Literature DB >> 31848610

The impact of disease extent and severity detected by quantitative ultrasound analysis in the diagnosis and outcome of giant cell arteritis.

Sara Monti1,2,3, Cristina Ponte4,5, Claudio Pereira3, Federica Manzoni6, Catherine Klersy6, Federica Rumi7, Greta Carrara7, Andrew Hutchings8, Wolfgang A Schmidt9, Bhaskar Dasgupta10, Roberto Caporali1, Carlomaurizio Montecucco1, Raashid Luqmani3.   

Abstract

OBJECTIVES: To develop a quantitative score based on colour duplex sonography (CDS) to predict the diagnosis and outcome of GCA.
METHODS: We selected patients with positive CDS and confirmed diagnosis of GCA recruited into the TA Biopsy (TAB) vs Ultrasound in Diagnosis of GCA (TABUL) study and in a validation, independent cohort. We fitted four CDS models including combinations of the following: number and distribution of halos at the TA branches, average and maximum intima-media thickness of TA and axillary arteries. We fitted four clinical/laboratory models. The combined CDS and clinical models were used to develop a score to predict risk of positive TAB and clinical outcome at 6 months.
RESULTS: We included 135 GCA patients from TABUL (female: 68%, age 73 (8) years) and 72 patients from the independent cohort (female: 46%, age 75 (7) years). The best-fitting CDS model for TAB used maximum intima-media thickness size and bilaterality of TA and axillary arteries' halos. The best-fitting clinical model included raised inflammatory markers, PMR, headache and ischaemic symptoms. By combining CDS and clinical models we derived a score to compute the probability of a positive TAB. Model discrimination was fair (area under the receiver operating characteristic curve 0.77, 95% CI: 0.68, 0.84). No significant association was found for prediction of clinical outcome at 6 months.
CONCLUSION: A quantitative analysis of CDS and clinical characteristics is useful to identify patients with a positive biopsy, supporting the use of CDS as a surrogate tool to replace TAB. No predictive role was found for worse prognosis.
© The Author(s) 2019. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Entities:  

Keywords:  GCA; TA biopsy; colour duplex sonography; diagnosis; prognosis; ultrasound

Year:  2020        PMID: 31848610     DOI: 10.1093/rheumatology/kez554

Source DB:  PubMed          Journal:  Rheumatology (Oxford)        ISSN: 1462-0324            Impact factor:   7.580


  5 in total

1.  Halo score (temporal artery, its branches and axillary artery) as a diagnostic, prognostic and disease monitoring tool for Giant Cell Arteritis (GCA).

Authors:  Alwin Sebastian; Kornelis S M van der Geest; Fiona Coath; Prisca Gondo; Abdul Kayani; Craig Mackerness; Bernard Hadebe; Sue Innes; Jo Jackson; Bhaskar Dasgupta
Journal:  BMC Rheumatol       Date:  2020-08-18

2.  Vascular Ultrasound for Giant Cell Arteritis: Establishing a Protocol Using Vascular Sonographers in a Fast-Track Clinic in the United States.

Authors:  Charles Oshinsky; Alison M Bays; Ingeborg Sacksen; Elizabeth Jernberg; R Eugene Zierler; Andreas P Diamantopoulos; Jean W Liew; Sarah H Chung; P Scott Pollock
Journal:  ACR Open Rheumatol       Date:  2021-10-14

Review 3.  Evolution of ultrasound in giant cell arteritis.

Authors:  Colm Kirby; Rachael Flood; Ronan Mullan; Grainne Murphy; David Kane
Journal:  Front Med (Lausanne)       Date:  2022-10-03

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

Authors:  Michael Czihal; Christian Lottspeich; Christoph Bernau; Teresa Henke; Ilaria Prearo; Marc Mackert; Siegfried Priglinger; Claudia Dechant; Hendrik Schulze-Koops; Ulrich Hoffmann
Journal:  J Clin Med       Date:  2021-03-10       Impact factor: 4.241

  5 in total

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