Literature DB >> 29784156

Lower ocular pulse amplitude with dynamic contour tonometry is associated with biopsy-proven giant cell arteritis.

Edsel Ing1, Christian Pagnoux2, Felix Tyndel3, Arun Sundaram3, Seymour Hershenfeld4, Paul Ranalli3, Shirley Chow2, Tran Le4, Carla Lutchman4, Susan Rutherford4, Kay Lam4, Harleen Bedi4, Nurhan Torun5.   

Abstract

OBJECTIVES: To determine the role of the ocular pulse amplitude (OPA) from Pascal dynamic contour tonometry in predicting the temporal artery biopsy (TABx) result in patients with suspected giant cell arteritis (GCA).
DESIGN: Prospective validation study. PARTICIPANTS: Adults aged 50 years or older who underwent TABx from March 2015 to April 2017.
METHODS: Subjects on high-dose glucocorticoids more than 14 days or without serology before glucocorticoid initiation were excluded. The OPA from both eyes was obtained and averaged just before TABx of the predominantly symptomatic side. The variables chosen for the a priori prediction model were age, average OPA, and C-reactive protein (CRP). Erythrocyte sedimentation rate (ESR), platelets, jaw claudication, and eye findings were also recorded. In this study, subjects with a negative biopsy were considered not to have GCA, and contralateral biopsy was performed if the clinical suspicion for GCA remained high. An external validation set (XVAL) was obtained.
RESULTS: Of 109 TABx, 19 were positive and 90 were negative. On univariate logistic regression, the average OPA had 0.60 odds for positive TABx (p = 0.03), with no statistically significant difference in age, sex, CRP, ESR, or jaw claudication. In suspected GCA, an OPA of 1 mm Hg had positive likelihood ratio 4.74 and negative likelihood ratio 0.87 for positive TABx. Multivariate regression of the prediction model using optimal mathematical transforms (inverse OPA, log CRP, age >65 years) had area under the receiver operating characteristic curve (AUROC) = 0.85 and AUROCXVAL = 0.81.
CONCLUSIONS: OPA is lower in subjects with biopsy-proven GCA and is a statistically significant predictor of GCA.
Copyright © 2018 Canadian Ophthalmological Society. Published by Elsevier Inc. All rights reserved.

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Year:  2017        PMID: 29784156     DOI: 10.1016/j.jcjo.2017.10.027

Source DB:  PubMed          Journal:  Can J Ophthalmol        ISSN: 0008-4182            Impact factor:   1.882


  3 in total

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

Authors:  Edsel B Ing; Neil R Miller; Angeline Nguyen; Wanhua Su; Lulu L C D Bursztyn; Meredith Poole; Vinay Kansal; Andrew Toren; Dana Albreki; Jack G Mouhanna; Alla Muladzanov; Mikaël Bernier; Mark Gans; Dongho Lee; Colten Wendel; Claire Sheldon; Marc Shields; Lorne Bellan; Matthew Lee-Wing; Yasaman Mohadjer; Navdeep Nijhawan; Felix Tyndel; Arun N E Sundaram; Martin W Ten Hove; John J Chen; Amadeo R Rodriguez; Angela Hu; Nader Khalidi; Royce Ing; Samuel W K Wong; Nurhan Torun
Journal:  Clin Ophthalmol       Date:  2019-02-21

2.  Comparison of Dynamic Contour Tonometry and Non-contact Tonometry in Older Patients Presenting with Headache or Vision Loss.

Authors:  Edsel Ing; Angela Zhang; Evan Michaelov; Wendy Wang
Journal:  Open Ophthalmol J       Date:  2018-06-22

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

Authors:  Kornelis S M van der Geest; Maria Sandovici; Elisabeth Brouwer; Sarah L Mackie
Journal:  JAMA Intern Med       Date:  2020-10-01       Impact factor: 21.873

  3 in total

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