P005 Performance of giant cell arteritis pre-test probability score in a tertiary care setting
| Autor: | Premila Kadamban, Shyanthi Pattapola, Hoda Alkoky, Natasha Jordan, Bhaskardas Gupta |
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| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | Rheumatology. 61 |
| ISSN: | 1462-0332 1462-0324 |
| DOI: | 10.1093/rheumatology/keac133.004 |
| Popis: | Background/Aims Giant cell arteritis (GCA) is a chronic, idiopathic, granulomatous vasculitis of medium and large arteries comprising overlapping phenotypes of cranial arteritis and extracranial GCA. Vascular complications are generally due to delay in diagnosis and initiation of effective treatment. Due to the imminent risk of visual loss and other ischaemic complications it is vital to secure the diagnosis and it is equally important to exclude the mimics as the treatment of GCA has it's own complications. The objective of this quality improvement project was to assess the performance of Southend GCA Pre-test Probability Score (GCA PS) in a cohort of patients who were referred urgently with suspected GCA to the Rheumatology Department of Addenbrooke’s Hospital. Methods We analysed the data of 50 new patients seen between Aug 2019 and Feb 2020. GCA PS were calculated based on the information from GPs (clinical and biochemical data). The likely hood of GCA was determined on review after 1 month, based on the clinical, biochemical, histopathological data and response to steroids. Results A total of 50 cases were included in the study. Thirty-eight (76%) of them were females while 12(24%) were males. The median age was 68.5. The median probability score was 12, it ranged between 0 to 24. Finally, 25 patients were diagnosed as likely to have GCA based on clinical, biochemical, histopathological findings and response to steroids. The lowest probability score among those who had a positive biopsy was 10. The p value for the likelihood of GCA when the probability score was 10 or higher was 0.0001 which was very significant. Conclusion GCA pre-test probability score is a very promising and utilitarian tool for risk stratification of patients with suspected GCA and prediction of the likelihood of GCA. It enables exclusion of GCA in cases with low probability score and to have a higher degree of scrutiny in those with intermediate and high probability scores. Clinical diagnostic algorithm based on the BSR guidelines could further be utilised for confirmation. Disclosure P. Kadamban: None. S. Pattapola: None. H. Alkoky: None. N. Jordan: None. B. Gupta: None. |
| Databáze: | OpenAIRE |
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