Department of Rheumatology, St Vincent's University Hospital, Dublin, Ireland.
Royal College of Surgeons in Ireland, Department of Ophthalmology, Royal Victoria Eye and Ear Hospital Dublin and Rheumatology Research Group, Education and Research Centre, St Vincent's University Hospital, Dublin, Ireland.
Ann Rheum Dis. 2015 Nov;74(11):1990-5. doi: 10.1136/annrheumdis-2014-205358. Epub 2014 Jun 13.
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).
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.
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.
Approximately 40% of patients presenting with idiopathic AAU have undiagnosed SpA. A simple to apply algorithm is described with excellent sensitivity and specificity.
迄今为止,尚无任何国际或国家学会制定或认可的急性前葡萄膜炎(AAU)患者的正式指南或转诊途径。我们的研究目的是开发和验证一种评估算法,以便将适当的 AAU 患者从眼科医生转诊至风湿病科,从而有助于早期诊断脊柱关节病(SpA)。
所有连续到当地眼科医院急诊科就诊的 AAU 患者,但无已知 SpA 诊断的患者,均有资格参加本研究。排除任何其他已知原因导致的 AAU 的患者。本研究纳入了两个独立的队列。在这些队列中,使用测试算法和都柏林葡萄膜炎评估工具(DUET)算法(测试算法的修订形式)来分别识别 SpA 疑似患者和非 SpA 对照。
研究阶段 1. 算法开发队列(n=101):对整个队列进行风湿病学评估后,41.6%(n=42)的患者患有未确诊的 SpA。我们的测试算法的灵敏度为 100%,特异性为 53.5%。进一步的回归分析导致了 DUET 算法的发展,该算法具有以下改进:灵敏度为 95%,特异性为 98%,阳性似然比(LR)为 56.19,阴性 LR 为 0.04。研究阶段 2. DUET 算法验证队列(n=72):对队列进行风湿病学评估后,40%(n=29)的患者被诊断为 SpA,DUET 算法的表现如下:灵敏度为 96%,特异性为 97%,阳性 LR 为 41.5,阴性 LR 为 0.03。
大约 40%的特发性 AAU 患者患有未确诊的 SpA。描述了一种简单易用的算法,具有良好的灵敏度和特异性。