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Shrinivas Pundlik, Archana Nigalye, Raviv Katz, Gang Luo, Deeba Husain; Using smartphone to measure dark adaptation in patients with AMD. Invest. Ophthalmol. Vis. Sci. 2020;61(7):936.
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© ARVO (1962-2015); The Authors (2016-present)
There is increasing evidence of the role of dark adaptation (DA) as a functional biomarker in age-related macular degeneration (AMD). Previously, feasibility of using a mobile device for DA measurement in normal vision (NV) adults was demonstrated by our group. In this study, we evaluated its effectiveness in measuring DA in AMD patients, with the expectation that delays in DA will be observed in AMD patients compared to age-similar NV subjects with no retinal disease.
A custom developed mobile application on Samsung Galaxy S8 smartphone was used for DA measurement. The device was placed at a reading distance in a dark room. Initial bleaching was achieved by presenting a bright white screen with a luminance of 300 Cd/m2. A flashing stimulus (λ = 455nm) of 1.5° with progressively reducing luminance was shown 8° inferior to the fixation target. The subjects tapped on the device screen if the stimulus was visible and the response was logged in the device. After testing, the data were exported to a computer to obtain DA characteristics, and area under the rod-mediated component of the DA characteristics (RAUC) was computed, with lower values indicating faster rod recovery. AMD patients and NV subjects with a visual acuity (VA) of 20/40 or better were included. Testing was done monocularly with the fellow eye patched. Data are reported for 11 AMD patients (2 early, 8 intermediate, and 1 late stage) and 11 age-similar NV subjects (>50 years of age) without any known AMD diagnosis. 1 AMD subject withdrew and was excluded from the analysis. Normalized RAUC was compared between the subject groups using Wilcoxon rank sum test.
There was no significant difference in the mean ages of the NV and AMD subject groups (mean ± std. years, NV: 66.5±11.1, AMD: 70.8±6.27; p=0.22). The normalized RAUC was significantly higher in AMD compared to the NV group ([median, inter-quartile range, min., max.], NV: [0.114, 0.045, 0.072, 0.276], AMD: [0.231, 0.085, 0.148, 0.364]; p=0.001). VA and RAUC were not correlated in AMD patients (ρ=0.31, p=0.36). For AMD detection, the sensitivity was 100% and specificity was 82% at 0.14 RAUC threshold.
Measurements with the smartphone showed significant delays corresponding to rod mediated DA component in AMD patients compared to age-similar NV subjects, indicating the clinical potential of using mobile device based DA measurements for AMD screening.
This is a 2020 ARVO Annual Meeting abstract.
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