantation and perform a meta-analysis of these models in the prediction of graft survival.
This review was registered with the PROSPERO database (CRD42021247469) and all peer-reviewed original articles that reported machine learning model-based prediction of graft survival were included. Quality assessment was performed by the criteria defined by Qiao and risk-of-bias assessment was performed using the PROBAST tool. The diagnostic performance of the meta-analysis was assessed by a meta-analysis of the area under the receiver operating characteristic curve and a hierarchical summary receiver operating characteristic plot.
A total of 31 studies met the inclusion criteria for the review and 27 studies were included in the meta-analysis. Twenty-nine different machine learning models were used to predict graft survival in the included studies. Nine studies compared the predictive performance of machine learning models with traditional regression methods. Five studies had a high risk of bias and three studies had an unclear risk of bias. The area under the hierarchical summary receiver operating characteristic curve was 0.82 and the summary sensitivity and specificity of machine learning-based models were 0.81 (95 per cent c.i. 0.76 to 0.86) and 0.81 (95 per cent c.i. 0.74 to 0.86) respectively for the overall model. The diagnostic odds ratio for the overall model was 18.24 (95 per cent c.i. 11.00 to 30.16) and 29.27 (95 per cent c.i. 13.22 to 44.46) based on the sensitivity analyses.
Prediction models using machine learning methods may improve the prediction of outcomes after kidney transplantation by the integration of the vast amounts of non-linear data.

Papers