Literature DB >> 35910712

Performance of the Southend pre-test probability score (PTPS) for giant cell arteritis in a fast-track clinic in Western Australia.

Mmoloki Mathake1, Julia Murdoch2, Jean-Louis DeSousa3, Andrew Taylor2, Helen Keen1.   

Abstract

Entities:  

Year:  2022        PMID: 35910712      PMCID: PMC9334783          DOI: 10.1093/rap/rkac055

Source DB:  PubMed          Journal:  Rheumatol Adv Pract        ISSN: 2514-1775


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The Southend pre-test probability score might be useful in risk stratifying patients presenting to GCA fast-track clinics. Dear Editor, We report the performance of the Southend pre-test probability score (PTPS) for GCA in our GCA assessment clinic. GCA is the most common large vessel vasculitis. Intense vascular inflammation leads to myointimal proliferation and potential vessel occlusion, which can result in major ischaemic events, such as blindness and stroke. Therefore, GCA is considered a medical emergency, necessitating timely and accurate diagnosis and intervention [1, 2]. GCA most frequently presents with headache, which is a common and non-specific presentation. Associated features can include jaw claudication, scalp tenderness, visual disturbances and non-specific constitutional symptoms; however, the symptoms at presentation are heterogeneous. Physical signs, when present, can include thickened or tender temporal arteries on palpation in addition to diminished or absent pulses [1]. Inflammatory markers are generally elevated, but normal inflammatory markers do not preclude the diagnosis. For these reasons, diagnosis can be challenging. Objective confirmation of the diagnosis is pursued to justify the use of aggressive and long-term immunosuppression. Historically, TA biopsy has been considered the gold standard for diagnosis for GCA. TA biopsy has a high specificity but low sensitivity (as low as 39%), is invasive and can be difficult to obtain in a timely manner [1]. Recently, imaging modalities such as US, PET scan, MRI and CT scan have been endorsed as diagnostic tools in international guidelines, but they assume local competency and ease of access [1-3]. Furthermore, the pre-test probablity of GCA is essential to consider when assessing the clinical utility of these imaging modalities, because none provides stand-alone definitive confirmation of the disease. The pre-test probability of disease is a crucial component of GCA assessment and clinical decision-making. Therefore, a clinical tool to define the probability of GCA objectively is likely to be very useful. Recently, the Southend pre-test probability score (PTPS) has been developed to aid GCA assessment [4, 5]. The tool was developed retrospectively and has not been tested in different populations. In this study, we aimed to apply the PTPS to patients seen through our GCA fast-track clinic in Western Australia to assess the utility of this score in risk stratifying patients with suspected GCA. Patients presenting to the Royal Perth Hospital GCA fast-track clinic were consented for prospective data collection. GCA was defined as clinical diagnosis of GCA at 6 months, based on the opinion of clinicians, formulated on history, examination, TA US and TA biopsy or additional imaging in select cases. We calculated the Southend PTPS retrospectively from the data collected prospectively over the 18 months between November 2019 and May 2021. Using the PTPS, we risk stratified patients into low-risk (PTPS < 9), intermediate-risk (PTPS = 9–12), and high-risk (PTPS > 12) groups and correlated these with the final clinical diagnosis. We then dichotomized the PTPS into low-risk or intermediate/high-risk groups to determine the sensitivity, specificity, positive predictive value and negative predictive value. Data were analysed from 104 patients over the specified time frame. The demographics and the prevalence of features of the Southend PTPS are presented in Table 1. The clinical diagnosis of GCA at 6 months occurred in 25, giving a prevalence of 24%. Using the PTPS, 45 (43%) of the 104 patients were classified as low risk, 34 (32%) intermediate risk and 25 (24%) high risk for GCA. In the low-risk category, GCA prevalence was 0%, in the intermediate-risk group 15% and in the high-risk category 80% (P < 0.001).
Table 1

Baseline demographics and features of patients with GCA compared with the total number of patients

DemographicsNumber of patients (n = 104)Patients with GCA (total n = 25 of 104)
Age, years
 <4940
 50–60204
 61–65193
 >666118
Gender
 Male3012
 Female7413
Duration of symptoms, weeks
 >24132
 12–2491
 6–12162
 <66620
CRP, mg/la
 0–5254
 6–10140
 11–25264
 >253615
Symptoms
 Headache
  No114
  Yes9321
 Polymylagia
  No8719
  Yes176
 Constitutional
  No7719
  Single226
  Combination50
 Ischaemic
  No8613
  Yes1812
Signs
 Visual
  No9217
  Yes128
 TA abnormality
  No8516
  Tenderness101
  Thickening43
  Pulse loss55
 Extracranial artery abnormality
  No10223
  Thickening22
  Bruit00
  Pulse loss00
 Cranial nerve palsy
  No10425
  Yes00
 Alternative
  Infection120
  Cancer52
  Systemic rheumatic diseases10
  Head and neck pathology00
  Other102

The CRP values for three patients in the control group and four in the GCA group were missing from the records (this would not have changed the category of the patients).

Baseline demographics and features of patients with GCA compared with the total number of patients The CRP values for three patients in the control group and four in the GCA group were missing from the records (this would not have changed the category of the patients). The Southend PTPS (dichotomized) had a sensitivity of 100%, specificity of 56.9%, positive predictive value of 42.3% and negative predictive value of 100%. In conclusion, the PTPS (applied retrospectively) successfully stratified patients referred to our fast-track clinic into high and low risk for GCA, when using the clinical diagnosis as the gold standard. Our study provides external validation to the currently published work. This tool might be useful in risk stratifying patients who are undergoing specialist assessment for GCA in the fast-track clinic setting; the negative predictive value suggests that this tool is valuable to exclude GCA, but this needs to be tested prospectively. Funding: No specific funding was received from any bodies in the public, commercial or not-for-profit sectors to carry out the work described in this article. Disclosure statement: The authors declare no conflict of interest.
  5 in total

1.  2018 Update of the EULAR recommendations for the management of large vessel vasculitis.

Authors:  Bernhard Hellmich; Ana Agueda; Sara Monti; Frank Buttgereit; Hubert de Boysson; Elisabeth Brouwer; Rebecca Cassie; Maria C Cid; Bhaskar Dasgupta; Christian Dejaco; Gulen Hatemi; Nicole Hollinger; Alfred Mahr; Susan P Mollan; Chetan Mukhtyar; Cristina Ponte; Carlo Salvarani; Rajappa Sivakumar; Xinping Tian; Gunnar Tomasson; Carl Turesson; Wolfgang Schmidt; Peter M Villiger; Richard Watts; Chris Young; Raashid Ahmed Luqmani
Journal:  Ann Rheum Dis       Date:  2019-07-03       Impact factor: 19.103

2.  A probability score to aid the diagnosis of suspected giant cell arteritis.

Authors:  Faidra Laskou; Fiona Coath; Sarah L Mackie; Siwalik Banerjee; Tin Aung; Bhaskar Dasgupta
Journal:  Clin Exp Rheumatol       Date:  2019-02-15       Impact factor: 4.473

Review 3.  Diagnosis of giant cell arteritis.

Authors:  Cristina Ponte; Joana Martins-Martinho; Raashid Ahmed Luqmani
Journal:  Rheumatology (Oxford)       Date:  2020-05-01       Impact factor: 7.580

4.  2021 American College of Rheumatology/Vasculitis Foundation Guideline for the Management of Giant Cell Arteritis and Takayasu Arteritis.

Authors:  Mehrdad Maz; Sharon A Chung; Andy Abril; Carol A Langford; Mark Gorelik; Gordon Guyatt; Amy M Archer; Doyt L Conn; Kathy A Full; Peter C Grayson; Maria F Ibarra; Lisa F Imundo; Susan Kim; Peter A Merkel; Rennie L Rhee; Philip Seo; John H Stone; Sangeeta Sule; Robert P Sundel; Omar I Vitobaldi; Ann Warner; Kevin Byram; Anisha B Dua; Nedaa Husainat; Karen E James; Mohamad A Kalot; Yih Chang Lin; Jason M Springer; Marat Turgunbaev; Alexandra Villa-Forte; Amy S Turner; Reem A Mustafa
Journal:  Arthritis Rheumatol       Date:  2021-07-08       Impact factor: 10.995

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

Authors:  Alwin Sebastian; Alessandro Tomelleri; Abdul Kayani; Diana Prieto-Pena; Chavini Ranasinghe; Bhaskar Dasgupta
Journal:  RMD Open       Date:  2020-09
  5 in total

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