Cultural Adaptation and Development of an Educational Intervention Relating to Cardiovascular Disease Associated with Rheumatoid Arthritis for South Asian People.

Background: The cardiovascular disease (CVD) risk is elevated by 1.5 times among South Asians with rheumatological conditions like rheumatoid arthritis (RA) in the UK. However, there is a dearth of culturally sensitive educational interventions tailored to this population.

Cardiovascular Magnetic Resonance for the Evaluation of Arrhythmogenic Substrates in Patients with Systemic Autoimmunity: An Update.

Patients with systemic autoimmunity due to autoimmune rheumatic diseases (ARDs) or sarcoidosis frequently present with systemic manifestations including cardiac involvement. Cardiac rhythm disturbances and specifically ventricular arrhythmias (VAs) may affect the prognosis of these patients. Cardiovascular magnetic resonance imaging (CMR) is a non-invasive imaging modality that can provide valuable diagnostic and prognostic information in patients with ARDs or systemic autoimmunity in general.

Biological use influences the impact of inflammation on risk of major adverse cardiovascular events in rheumatoid arthritis.

Objectives: Chronic inflammation promotes cardiovascular risk in rheumatoid arthritis (RA). Biological disease-modifying antirheumatic drugs (bDMARDs) improve disease activity and cardiovascular disease outcomes. We explored whether bDMARDs influence the impact of disease activity and inflammatory markers on long-term cardiovascular risk in RA.

Artificial intelligence for cardiovascular disease risk assessment in personalised framework: a scoping review.

Background: The field of precision medicine endeavors to transform the healthcare industry by advancing individualised strategies for diagnosis, treatment modalities, and predictive assessments. This is achieved by utilizing extensive multidimensional biological datasets encompassing diverse components, such as an individual's genetic makeup, functional attributes, and environmental influences. Artificial intelligence (AI) systems, namely machine learning (ML) and deep learning (DL), have exhibited remarkable efficacy in predicting the potential occurrence of specific cancers and cardiovascular diseases (CVD).