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Background To use biochemical markers and ultrasound to differentiate between inflammatory and noninflammatory diagnoses in the early inflammatory arthritis (EIA) referral setting. Careful patient selection is crucial to ensure timely and efficient use of secondary care resources. Methods A retrospective audit of the EIA pathway was conducted over six months at two partnered district general hospitals in London in 2018. For each of the 75 patients studied, data collected included demographics, biomarkers of disease and inflammation, appointments dates, details of scans requested, and the clinical diagnosis made at the EIA appointment. Statistical tests included pairwise comparisons using Welch’s 2-sample t-test for continuous variables and two-sample chi squared tests for equality of proportions with continuity correction for categorical variables. Logistic regression models were used, incorporating age, inflammatory markers and serostatus. Goodness of fit was evaluated using the log likelihood method and McFadden’s pseudo-R2. Predictive modelling was carried out using the Caret package. Analysis was conducted in R (R v3.5). Results Over half of participants (59%) were diagnosed with non-inflammatory disorders; the most common diagnosis was osteoarthritis (31%). Rheumatoid Arthritis (15%) was most common amongst the 41% of Inflammatory arthritides (IA). Ultrasound confirmed the clinical diagnosis of IA vs non-IA with 70% accuracy. There were no significant differences between those with and without ultrasound evidence of synovitis in terms of age (p 0.25), CRP (p 0.22), ESR (p 0.59), RF (p 0.43) or CCP (p 1) positivity. This null is likely due to a small sample size and lack of statistical power. Comparison of patients with a clinical diagnosis of IA vs non-IA revealed significantly increased CRP (9.5 vs 4.2 p 0.01) and CCP positivity rates (22.5% vs 0%, p 0.003) in the inflammatory group, with no significant differences in age (p 0.45), ESR (p 0.24), or RF positivity rate (p 0.18). In those with a clinical diagnosis of osteoarthritis, there were a significantly higher age (55.0 vs 43.5, p 0.0009), lower CRP (3.2 vs 7.8, p 0.005), and lower ESR (9.2 vs 19.7, p 0.006). Neither RF (p 0.73) nor CCP (p 0.16) positivity rates differed significantly between osteoarthritis or other diagnoses. Conclusion It was demonstrated that even in small cohorts, simple predictive variables can be used to risk-stratify and assess the likelihood that a patient will have osteoarthritis rather than IA. It is shown that older age, lower ESR and lower CRP are indicators at differentiating IA from non-IA. Given the national high prevalence of osteoarthritis and the clinical uncertainty in distinguishing osteoarthritis from IA, ultrasound has significant value in the diagnostic work-up. Further research should attempt to predict eventual diagnosis from clinical characteristics alone to help general practitioners distinguish patients with IA from those with non-IA. Disclosures B.M. Jacobs None. N. Sarathchandra None. M. Karela None. L.E. Daniels None. N. Purkayastha None.

rheumatology

P90 Streamlining primary care referrals to an early inflammatory arthritis (EIA) clinic: distinguishing between patients with osteoarthritis and inflammatory arthritis