April 2010
Volume 51, Issue 13
Free
ARVO Annual Meeting Abstract  |   April 2010
Monitoring Progression of AMD Through Visual Function Loss
Author Affiliations & Notes
  • P. N. Dimitrov
    Center for Eye Research Australia, University of Melbourne, East Melbourne, Australia
  • A. J. Vingrys
    Optometry & Vision Sciences, University of Melbourne, Carlton, Australia
  • L. D. Robman
    Center for Eye Research Australia, University of Melbourne, East Melbourne, Australia
  • G. A. Makeyeva
    Center for Eye Research Australia, University of Melbourne, East Melbourne, Australia
  • K. Aung
    Center for Eye Research Australia, University of Melbourne, East Melbourne, Australia
  • M. Varsamidis
    Center for Eye Research Australia, University of Melbourne, East Melbourne, Australia
  • R. H. Guymer
    Center for Eye Research Australia, University of Melbourne, East Melbourne, Australia
  • Footnotes
    Commercial Relationships  P.N. Dimitrov, None; A.J. Vingrys, None; L.D. Robman, None; G.A. Makeyeva, None; K. Aung, None; M. Varsamidis, None; R.H. Guymer, None.
  • Footnotes
    Support  NHMRC Grant 350224 RHG/AJV
Investigative Ophthalmology & Visual Science April 2010, Vol.51, 4522. doi:
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      P. N. Dimitrov, A. J. Vingrys, L. D. Robman, G. A. Makeyeva, K. Aung, M. Varsamidis, R. H. Guymer; Monitoring Progression of AMD Through Visual Function Loss. Invest. Ophthalmol. Vis. Sci. 2010;51(13):4522.

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

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Abstract

Purpose: : To identify visual function test(s) that are sensitive and specific to detect AMD and monitor progression of the disease.

Methods: : A suite of visual function tests (static tests: achromatic 4Hz and 14Hz flickering and isoluminant Red and Blue thresholds; dynamic tests: photostress recovery and dark adaptation) was developed. Stimuli were presented on a high-resolution, calibrated CRT monitor driven by 8-bit Radeon video-card (0-255 LUT) on a 30 or 0 cd/sq.m background. Visual function was measured on 109 healthy participants and 221 people with AMD with VA better than 20/40 (no diabetes, glaucoma or cataract). Clinical stage of AMD was assessed using digital fundus photographs. Participants were tested biannually for three years to determine AMD progression rates.

Results: : We found significantly larger visual functions deficiency in people with AMD in all tests compared to age-matched controls. Although both static and dynamic tests had good AMD detection capacity, the dynamic parameters gave better diagnostic ability (95% [90.9 to 97.2] vs 61% [54.1 to 67.2], p<0.05). Our functional suite revealed a larger number of cases that deteriorated over three years compared with conventional visual acuity testing (37% [29.6 to 43.5] vs 9% [4.79 to 12.1], p<0.05). We found that the rate of deterioration in visual function increased with the worsening of visible clinical fundus features and that progression was monitored better with static tests than with dynamic tests (37% [30.2 to 44.1] vs 28% [17.9 to 29.0] respectively, p<0.05).

Conclusions: : Our visual function measurements were better able to track changes than was acuity testing. Although cone and rod recovery gave the best diagnostic capacity for AMD, our static tests (color and flicker thresholds) were better suited for the assessment of progression. These findings indicate that quantitative assessment of visual function is a clinically valuable approach in monitoring progression and can potentially be used to evaluate the efficacy of novel treatments for AMD.

Keywords: age-related macular degeneration • photoreceptors: visual performance • macula/fovea 
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