Timely rheumatologic referral and management are crucial for patients with potential inflammatory arthritis. To meet this need, tools such as the early inflammatory arthritis (EIA) detection tool was developed and has been evaluated in Western populations. The aims of this study were to translate the English version of the EIA detection tool to Chinese and to determine its clinimetric properties in Taiwanese patients.
Twenty controls and 111 patients with established diagnosis of osteoarthritis, rheumatoid arthritis, systemic autoimmune diseases, psoriatic arthritis, and ankylosing spondylitis were recruited from a regional hospital in south Taiwan. Multivariate logistic regression analysis was used to evaluate the independent and significant variables associated with diagnosis by rheumatologists. A prediction model was also developed for differentiating between patients with inflammatory arthritis and those with non-inflammatory arthritis musculoskeletal conditions.
The Chinese version of the EIA detection tool showed acceptable internal consistency (KR-20 coefficient 0.78) and test-retest reliability (κ statistic ranged from 0.43 to 0.94). A prediction model consisting of three EIA detection tool items (joint pain, swelling in hands or wrists, and ever been told to have rheumatoid arthritis) and sex was able to differentiate inflammatory arthritis and non-inflammatory arthritis musculoskeletal conditions with a sensitivity of 0.84, a specificity of 0.86, a positive predictive value of 0.92, and a negative predictive value of 0.76.
The Chinese version of the EIA detection tool showed good clinimetric properties in this study population and it can be used to differentiate Taiwanese patients with inflammatory arthritis and non-inflammatory arthritis musculoskeletal conditions.