Intranasal antihistamines and corticosteroids are some of the most frequently used drug classes in the treatment of allergic rhinitis. However, there is uncertainty as to whether effectiveness differences may exist among different intranasal specific medications. This systematic review aims to analyse and synthesise all evidence from randomised controlled trials (RCTs) on the effectiveness of intranasal antihistamines and corticosteroids in rhinitis nasal and ocular symptoms and in rhinoconjunctivitis-related quality-of-life.

We will search four electronic bibliographic databases and three clinical trials databases for RCTs (1) assessing patients ≥12 years old with seasonal or perennial allergic rhinitis and (2) comparing the use of intranasal antihistamines or corticosteroids versus placebo. Assessed outcomes will include the Total Nasal Symptom Score (TNSS), the Total Ocular Symptom Score (TOSS) and the Rhinoconjunctivitis Quality-of-Life Questionnaire (RQLQ). We will assess the methodological quality of included primary studies by using the Cochrane risk-of-bias tool. Certainty in the body of evidence for the analysed outcomes will be assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. We will perform a random-effects meta-analysis for each assessed medication and outcome, presenting results as pooled mean differences and standardised mean differences. Heterogeneity will be explored by sensitivity and subgroup analyses, considering (1) the risk of bias, (2) the follow-up period and (3) the drug dose.

Ethical considerations will not be required. Results will be disseminated in a peer-review journal.

CRD42023416573.

Peanut allergies cause serious health problems worldwide. A strong finding has shown that the early introduction of peanuts into the diet of infants at high risk of food allergy reduces the prevalence of peanut allergy. Allergies to peanuts, sesame and tree nuts have been shown to coexist in 60% of cases and vary according to geographical location and dietary habits. Insights into the prevalence of nut and seed allergies in societies with varying consumption levels are essential for developing population-specific weaning guidelines. Understanding the age at which peanut allergy develops is paramount for successful early introduction strategies.

We will perform a cross-sectional study at two tertiary allergy centres in Warsaw and Bydgoszcz. Two hundred forty children aged 4–36 months with eczema or egg allergy will undergo an extensive assessment of their peanut, sesame and tree nut allergy status through skin testing, specific IgE measurements and oral food challenges. The primary outcome is the prevalence of peanut, sesame and tree nut allergies in Polish children at high risk of food allergy. Additionally, the timing of the development of peanut, sesame and tree nut allergies in the first 3 years of life in a high-risk population will be assessed.

The Ethics Committee of the Medical University of Warsaw, Poland approved this protocol (KB/86/2021). The results of this study will be submitted to a peer-reviewed journal no later than 1 year after data collection. The abstract will be presented at relevant national and international conferences.

Although the authors may be able to commit to journal submission no later than 1 year after data collection, publication dates remain beyond their control.

NCT05662800.

Food allergy affects a large population throughout the world. Recently, oral immunotherapy (OIT) has been reported as an effective treatment for severe food allergy. Although OIT was successful in numerous trials in desensitisation, adverse events including anaphylaxis during OIT frequently occur. Additionally, some patients fail to be desensitised after OIT and the response to treatment is often not sustained. As a further adjunctive therapy to facilitate OIT, the role of biological agents has been identified. For example, efficacy and safety of omalizumab as an adjuvant therapy of OIT has become apparent through some RCTs and observational studies. Interest towards this topic is growing worldwide, and ongoing trials will provide additional data on the biologics in food allergy.

We aim to systematically analyse the efficacy and safety of OIT combined with biological agents for food allergy.

This paper provides a protocol for a systematic review of the relevant published analytical studies using an aggregate approach following the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols guidelines. Two authors will perform a comprehensive search for studies on MEDLINE/PubMed, EMBASE and the Cochrane Central Register of Controlled Trials (CENTRAL) databases. Subsequently, two independent authors will perform abstract screening, full-text screening and data extraction. A meta-analysis will be conducted as appropriate.

The protocol of this systematic review will be provided in a peer-reviewed journal. As the researchers will not identify the individual patients included in the studies, they do not need to acquire ethics approval.

CRD42022373015.

Arthritis is thought to be closely related to serum uric acid. The study aims to assess the association between asymptomatic hyperuricemia (AH) and arthritis.

A multistage, stratified cluster was used to conduct a cross-sectional study of adult US civilians aged≥20 years from the 2007–2018 National Health and Nutrition Examination Survey. Participants with hyperuricemia and without hyperuricemia prior to gout were included. A questionnaire was used to determine whether participants had arthritis and the type of arthritis. Logistic regression was used to investigate the association between hyperuricemia and arthritis.

During the past 12 years, the percentage of participants with arthritis changed from 25.95% (22.53%–29.36%) to 25.53% (21.62%–29.44%). The prevalence of osteoarthritis (OA) increased from 8.70% (95% CI: 6.56% to 10.85%) to 12.44% (95% CI: 9.32% to 15.55%), the prevalence of AH changed from 16.35% (95% CI: 14.01% to 18.40%) to 16.39% (95% CI: 13.47% to 19.30%). Participants with AH were associated with onset of arthritis (OR=1.34, 95% CI: 1.07 to 1.69), but the association was muted after adjusting demographic and socioeconomic factors. For participants aged 40–49 years, AH is associated with incident arthritis (OR=1.96, 95% CI: 1.23 to 2.99) and the relationship remained after adjusting for education level, income to poverty ratio, body mass index, diabetes, hypertension and smoking (OR=2.00, 95% CI: 1.94 to 3.36). Compared with male, female participants with AH are more likely to develop arthritis, especially in OA (OR=1.35, 95% CI: 1.14 to 1.60).

Our data identified AH as the risk factor for incident arthritis, especially for OA, which might be exaggerated in aged population and female population.

Several studies have demonstrated that mycophenolate mofetil (MMF) may be an excellent alternative to cyclophosphamide (CYC) or rituximab for the induction of remission in non-life-threatening anti-neutrophil cytoplasmic antibodies associated vasculitis because of its strong immunosuppressive potency and low toxicity profile. Enteric-coated mycophenolate sodium (EC-MPS) was introduced to reduce gastrointestinal adverse reactions of MMF. This study will evaluate the efficacy and safety of EC-MPS combined with glucocorticoid in patients with active and non-life-threatening microscopic polyangiitis (MPA).

This study is a multicentre, open-label, randomised controlled, non-inferiority trial. A total of 110 patients with active and non-life-threatening MPA from 11 hospitals in Shanxi Province of China will be recruited and randomised in a 1:1 ratio to receive either EC-MPS or CYC. All patients will receive the same glucocorticoid plan. We will compare oral EC-MPS (720–1440 mg/day) with intravenous pulsed CYC (7.5–15 mg/kg) administered for 3–6 months. All patients will be switched from their assigned treatment (EC-MPS or CYC) to oral azathioprine (2 mg/kg/day) after remission has been achieved, between 3 and 6 months. Azathioprine will be continued until the study ends at 18 months. The primary end point of efficacy is the remission rate at 6 months. Follow-up will continue for 18 months in order to detect an influence of induction regimen on subsequent relapse rates.

This study has received approval from the Ethics Committee of the Second Hospital of Shanxi Medical University (2022YX-026). All participants are required to provide written informed consent and no study-related procedures will be performed until consent is obtained. The results of this trial will be published in peer-reviewed journals and presented at conferences.

ChiCTR2200063823.

To develop an interpretable deep learning model of lupus nephritis (LN) relapse prediction based on dynamic multivariable time-series data.

A single-centre, retrospective cohort study in China.

A Chinese central tertiary hospital.

The cohort study consisted of 1694 LN patients who had been registered in the Nanjing Glomerulonephritis Registry at the National Clinical Research Center of Kidney Diseases, Jinling Hospital from January 1985 to December 2010.

We developed a deep learning algorithm to predict LN relapse that consists of 59 features, including demographic, clinical, immunological, pathological and therapeutic characteristics that were collected for baseline analysis. A total of 32 227 data points were collected by the sliding window method and randomly divided into training (80%), validation (10%) and testing sets (10%). We developed a deep learning algorithm-based interpretable multivariable long short-term memory model for LN relapse risk prediction considering censored time-series data based on a cohort of 1694 LN patients. A mixture attention mechanism was deployed to capture variable interactions at different time points for estimating the temporal importance of the variables. Model performance was assessed according to C-index (concordance index).

The median follow-up time since remission was 4.1 (IQR, 1.7–6.7) years. The interpretable deep learning model based on dynamic multivariable time-series data achieved the best performance, with a C-index of 0.897, among models using only variables at the point of remission or time-variant variables. The importance of urinary protein, serum albumin and serum C3 showed time dependency in the model, that is, their contributions to the risk prediction increased over time.

Deep learning algorithms can effectively learn through time-series data to develop a predictive model for LN relapse. The model provides accurate predictions of LN relapse for different renal disease stages, which could be used in clinical practice to guide physicians on the management of LN patients.