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Profiling risk factors for chronic uveitis in juvenile idiopathic arthritis: a new model for EHR-based research

Tyler S Cole1*, Jennifer Frankovich2, Srinivasan Iyer1, Paea LePendu1, Anna Bauer-Mehren1 and Nigam H Shah1

Author Affiliations

1 Stanford Center for Biomedical Informatics Research, Stanford University School of Medicine, 1265 Welch Road, MSOB, X-215, Stanford, CA 94305-5479, USA

2 Division of Rheumatology, Department of Pediatrics, Stanford University School of Medicine, Palo Alto, CA, USA

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Pediatric Rheumatology 2013, 11:45  doi:10.1186/1546-0096-11-45

Published: 3 December 2013

Abstract

Background

Juvenile idiopathic arthritis is the most common rheumatic disease in children. Chronic uveitis is a common and serious comorbid condition of juvenile idiopathic arthritis, with insidious presentation and potential to cause blindness. Knowledge of clinical associations will improve risk stratification. Based on clinical observation, we hypothesized that allergic conditions are associated with chronic uveitis in juvenile idiopathic arthritis patients.

Methods

This study is a retrospective cohort study using Stanford’s clinical data warehouse containing data from Lucile Packard Children’s Hospital from 2000–2011 to analyze patient characteristics associated with chronic uveitis in a large juvenile idiopathic arthritis cohort. Clinical notes in patients under 16 years of age were processed via a validated text analytics pipeline. Bivariate-associated variables were used in a multivariate logistic regression adjusted for age, gender, and race. Previously reported associations were evaluated to validate our methods. The main outcome measure was presence of terms indicating allergy or allergy medications use overrepresented in juvenile idiopathic arthritis patients with chronic uveitis. Residual text features were then used in unsupervised hierarchical clustering to compare clinical text similarity between patients with and without uveitis.

Results

Previously reported associations with uveitis in juvenile idiopathic arthritis patients (earlier age at arthritis diagnosis, oligoarticular-onset disease, antinuclear antibody status, history of psoriasis) were reproduced in our study. Use of allergy medications and terms describing allergic conditions were independently associated with chronic uveitis. The association with allergy drugs when adjusted for known associations remained significant (OR 2.54, 95% CI 1.22–5.4).

Conclusions

This study shows the potential of using a validated text analytics pipeline on clinical data warehouses to examine practice-based evidence for evaluating hypotheses formed during patient care. Our study reproduces four known associations with uveitis development in juvenile idiopathic arthritis patients, and reports a new association between allergic conditions and chronic uveitis in juvenile idiopathic arthritis patients.

Keywords:
Juvenile idiopathic arthritis; Uveitis; Allergy; Electronic health records; Text mining; Biomedical informatics