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.

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.

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.

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, respectively. There was a decrease in mean CUVAF area over time (change in total CUVAF area=-0.96 mm 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 per year (95% CI: -0.72 to -0.12) on average. Fourteen (1.5%) participants developed a pterygium.

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.

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http://dx.doi.org/10.1136/bjophthalmol-2021-320284DOI Listing

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