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Conjunctival ultraviolet autofluorescence area decreases with age and sunglasses use.

Authors :
Lingham G
Kugelman J
Charng J
Lee SS
Yazar S
McKnight CM
Coroneo MT
Lucas RM
Brown H
Stevenson LJ
Mackey DA
Alonso-Caneiro D
Source :
The British journal of ophthalmology [Br J Ophthalmol] 2023 May; Vol. 107 (5), pp. 614-620. Date of Electronic Publication: 2021 Nov 23.
Publication Year :
2023

Abstract

Background: Conjunctival ultraviolet autofluorescence (CUVAF) is a method of detecting conjunctival damage related to ultraviolet radiation exposure. In cross-sectional studies, CUVAF area is positively associated with self-reported time spent outdoors and pterygium and negatively associated with myopia; however, longitudinal studies are scarce.<br />Aims: To use a novel deep learning-based tool to assess 8-year change in CUVAF area in young adults, investigate factors associated with this change and identify the number of new onset pterygia.<br />Methods: A deep learning-based CUVAF tool was developed to measure CUVAF area. CUVAF area and pterygium status were assessed at three study visits: baseline (participants were approximately 20 years old) and at 7-year and 8-year follow-ups. Participants self-reported sun protection behaviours and ocular history.<br />Results: CUVAF data were available for 1497 participants from at least one study visit; 633 (43%) participants had complete CUVAF data. Mean CUVAF areas at baseline and the 7-year and 8-year follow-ups were 48.4, 39.3 and 37.7 mm <superscript>2</superscript> , respectively. There was a decrease in mean CUVAF area over time (change in total CUVAF area=-0.96 mm <superscript>2</superscript> per year (95% CI: -1.07 to -0.86)). For participants who wore sunglasses ≥1/2 of the time, CUVAF area decreased by an additional -0.42 mm <superscript>2</superscript> per year (95% CI: -0.72 to -0.12) on average. Fourteen (1.5%) participants developed a pterygium.<br />Conclusions: In this young adult cohort, CUVAF area declined over an 8-year period. Wearing sunglasses was associated with a faster reduction in CUVAF area. Deep learning-based models can assist in accurate and efficient measurement of CUVAF area.<br />Competing Interests: Competing interests: None declared.<br /> (© Author(s) (or their employer(s)) 2023. No commercial re-use. See rights and permissions. Published by BMJ.)

Details

Language :
English
ISSN :
1468-2079
Volume :
107
Issue :
5
Database :
MEDLINE
Journal :
The British journal of ophthalmology
Publication Type :
Academic Journal
Accession number :
34815236
Full Text :
https://doi.org/10.1136/bjophthalmol-2021-320284