Literature DB >> 3763131

Variability of quantitative automated perimetry in normal observers.

R A Lewis, C A Johnson, J L Keltner, P K Labermeier.   

Abstract

The test/retest variability in different regions of the visual field were evaluated in six commercially available automated threshold static perimeters using normal volunteers. Three of the devices were projection perimeters (Squid, Octopus 500, Humphrey Field analyzer) and three of them used light-emitting diode stimuli (Dicon 2000, Fieldmaster 50, Digilab 350). The authors' results show that, although some devices were better than others, all have some degree of variability. In addition, they found that there is increased variability from the central 10 degrees out to 30 degrees eccentricity for each perimeter.

Mesh:

Year:  1986        PMID: 3763131     DOI: 10.1016/s0161-6420(86)33647-9

Source DB:  PubMed          Journal:  Ophthalmology        ISSN: 0161-6420            Impact factor:   12.079


  15 in total

1.  On weighted visual field indices.

Authors:  A Heijl; G Lindgren; J Olsson; P Asman
Journal:  Graefes Arch Clin Exp Ophthalmol       Date:  1992       Impact factor: 3.117

2.  Variability of visual field measurements is correlated with the gradient of visual sensitivity.

Authors:  Harry J Wyatt; Mitchell W Dul; William H Swanson
Journal:  Vision Res       Date:  2007-02-23       Impact factor: 1.886

3.  MICROPERIMETRY AS A SCREENING TEST FOR HYDROXYCHLOROQUINE RETINOPATHY: The Hard-Risk-1 Study.

Authors:  Mustafa Iftikhar; Ramandeep Kaur; April Nefalar; Bushra Usmani; Saleema Kherani; Isra Rashid; Etienne Schönbach; Michelle Petri; Hendrik P N Scholl; Syed M Shah
Journal:  Retina       Date:  2019-03       Impact factor: 4.256

4.  Glaucoma detection with matrix and standard achromatic perimetry.

Authors:  Zvia Burgansky-Eliash; Gadi Wollstein; Avni Patel; Richard A Bilonick; Hiroshi Ishikawa; Larry Kagemann; William D Dilworth; Joel S Schuman
Journal:  Br J Ophthalmol       Date:  2007-01-10       Impact factor: 4.638

5.  Automated perimetry: using gaze-direction data to improve the estimate of scotoma edges.

Authors:  Harry J Wyatt
Journal:  Invest Ophthalmol Vis Sci       Date:  2011-07-29       Impact factor: 4.799

6.  The influence of stimulus parameters on the visual field indices by automated projection perimetry.

Authors:  M Dengler-Harles; J M Wild; M D Cole; E C O'Neill
Journal:  Graefes Arch Clin Exp Ophthalmol       Date:  1993-06       Impact factor: 3.117

7.  Progression of patterns (POP): a machine classifier algorithm to identify glaucoma progression in visual fields.

Authors:  Michael H Goldbaum; Intae Lee; Giljin Jang; Madhusudhanan Balasubramanian; Pamela A Sample; Robert N Weinreb; Jeffrey M Liebmann; Christopher A Girkin; Douglas R Anderson; Linda M Zangwill; Marie-Josee Fredette; Tzyy-Ping Jung; Felipe A Medeiros; Christopher Bowd
Journal:  Invest Ophthalmol Vis Sci       Date:  2012-09-25       Impact factor: 4.799

8.  Comparison of the visual field test of Glaufield Lite with Humphrey Field Analyser.

Authors:  Geeta Behera; Shradha Vijay Waghmare; Amala Ramasamy
Journal:  Int Ophthalmol       Date:  2022-08-10       Impact factor: 2.029

9.  A novel Bayesian adaptive method for mapping the visual field.

Authors:  Pengjing Xu; Luis Andres Lesmes; Deyue Yu; Zhong-Lin Lu
Journal:  J Vis       Date:  2019-12-02       Impact factor: 2.240

10.  Predicting Global Test-Retest Variability of Visual Fields in Glaucoma.

Authors:  Eun Young Choi; Dian Li; Yuying Fan; Louis R Pasquale; Lucy Q Shen; Michael V Boland; Pradeep Ramulu; Siamak Yousefi; Carlos Gustavo De Moraes; Sarah R Wellik; Jonathan S Myers; Peter J Bex; Tobias Elze; Mengyu Wang
Journal:  Ophthalmol Glaucoma       Date:  2020-12-11
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