September 2016
Volume 57, Issue 12
Open Access
ARVO Annual Meeting Abstract  |   September 2016
Comparison of contrast sensitivity, visual acuity, and the contrast sensitivity function as predictors of gait in glaucoma
Author Affiliations & Notes
  • Angeline Michelle Nguyen
    Johns Hopkins University/ Wilmer Eye Institute, Baltimore, Maryland, United States
  • Aleksandra Mihailovic
    Johns Hopkins University/ Wilmer Eye Institute, Baltimore, Maryland, United States
    Dana Center for Preventive Ophthalmology, Baltimore, Maryland, United States
  • David S Friedman
    Johns Hopkins University/ Wilmer Eye Institute, Baltimore, Maryland, United States
    Dana Center for Preventive Ophthalmology, Baltimore, Maryland, United States
  • Pradeep Y Ramulu
    Johns Hopkins University/ Wilmer Eye Institute, Baltimore, Maryland, United States
    Dana Center for Preventive Ophthalmology, Baltimore, Maryland, United States
  • Footnotes
    Commercial Relationships   Angeline Nguyen, None; Aleksandra Mihailovic, None; David Friedman, None; Pradeep Ramulu, None
  • Footnotes
    Support  NIH R01 EY022976-01; Research to prevent blindness
Investigative Ophthalmology & Visual Science September 2016, Vol.57, 1953. doi:
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    • Get Citation

      Angeline Michelle Nguyen, Aleksandra Mihailovic, David S Friedman, Pradeep Y Ramulu; Comparison of contrast sensitivity, visual acuity, and the contrast sensitivity function as predictors of gait in glaucoma. Invest. Ophthalmol. Vis. Sci. 2016;57(12):1953.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : To investigate whether the contrast sensitivity function (CSF), a measure combining visual acuity (VA) and contrast sensitivity (CS), is better at predicting gait parameters than CS or VA alone.

Methods : 211 patients with varying degrees of glaucoma damage underwent assessment of CSF using the quick CSF method (Adaptive Sensory Technology), CS using the MARS chart, and VA using the ETDRS chart. qCSF, CS, and VA data were converted to area under log CSF (AULCSF), logCS, and logMAR, respectively. Gait measurements were collected as the average of 4 normal walking trials using the GAITRite Electronic Walkway system (CIR System Inc.). R2 values of linear regression models were used to determine the extent to which vision measures captured variability in the gait parameter of interest, while controlling for age, sex, race, comorbidities, and polypharmacy.

Results : AULCSF was significantly associated (p<0.05) with 5 gait measures (step count, stride length, step length, base of support, and step length difference between feet), with R2 values ranging from 5%-29%. By comparison, logCS was associated with only 3 gait measures (step count, base of support, and step length difference), while logMAR VA was associated 9 gait measures (those mentioned for AULCSF plus swing time, step time, single support time, and cadence). Of the 3 gait measures demonstrating a significant association with both AULCSF and logCS, R2 values were all similar (within a range of 1%). For the 5 gait parameters demonstrating a significant association for both AULCSF and logMAR VA (step count, stride length, step length, base of support, and step length difference), model R2 values was more than 1% higher when AULCSF was the visual predictor for base of support, while R2 values were within 0.8% for the remaining models.

Conclusions : CSF, CS, and VA all demonstrate an impact of glaucoma on gait, though different gait parameters show inconsistent associations when different measures of vision are employed. More work is required to understand the specific visual features most likely to account for functional impairments in eye disease.

This is an abstract that was submitted for the 2016 ARVO Annual Meeting, held in Seattle, Wash., May 1-5, 2016.

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