AI-BASED DYNAMIC PREDICTION OF CARDIOVASCULAR RISK IN RHEUMATOLOGIC PATIENTS: INTEGRATION OF CLINICAL AND IMMUNOLOGICAL MARKERS

Abstract

Chronic inflammatory rheumatologic diseases are increasingly recognized as systemic disorders with profound cardiovascular implications. Among these conditions, rheumatoid arthritis (RA) and reactive arthritis (ReA) are associated with a markedly elevated risk of cardiovascular morbidity and mortality compared with the general population. Epidemiological studies consistently demonstrate that patients with RA experience cardiovascular events at rates comparable to those observed in diabetes mellitus, a condition traditionally classified as a major cardiovascular risk equivalent. Reactive arthritis, although often episodic, also contributes to long-term vascular vulnerability through persistent immune activation and inflammatory cascades. The excess cardiovascular burden observed in these populations cannot be fully explained by traditional risk factors such as hypertension, dyslipidemia, smoking, and obesity. Instead, systemic inflammation acts as an independent driver of accelerated atherosclerosis, endothelial dysfunction, and vascular remodeling.