Predicting visual disability in glaucoma with combinations of vision measures

Stephanie Lin, Aleksandra Mihailovic, Sheila K. West, Chris A. Johnson, David S. Friedman, Xiangrong Kong, Pradeep Y. Ramulu

Research output: Contribution to journalArticle

Abstract

Purpose: We characterized vision in glaucoma using seven visual measures, with the goals of determining the dimensionality of vision, and how many and which visual measures best model activity limitation. Methods: We analyzed cross-sectional data from 150 older adults with glaucoma, collecting seven visual measures: integrated visual field (VF) sensitivity, visual acuity, contrast sensitivity (CS), area under the log CS function, color vision, stereoacuity, and visual acuity with noise. Principal component analysis was used to examine the dimensionality of vision. Multivariable regression models using one, two, or three vision tests (and nonvisual predictors) were compared to determine which was best associated with Rasch-analyzed Glaucoma Quality of Life-15 (GQL-15) person measure scores. Results: The participants had a mean age of 70.2 and IVF sensitivity of 26.6 dB, suggesting mild-to-moderate glaucoma. All seven vision measures loaded similarly onto the first principal component (eigenvectors, 0.220–0.442), which explained 56.9% of the variance in vision scores. In models for GQL scores, the maximum adjusted-R2 values obtained were 0.263, 0.296, and 0.301 when using one, two, and three vision tests in the models, respectively, though several models in each category had similar adjusted-R2 values. All three of the best-performing models contained CS. Conclusions: Vision in glaucoma is a multidimensional construct that can be described by several variably-correlated vision measures. Measuring more than two vision tests does not substantially improve models for activity limitation. Translational Relevance: A sufficient description of disability in glaucoma can be obtained using one to two vision tests, especially VF and CS.

Original languageEnglish (US)
Article number22
JournalTranslational Vision Science and Technology
Volume7
Issue number2
DOIs
StatePublished - Mar 1 2018

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Glaucoma
Vision Tests
Contrast Sensitivity
Visual Fields
Visual Acuity
Color vision
Color Vision
Principal Component Analysis
Eigenvalues and eigenfunctions
Principal component analysis
Noise
Quality of Life

Keywords

  • Contrast sensitivity
  • Glaucoma
  • Quality of life
  • Vision testing
  • Visual fields

ASJC Scopus subject areas

  • Biomedical Engineering
  • Ophthalmology

Cite this

Predicting visual disability in glaucoma with combinations of vision measures. / Lin, Stephanie; Mihailovic, Aleksandra; West, Sheila K.; Johnson, Chris A.; Friedman, David S.; Kong, Xiangrong; Ramulu, Pradeep Y.

In: Translational Vision Science and Technology, Vol. 7, No. 2, 22, 01.03.2018.

Research output: Contribution to journalArticle

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abstract = "Purpose: We characterized vision in glaucoma using seven visual measures, with the goals of determining the dimensionality of vision, and how many and which visual measures best model activity limitation. Methods: We analyzed cross-sectional data from 150 older adults with glaucoma, collecting seven visual measures: integrated visual field (VF) sensitivity, visual acuity, contrast sensitivity (CS), area under the log CS function, color vision, stereoacuity, and visual acuity with noise. Principal component analysis was used to examine the dimensionality of vision. Multivariable regression models using one, two, or three vision tests (and nonvisual predictors) were compared to determine which was best associated with Rasch-analyzed Glaucoma Quality of Life-15 (GQL-15) person measure scores. Results: The participants had a mean age of 70.2 and IVF sensitivity of 26.6 dB, suggesting mild-to-moderate glaucoma. All seven vision measures loaded similarly onto the first principal component (eigenvectors, 0.220–0.442), which explained 56.9{\%} of the variance in vision scores. In models for GQL scores, the maximum adjusted-R2 values obtained were 0.263, 0.296, and 0.301 when using one, two, and three vision tests in the models, respectively, though several models in each category had similar adjusted-R2 values. All three of the best-performing models contained CS. Conclusions: Vision in glaucoma is a multidimensional construct that can be described by several variably-correlated vision measures. Measuring more than two vision tests does not substantially improve models for activity limitation. Translational Relevance: A sufficient description of disability in glaucoma can be obtained using one to two vision tests, especially VF and CS.",
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AB - Purpose: We characterized vision in glaucoma using seven visual measures, with the goals of determining the dimensionality of vision, and how many and which visual measures best model activity limitation. Methods: We analyzed cross-sectional data from 150 older adults with glaucoma, collecting seven visual measures: integrated visual field (VF) sensitivity, visual acuity, contrast sensitivity (CS), area under the log CS function, color vision, stereoacuity, and visual acuity with noise. Principal component analysis was used to examine the dimensionality of vision. Multivariable regression models using one, two, or three vision tests (and nonvisual predictors) were compared to determine which was best associated with Rasch-analyzed Glaucoma Quality of Life-15 (GQL-15) person measure scores. Results: The participants had a mean age of 70.2 and IVF sensitivity of 26.6 dB, suggesting mild-to-moderate glaucoma. All seven vision measures loaded similarly onto the first principal component (eigenvectors, 0.220–0.442), which explained 56.9% of the variance in vision scores. In models for GQL scores, the maximum adjusted-R2 values obtained were 0.263, 0.296, and 0.301 when using one, two, and three vision tests in the models, respectively, though several models in each category had similar adjusted-R2 values. All three of the best-performing models contained CS. Conclusions: Vision in glaucoma is a multidimensional construct that can be described by several variably-correlated vision measures. Measuring more than two vision tests does not substantially improve models for activity limitation. Translational Relevance: A sufficient description of disability in glaucoma can be obtained using one to two vision tests, especially VF and CS.

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