Damage in rheumatic diseases: Contemporary international standpoint and scores emerging from clinical, radiological and machine learning

Abstract

In rheumatic diseases, damage is a major concern and reflects irreversible organ scarring or tissue degradation. Quantifying damage or measuring its severity is an indispensable concern in determining the overall outcome. Damage considerably influences both longterm prognosis and quality of life. Rheumatic diseases (RD) represent a significant health burden. Organ damage is consistently associated with increased mortality. Monitoring damage is critical in the evaluation of patients and in appraising treatment efficacy. Proper assessment and early detection of damage paves way for modifying the disease course with effective medications and regimens may reduce organ damage, improve outcomes and decrease mortality. With the exception of systemic lupus erythematosus and vasculitis, most RDs lack an established damage index making it an ongoing demand to develop effective scores and prediction models for damage accrual early in the disease course. A better understanding of machine learning with the increasing availability of medical large data may facilitate the development of meaningful precision medicine for patients with RDs. An updated spectrum of clinical and radiological damage scores and indices as well as the role of machine learning are presented in this review for the key RDs.