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Diagnostic Algorithm for Patients With Suspected Giant Cell Arteritis

Overview
Specialties Neurology
Ophthalmology
Date 2015 Mar 25
PMID 25802967
Citations 9
Authors
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Abstract

Background: To identify clinical and laboratory factors contributing to the diagnosis of giant cell arteritis (GCA) and develop a diagnostic algorithm for the evaluation of GCA.

Methods: Retrospective review of 213 consecutive cases of temporal artery biopsy (TAB) seen at a single academic center over a 10-year period (2000-2009). Pathologic specimens were re-reviewed and agreement between the original and second readings was assessed. A composite clinical suspicion score was created by adding 1 point for each of the following criteria: anterior extracranial circulation ischemia, new onset headache, abnormal laboratory results (erythrocyte sedimentation rate, C-reactive protein (CRP), or platelet count), jaw claudication, abnormal or tender superficial temporal artery, constitutional symptoms, and polymyalgia rheumatica; one point was subtracted if a comorbid condition could explain a criterion.

Results: Of the 204 TABs analyzed, pathologic findings were confirmatory in 49 (24.0%) and suggestive in 12 (5.9%). TAB-positive patients were more likely to be older (age 75.2 ± 7.8 vs 69.7 ± 11.0 years, P = 0.0002), complain of jaw claudication (relative-risk = 3.26, P = 0.0014), and have thrombocytosis (relative-risk = 3.3, P = 0.0072) and elevated CRP (relative-risk = 1.8, P = 0.037). None of the patients with a clinical score less than 2 had a positive TAB. Diabetes mellitus and kidney disease were often the explanation for the symptoms and abnormal clinical finding(s) that led to a negative TAB.

Conclusions: We propose a clinical algorithm that is highly predictive for a positive TAB and can be valuable in the evaluation process of suspected cases of GCA.

Citing Articles

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

Czihal M, Lottspeich C, Bernau C, Henke T, Prearo I, Mackert M J Clin Med. 2021; 10(6).

PMID: 33802092 PMC: 8001831. DOI: 10.3390/jcm10061163.


Diagnostic Accuracy of Symptoms, Physical Signs, and Laboratory Tests for Giant Cell Arteritis: A Systematic Review and Meta-analysis.

van der Geest K, Sandovici M, Brouwer E, Mackie S JAMA Intern Med. 2020; 180(10):1295-1304.

PMID: 32804186 PMC: 7432275. DOI: 10.1001/jamainternmed.2020.3050.


Neural network and logistic regression diagnostic prediction models for giant cell arteritis: development and validation.

Ing E, Miller N, Nguyen A, Su W, Bursztyn L, Poole M Clin Ophthalmol. 2019; 13:421-430.

PMID: 30863010 PMC: 6388759. DOI: 10.2147/OPTH.S193460.


The Platelet-to-Lymphocyte Ratio as an Inflammatory Marker in Rheumatic Diseases.

Gasparyan A, Ayvazyan L, Mukanova U, Yessirkepov M, Kitas G Ann Lab Med. 2019; 39(4):345-357.

PMID: 30809980 PMC: 6400713. DOI: 10.3343/alm.2019.39.4.345.


Giant cell arteritis: early diagnosis is key.

Baig I, Pascoe A, Kini A, Lee A Eye Brain. 2019; 11:1-12.

PMID: 30697092 PMC: 6340646. DOI: 10.2147/EB.S170388.