Clinical presentations of giant cell arteritis (GCA) are protean, and it is vital to make a secure diagnosis and exclude mimics for urgent referrals with suspected GCA. The main objective was to develop a joined-up, end-to-end, fast-track confirmatory/exclusionary, algorithmic process based on a probability score triage to drive subsequent investigations with ultrasound (US) and any appropriate additional tests as required.
The algorithm was initiated by stratifying patients to low-risk category (LRC), intermediate-risk category (IRC) and high-risk category (HRC). Retrospective data was extracted from case records. The Southend pretest probability score (PTPS) overall showed a median score of 9 and a 75th percentile score of 12. We, therefore, classified LRC as PTPS <9, IRC 9-12 and HRC >12. GCA diagnosis was made by a combination of clinical, US, and laboratory findings. The algorithm was assessed in all referrals seen in 2018-2019 to test the diagnostic performance of US overall and in individual categories.
Of 354 referrals, 89 had GCA with cases categorised as LRC (151), IRC (137) and HRC (66). 250 had US, whereas 104 did not (score <7, and/or high probability of alternative diagnoses). In HRC, US showed sensitivity 94%, specificity 85%, accuracy 92% and GCA prevalence 80%. In LRC, US showed sensitivity undefined (0/0), specificity 98%, accuracy 98% and GCA prevalence 0%. In IRC, US showed sensitivity 100%, specificity 97%, accuracy 98% and GCA prevalence 26%. In the total population, US showed sensitivity 97%, specificity 97% and accuracy 97%. Prevalence of GCA overall was 25%.
The Southend PTPS successfully stratifies fast-track clinic referrals and excludes mimics. The algorithm interprets US in context, clarifies a diagnostic approach and identifies uncertainty, need for re-evaluation and alternative tests. Test performance of US is significantly enhanced with PTPS.