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Liara Hirota, MARCO SANTOS ALMEIDA, Roberta Pereira de Almeida Manzano, Ronaldo Yuiti Sano; Analysis of foveal thickness in patients with oculocutaneous albinism using OCT with eyetracker. Invest. Ophthalmol. Vis. Sci. 2018;59(9):1110.
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© ARVO (1962-2015); The Authors (2016-present)
Compare the foveal thickness (FT) of patients with oculocutaneous albinism (OCA) and patients with no ocular abnormalities and correlate FT with age, visual acuity (VA), spherical equivalent (SE), iris transparency degree and retina transparency degree.
This was an observational, prospective and analytical study that evaluated the foveal thickness by the Optical Coherence Tomography (OCT) Angiography Avanti XR with eye tracker RTVue® in 60 eyes of individuals with OCA (mean age of 33,3 years) and 52 eyes of individuals with no ocular abnormalities (mean age of 30,92 years). Three images of each eye were captured in the Retina Map mode 6mm x 6mm from an area located topographically two disc diameters temporally to the optic disc and were analyzed by the same examiner (figure 1). All data were executed using the software SPSS v.20.0, adopting level of 5% for all analyzes.
Individuals with OCA had a mean FT of 273,58μm (standard error of 3,38 and p=0,003) and the control group a mean FT of 256,85 μm (standard error of 4,59 and p=0,003). The mean value of FT in the study group was 16,73μm higher than the mean average of control group with a confidence interval different between them (table 1). The confidence intervals of macular thickness between the groups was different and significant (p=0,003). The study demonstrates that there were statistical relevance between FT and the following variables (table 2): age (-0,309 and p< 0,05 ), iris transparency (0,384 and p< 0,01) and retinal transparency (0,269 and p< 0,05).
Foveal thickness in patients with OCA is thicker than patients with no ocular abnormalities and there was a significant positive correlation with iris transparency, retinal transparency and a negative correlation with age.
This is an abstract that was submitted for the 2018 ARVO Annual Meeting, held in Honolulu, Hawaii, April 29 - May 3, 2018.
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