Attitudes towards technology supported rheumatoid arthritis care: investigating patient- and clinician-perceived opportunities and barriers.

Objectives: Globally, demand outstrips capacity in rheumatology services, making Mobile Health (mHealth) attractive, with the potential to improve access, empower patient self-management and save costs. Existing mHealth interventions have poor uptake by end users. This study was designed to understand existing challenges, opportunities and barriers for computer technology in the RA care pathway. Methods: People with RA were recruited from Barts Health NHS Trust rheumatology clinics to complete paper questionnaires and clinicians were recruited from a variety of centres in the UK to complete an online questionnaire. Data collected included demographics, current technology use, challenges managing RA, RA medications and monitoring, clinic appointments, opportunities for technology and barriers to technology. Results: A total of 109 patient and 41 clinician questionnaires were completed. A total of 83.5% of patients and 93.5% of clinicians use smartphones daily. However, only 25% had ever used an arthritis app and only 5% had persisted with one. Both groups identified managing pain, flares and RA medications as areas of existing need. Access to care, medication support and disease education were mutually agreeable opportunities; however, discrepancies existed between groups with clinicians prioritizing education over access, likely due to concerns of data overwhelm (80.6% considered this a barrier). Conclusions: In spite of high technology use and willingness from both sides, our cohort did not utilize technology to support care, suggesting inadequacies in the existing software. The lack of an objective biomarker for RA disease activity, existing challenges in the healthcare system and the need for integration with existing technical systems were identified as the greatest barriers. Trial registration: Registered on the Clinical Research Network registry (IRAS ID: 264690).

A case of antisynthetase syndrome presenting solely with life-threatening interstitial lung disease.

A previously fit and well 38-year-old man presented during the COVID-19 pandemic with dyspnoea, cough and palpitations. C-reactive protein was elevated and chest X-ray demonstrated bilateral lower zone consolidation. SARS CoV-2 swab was negative. He was diagnosed with community-acquired pneumonia and treated with oral antibiotics. He developed severe type 1 respiratory failure and was admitted to the high-dependency unit for non-invasive ventilation. CTPA was negative for pulmonary embolism, instead demonstrating bilateral organising pneumonia. Empirical treatment for swab-negative COVID-19 pneumonitis was started; however, further deterioration ensued and prompted intubation and ventilation. Microbiological testing did not yield any positive results, thereby raising suspicion for the presence of an autoimmune disease. Pulsed intravenous methylprednisolone was administered with good effect. ENA screen was positive for anti-Jo1 and myositis-specific autoantibodies were positive for Ro-52, Ku and PL-12. The patient was extubated and did not exhibit any muscle weakness on clinical examination. Creatine kinase was only mildly elevated. He was diagnosed with amyopathic antisynthetase syndrome - frequently considered as a form of idiopathic inflammatory myopathy (IIM) - and treated with further intravenous methylprednisolone and cyclophosphamide. Oxygen therapy was gradually weaned and the patient discharged on mycophenolate mofetil and a weaning course of oral steroids.

From Personalised Predictions to Targeted Advice: Improving Self-Management in Rheumatoid Arthritis.

Rheumatoid arthritis (RA) is a chronic inflammatory autoimmune disease, that can lead to joint damage but also affects quality of life (QoL) including aspects such as self-esteem, fatigue, and mood. Current medical management focuses on the fluctuating disease activity to prevent progressive disability, but practical constraints mean periodic clinic appointments give little attention to the patient's experience of managing the wider consequences of chronic illness. The main aim of this study is to explore how to use patient-derived data both for clinical decision-making and for personalisation, with the first steps towards a platform for tailoring self-management advice to patients' lifestyle changes. As a result, we proposed a Bayesian network model for personalisation and have obtained promising outcomes.