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Diagnostic Algorithm for Patients With Suspected Giant Cell Arteritis.

Publication ,  Journal Article
El-Dairi, MA; Chang, L; Proia, AD; Cummings, TJ; Stinnett, SS; Bhatti, MT
Published in: J Neuroophthalmol
September 2015

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.

Duke Scholars

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Published In

J Neuroophthalmol

DOI

EISSN

1536-5166

Publication Date

September 2015

Volume

35

Issue

3

Start / End Page

246 / 253

Location

United States

Related Subject Headings

  • ROC Curve
  • Platelet Count
  • Ophthalmology & Optometry
  • Middle Aged
  • Male
  • Longitudinal Studies
  • Humans
  • Giant Cell Arteritis
  • Female
  • Diagnostic Techniques, Ophthalmological
 

Citation

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El-Dairi, M. A., Chang, L., Proia, A. D., Cummings, T. J., Stinnett, S. S., & Bhatti, M. T. (2015). Diagnostic Algorithm for Patients With Suspected Giant Cell Arteritis. J Neuroophthalmol, 35(3), 246–253. https://doi.org/10.1097/WNO.0000000000000234
El-Dairi, Mays A., Lan Chang, Alan D. Proia, Thomas J. Cummings, Sandra S. Stinnett, and M Tariq Bhatti. “Diagnostic Algorithm for Patients With Suspected Giant Cell Arteritis.J Neuroophthalmol 35, no. 3 (September 2015): 246–53. https://doi.org/10.1097/WNO.0000000000000234.
El-Dairi MA, Chang L, Proia AD, Cummings TJ, Stinnett SS, Bhatti MT. Diagnostic Algorithm for Patients With Suspected Giant Cell Arteritis. J Neuroophthalmol. 2015 Sep;35(3):246–53.
El-Dairi, Mays A., et al. “Diagnostic Algorithm for Patients With Suspected Giant Cell Arteritis.J Neuroophthalmol, vol. 35, no. 3, Sept. 2015, pp. 246–53. Pubmed, doi:10.1097/WNO.0000000000000234.
El-Dairi MA, Chang L, Proia AD, Cummings TJ, Stinnett SS, Bhatti MT. Diagnostic Algorithm for Patients With Suspected Giant Cell Arteritis. J Neuroophthalmol. 2015 Sep;35(3):246–253.

Published In

J Neuroophthalmol

DOI

EISSN

1536-5166

Publication Date

September 2015

Volume

35

Issue

3

Start / End Page

246 / 253

Location

United States

Related Subject Headings

  • ROC Curve
  • Platelet Count
  • Ophthalmology & Optometry
  • Middle Aged
  • Male
  • Longitudinal Studies
  • Humans
  • Giant Cell Arteritis
  • Female
  • Diagnostic Techniques, Ophthalmological