Multivariable Models to Predict a Diagnosis of Giant Cell Arteritis: Systematic Review and Metaanalysis
Predictors of GCA were consistent across models; however, models were of poor methodologic quality. Future models to predict a diagnosis of GCA should be constructed with improved methodologic rigor. (PROSPERO registration: CRD42020186725).
Authors
- Mats Junek (ORCID: https://orcid.org/0000-0001-8416-3955)
- NADER A. KHALIDI (ORCID: https://orcid.org/0000-0002-8270-2617)
- Seungwon Choi
- Matthew Jessome
- John Koussiouris (ORCID: https://orcid.org/0000-0002-8288-0907)
- Deborah Koh
- Iva Okaj (ORCID: https://orcid.org/0000-0001-8292-9080)
- Farid Foroutan (ORCID: https://orcid.org/0000-0002-1029-1812)
- Angela Hu (ORCID: https://orcid.org/0009-0001-3168-4041)
- Sagar Patel (ORCID: https://orcid.org/0000-0002-0897-9300)
- Stephanie Garner (ORCID: https://orcid.org/0009-0002-5229-471X)
- Sukhreet Atwal
- Colin Stark
- Johan Pushani
Institutions
- University of British Columbia (CA)
- McMaster Divinity College (CA)
- University of Calgary (CA)
- Queen's University (CA)
- Ted Rogers Centre for Heart Research (CA)
- St. Joseph’s Healthcare Hamilton (CA)
- Hamilton Health Sciences (CA)
- McMaster University (CA)
Publication Details
- Journal
- The Journal of Rheumatology
- Published
- 2025-07-01
- DOI
- https://doi.org/10.3899/jrheum.2022-1204
- Citations
- 1
- Primary Topic
- Vasculitis and related conditions
- Type
- article
- Field-Weighted Citation Impact
- 1.52