A novel evidence-based detection of undiagnosed spondyloarthritis in patients presenting with acute anterior uveitis: the DUET (Dublin Uveitis Evaluation Tool)

Background

To date, there are no formal guidelines or referral pathways for acute anterior uveitis (AAU) patients developed or endorsed by any international or national societies. The objective of our study was to develop and validate an assessment algorithm for referral from ophthalmologists of appropriate AAU patients to rheumatology that will aid the early diagnosis of the spondyloarthropathy (SpA).

Methods

All consecutive patients attending the emergency department of local ophthalmology hospital with AAU, but who did not have a known diagnosis of SpA, were eligible to participate in this study. Patients with any other known cause of AAU were excluded. Two independent cohorts were enrolled. Test algorithm and Dublin Uveitis Evaluation Tool (DUET) algorithm (revised form of test algorithm) were used in these cohorts to identify patients as SpA suspects and non-SpA controls, respectively.

Results

STUDY PHASE-1. ALGORITHM DEVELOPMENT COHORT (n=101): After rheumatologic evaluation of the entire cohort, 41.6% (n=42) had undiagnosed SpA. Our test algorithm was noted to have: sensitivity 100% and specificity 53.5%. Further regression analysis resulted in the development of the DUET algorithm which made the following improvements: sensitivity 95%, specificity 98%, positive likelihood ratio (LR) 56.19, and negative LR 0.04. STUDY PHASE-2. DUET ALGORITHM VALIDATION COHORT (n=72): After rheumatologic evaluation of the cohort, 40% (n=29) were diagnosed with SpA, with the following performance of DUET algorithm—sensitivity 96%, specificity 97%, positive LR 41.5 and negative LR 0.03.

Conclusions

Approximately 40% of patients presenting with idiopathic AAU have undiagnosed SpA. A simple to apply algorithm is described with excellent sensitivity and specificity.