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ABSTRACT: Purpose
We evaluated racial/ethnic differences in primary open-angle glaucoma (POAG) defined by machine-learning-derived regional visual field (VF) loss patterns.Methods
Participants (N = 209,036) from the Nurses' Health Study (NHS; 1980-2018), Nurses' Health Study II (NHS2; 1989-2019), and Health Professionals Follow-Up Study (HPFS; 1986-2018) who were ≥40 years of age and free of glaucoma were followed biennially. Incident POAG cases (n = 1946) with reproducible VF loss were confirmed with medical records. Total deviation information from the earliest reliable glaucomatous VF for each POAG eye (n = 2564) was extracted, and machine learning analyses were used to identify optimal solutions ("archetypes") for regional VF loss patterns. Each POAG eye was assigned a VF archety
SUBMITTER: Kang JH
PROVIDER: S-EPMC9339699 | biostudies-literature | 2022 Jul
REPOSITORIES: biostudies-literature