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

Abstract

ObjectivesClinical 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.MethodsThe 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.ResultsOf 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%.ConclusionsThe 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.

A Diagnostic Algorithm Based on a Simple Clinical Prediction Rule for the Diagnosis of Cranial Giant Cell Arteritis

“…The specific diagnoses in patients not classified as suffering from cGCA are listed in Table S1 of the Supplementary Materials . Logistic regression analysis substantiated the results of the literature review [ 12 , 13 , 14 , 15 , 16 , 17 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 ], showing that a model including jaw claudication (logOR 4.1, 95% CI 1.7–6.7), new onset permanent headache (logOR 3.5, 95% CI 0.6–4.8), age > 70 (logOR 2.2, 95% CI 0.03–4.4), and an ophthalmological diagnosis of anterior ischemic optic neuropathy (AION; unilateral: logOR 2.7, 95% CI 0.6–4.7; bilateral: logOR 3.5, 95% CI 0.07–6.8) discriminated patients with and without cGCA with the highest diagnostic accuracy (AIC 48.6; area under the curve (AUC) 0.96).…”

“…Of note, Laskou et al were the first to use a clinical reference diagnosis, taking into account the clinical course over time [ 28 ]. Subsequently, this Southend pretest probability score, stratifying fast-track referral patients into low-risk, intermediate-risk, and high-risk probability categories based on 17 items, was shown to enhance the test performance of temporal/axillary artery sonography [ 29 ]. Most recently, a Canadian study contextualized the diagnostic yield of temporal artery magnetic resonance angiography in the diagnosis of GCA dependent on pre-test-probability [ 38 ].…”

“…We performed a literature review to identify clinical symptoms and signs predictive for a diagnosis of cGCA [ 12 , 13 , 14 , 15 , 16 , 17 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 ]. We analyzed the prevalence of potential candidate items in the first cohort, comprising 92 patients referred to our institution with suspected GCA (cranial and/or extracranial) between October 2014 and October 2015 [ 8 ].…”

Role of the halo sign in the assessment of giant cell arteritis: a systematic review and meta-analysis

“…Another reason could be that occlusion and stenosis are not assessed routinely, as mentioned in OMERACT, and more work is certainly needed to standardize the definition of these findings. A recent study showed that when combining the GCA pre-test probability score with the halo sign, the sensitivity increases to between 94 and 100% [ 57 ].…”

Imaging Tests in the Early Diagnosis of Giant Cell Arteritis

“…It should be noted that imaging test results should always be interpreted in the context of the level of suspicion of GCA, which is generally based on the clinical judgment and experience of the physician treating patients with GCA. Efforts have been made by different expert groups to develop pre-test clinical probability scores for GCA to help clinicians estimate the likelihood of GCA [65,66]. These scores can be potentially useful in ensuring a more homogeneous management of patients with GCA and in optimizing the performance of imaging techniques.…”