Literature DB >> 14522760

Evaluating several sources of variability for standard and SWAP visual fields in glaucoma patients, suspects, and normals.

Eytan Z Blumenthal1, Pamela A Sample, Charles C Berry, Alexander C Lee, Christopher A Girkin, Linda Zangwill, Joseph Caprioli, Robert N Weinreb.   

Abstract

PURPOSE: To quantify factors affecting test-retest variability of threshold measurements over a series of 3 serial visual fields (VF).
DESIGN: Prospective comparative observational study. PARTICIPANTS: Forty-one normals, 10 suspects and 35 stable glaucoma patients.
METHODS: All subjects performed 3 standard and 3 short-wavelength automated perimetry (SWAP) VFs. At each VF location, severity (defined as age-corrected total deviation) and test-retest variability (TRV), defined as the standard deviation of 3 serial threshold values, were calculated. A multiple regression model (constructed separately for standard VF and SWAP) incorporated 13 factors: severity, location, eccentricity, study group, diagnosis, superior versus inferior hemifield, nasal versus temporal hemifield, one-versus-two thresholds, age, mean pupil size, pupil size variability, between-subject variation, and residual variation. MAIN OUTCOME MEASURES: Variability in threshold sensitivity VF values.
RESULTS: Mean TRV (+/- standard deviation) for normal, suspect and glaucoma eyes, respectively, was: 1.28 +/- 0.87, 1.53 +/- 1.04 and 2.20 +/- 1.79 dB for standard VF, and 1.87 +/- 1.35, 1.86 +/- 1.24 and 2.68 +/- 1.85 dB for SWAP. The contribution of each factor to the model for standard VF and SWAP (SWAP in parentheses) were: severity 15.5% (6.9%); location 2.7% (4.1%); eccentricity 1.1% (0.64%); diagnosis 2.9% (5.9%); "superior versus inferior" hemifield 0.17% (1.7%); "nasal versus temporal" hemifield 0.06% (0.02%); one-versus-two thresholds 0.04% (0.16%); age 0.1% (0.06%); mean pupil size 0.59% (0.1%); pupil size variability 3.2% (2.8%); between-subject 8.0% (13.5%) and residual variation 61.0% (66.6%). Excluding between-subject and residual variation, the 11-factor model was able to account for less than one third of the variability seen in both standard VF and SWAP.
CONCLUSIONS: Severity of defect and between subject variation exerted the largest effect on TRV. However, even if all 11 factors could be adjusted for, it would reduce the magnitude of TRV by only 30%. More work is needed to reduce the remaining variability inherent in psychophysical testing and to better understand the intrinsic physiological variability present both in healthy and diseased eyes. It is possible that a larger number of VFs used for the calculation of TRV might further reduce the magnitude of the remaining variability found in this study.

Entities:  

Mesh:

Year:  2003        PMID: 14522760     DOI: 10.1016/S0161-6420(03)00541-4

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


  22 in total

1.  Spatial pattern of glaucomatous visual field loss obtained with regionally condensed stimulus arrangements.

Authors:  Ulrich Schiefer; Eleni Papageorgiou; Pamela A Sample; John P Pascual; Bettina Selig; Elke Krapp; Jens Paetzold
Journal:  Invest Ophthalmol Vis Sci       Date:  2010-06-10       Impact factor: 4.799

2.  The development of a decision analytic model of changes in mean deviation in people with glaucoma: the COA model.

Authors:  Steven M Kymes; Dennis L Lambert; Paul P Lee; David C Musch; Carla J Siegfried; Sameer V Kotak; Dustin L Stwalley; Joel Fain; Chris Johnson; Mae O Gordon
Journal:  Ophthalmology       Date:  2012-04-25       Impact factor: 12.079

Review 3.  Detection of visual field progression in glaucoma with standard achromatic perimetry: a review and practical implications.

Authors:  Kouros Nouri-Mahdavi; Nariman Nassiri; Annette Giangiacomo; Joseph Caprioli
Journal:  Graefes Arch Clin Exp Ophthalmol       Date:  2011-08-26       Impact factor: 3.117

4.  Comparison between broadband and monochromatic photopic negative response in full-field electroretinogram in controls and subjects with primary open-angle glaucoma.

Authors:  Aniruddha Banerjee; Mona Khurana; Ramya Sachidanandam; Parveen Sen
Journal:  Doc Ophthalmol       Date:  2019-01-12       Impact factor: 2.379

5.  Variability in short-wavelength automated perimetry among peri- or postmenopausal women: a dependence on phyto-oestrogen consumption?

Authors:  Alvin Eisner; Shaban Demirel
Journal:  Acta Ophthalmol       Date:  2011-05       Impact factor: 3.761

Review 6.  Macular imaging with optical coherence tomography in glaucoma.

Authors:  Vahid Mohammadzadeh; Nima Fatehi; Adeleh Yarmohammadi; Ji Woong Lee; Farideh Sharifipour; Ramin Daneshvar; Joseph Caprioli; Kouros Nouri-Mahdavi
Journal:  Surv Ophthalmol       Date:  2020-03-19       Impact factor: 6.048

Review 7.  Diagnostic tools for glaucoma detection and management.

Authors:  Pooja Sharma; Pamela A Sample; Linda M Zangwill; Joel S Schuman
Journal:  Surv Ophthalmol       Date:  2008-11       Impact factor: 6.048

8.  Assessment of the reliability of standard automated perimetry in regions of glaucomatous damage.

Authors:  Stuart K Gardiner; William H Swanson; Deborah Goren; Steven L Mansberger; Shaban Demirel
Journal:  Ophthalmology       Date:  2014-03-12       Impact factor: 12.079

9.  Pointwise Methods to Measure Long-term Visual Field Progression in Glaucoma.

Authors:  Diana Salazar; Esteban Morales; Alessandro Rabiolo; Vicente Capistrano; Mark Lin; Abdelmonem A Afifi; Fei Yu; Kouros Nouri-Mahdavi; Joseph Caprioli
Journal:  JAMA Ophthalmol       Date:  2020-05-01       Impact factor: 7.389

10.  Quantification of Visual Field Variability in Glaucoma: Implications for Visual Field Prediction and Modeling.

Authors:  Alessandro Rabiolo; Esteban Morales; Abdelmonem A Afifi; Fei Yu; Kouros Nouri-Mahdavi; Joseph Caprioli
Journal:  Transl Vis Sci Technol       Date:  2019-10-17       Impact factor: 3.283

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.