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Deep Learning Study Exposes Global Rise and Inequalities in Rheumatoid Arthritis Burden

The analysis forecasts disease burden through 2040 with unprecedented local precision.

Overview

  • Researchers applied an AI-powered deep learning model to Global Burden of Disease data from 1980 to 2021 across 953 global and subnational locations.
  • Global incidence, prevalence and disability-adjusted life years for rheumatoid arthritis have steadily increased since 1980, driven largely by demographic aging and population growth.
  • Disparities widened with DALY-related inequality surging 62.6% between 1990 and 2021, with Finland, Ireland and New Zealand among the most affected.
  • High-SDI countries exhibited contrasting patterns, as Japan’s early-diagnosis programs and biologic therapies coincided with declining DALYs while the UK experienced smaller gains.
  • Projections indicate rising burdens in low-middle SDI regions by 2040 and identify smoking control as a strategy to reduce RA deaths by 16.8% and DALYs by 20.6% in high-smoking areas.