Abstract
Juvenile idiopathic arthritis (JIA) is the most common chronic rheumatic disease in children, affecting roughly 1 in 1,000 children worldwide. Beyond the joint inflammation that defines the disease, JIA patients face an elevated risk of developing a range of comorbid conditions — from uveitis to growth disturbances to cardiovascular complications. However, the temporal patterns of comorbidity development are not well characterized in large populations. Do certain comorbidities emerge predominantly before diagnosis (suggesting shared etiology or early systemic effects), or do they accumulate primarily after diagnosis (suggesting consequences of the disease or its treatment)? Do patterns differ between systemic and non-systemic subtypes?
This project used electronic health record data to analyze comorbidity patterns before and after diagnosis in children with non-systemic RF-negative JIA — the most common subtype. By examining the timing and frequency of comorbid conditions relative to the date of JIA diagnosis, we can identify which conditions warrant heightened clinical surveillance at different stages of the disease course. The findings were presented at the IISE Annual Conference.