Advances in the diagnosis of giant cell arteritis.


Journal

Current opinion in ophthalmology
ISSN: 1531-7021
Titre abrégé: Curr Opin Ophthalmol
Pays: United States
ID NLM: 9011108

Informations de publication

Date de publication:
Nov 2019
Historique:
pubmed: 11 9 2019
medline: 21 12 2019
entrez: 11 9 2019
Statut: ppublish

Résumé

To summarize recent advances in the diagnosis of giant cell arteritis (GCA). Less common manifestations of GCA include corneal edema, proptosis from lacrimal gland ischemia and sensorineuronal hearing loss. Histology studies have suggested that temporal artery biopsies (TAB) with fixed specimen lengths of 15 mm may be adequate to prevent false negative biopsies. In centers with appropriate radiologic expertise, a European rheumatology consensus guideline has proposed Doppler ultrasound as a first-line confirmatory test for GCA in lieu of temporal artery biopsy. Finding extracranial large vessel disease can help to diagnose GCA. Statistical prediction rules can help risk stratify patients with suspected GCA. Age and platelet level when maintained as continuous variables are the strongest predictors for GCA. GCA can present with diverse ophthalmic and systemic presentations and expedient recognition of same can avoid diagnostic delay and possible vision loss, among other complications. TAB remains the conventional diagnostic standard test for GCA. The use of statistical prediction models and increased expertise in noninvasive imaging techniques such as ultrasound may decrease reliance on TAB, especially in patients determined to be at low risk for GCA.

Identifiants

pubmed: 31503077
doi: 10.1097/ICU.0000000000000616
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

407-411

Auteurs

Edsel Ing (E)

Department of Ophthalmology, University of Toronto, Michael Garron Hospital.

Christian Pagnoux (C)

Division of Rheumatology, Mt. Sinai Hospital, Toronto, Ontario, Canada.

Nurhan Torun (N)

Division of Ophthalmology, Beth Israel Deaconess Hospital, Harvard Medical School, Boston, Massachusetts, USA.

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Classifications MeSH