Probability-based algorithm using ultrasound and additional tests for suspected GCA in a fast-track clinic

OBJECTIVES: 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 ba...

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Detalles Bibliográficos
Autores principales: Sebastian, Alwin, Tomelleri, Alessandro, Kayani, Abdul, Prieto-Pena, Diana, Ranasinghe, Chavini, Dasgupta, Bhaskar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2020
Materias:
Vasculitis
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7547539/
https://www.ncbi.nlm.nih.gov/pubmed/32994361
http://dx.doi.org/10.1136/rmdopen-2020-001297
Descripción
Sumario:OBJECTIVES: 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. METHODS: 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. RESULTS: 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%. CONCLUSIONS: 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.

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