Cardiovascular risk assessment in patients with rheumatoid arthritis using carotid ultrasound B-mode imaging

Area of Science:

• Rheumatology
• Cardiology
• Medical Imaging
• Artificial Intelligence

Background:

• Rheumatoid arthritis (RA) is a chronic inflammatory disease associated with increased cardiovascular disease (CVD) risk.
• The underlying pathophysiological links between RA and CVD remain incompletely understood.
• Inflammation is a shared characteristic in both RA and CVD, highlighting potential common pathways.

Purpose of the Study:

• To elucidate the three primary pathophysiological pathways connecting RA and CVD.
• To identify effective CVD risk calculators, including traditional and carotid ultrasound-based methods, for RA patients.
• To explore the emerging role of artificial intelligence (AI) in assessing CVD risk within the RA population.

Main Methods:

• Extensive literature searches were conducted in PubMed and Web of Science databases.
• Search terms focused on cardiovascular disease risk assessment in rheumatoid arthritis patients.
• A total of 120 peer-reviewed articles were screened for inclusion in this review.

Main Results:

• Two of the three discussed pathophysiological pathways directly contribute to the atherosclerotic process and subsequent cardiac injury.
• Carotid ultrasound image-based risk calculators demonstrated superior predictive performance over conventional methods.
• Artificial intelligence technologies are increasingly being integrated into routine clinical practice for CVD risk assessment in RA patients.

Conclusions:

• Understanding the RA-CVD link is crucial for improving patient outcomes.
• Advanced imaging techniques like carotid ultrasound offer enhanced CVD risk stratification in RA.
• AI holds significant promise for optimizing CVD risk management in individuals with rheumatoid arthritis.