Using Cardiovascular Risk Scores to Predict and Prevent Serious Eye Diseases

A UCLA study finds cardiovascular risk scores predict future development of serious eye disease—most notably age-related macular degeneration and diabetic retinopathy—using data already in the primary care record. This matters for primary care and ophthalmology because these conditions are common, progressive, and often detected late. The investigators found cardiovascular risk scores associated with multiple retinal and optic nerve outcomes in adults, suggesting primary care risk workflows already capture information relevant to eye health. Integrating that signal into referral decisions could change when and whom clinicians send for ophthalmic evaluation, using existing cardiovascular-risk data to trigger earlier ophthalmology referral pathways.

The analysis used electronic health records from 35,909 adults aged 40–79 and applied the Pooled Cohort Equations (PCE) cardiovascular risk score to stratify participants into Low, Borderline, Intermediate, and High risk groups, with outcomes tracked over five to seven years. Models were adjusted for factors not included in the PCE, and primary ocular endpoints included age-related macular degeneration, diabetic retinopathy, glaucoma, retinal vein occlusion, and hypertensive retinopathy. Adults in the High-risk PCE group had markedly higher incidence rates versus the Low group—for example, roughly 6.2-fold greater risk for age-related macular degeneration and about 5.9-fold greater risk for diabetic retinopathy—while other outcomes showed graded increases across risk categories. These associations were large and consistent across follow-up intervals, with particularly strong predictive performance for diabetic retinopathy, hypertensive retinopathy, and age-related macular degeneration.

Current screening practice relies primarily on age-based referral triggers and routine diabetic retinopathy protocols. A risk-stratified model would repurpose cardiovascular risk scores to prioritize patients for earlier ophthalmic assessment. Advantages include earlier identification of at-risk individuals, use of data already captured during routine primary care visits, and seamless integration with EHR-embedded calculators and flagging systems. Limitations include potential false positives, the need to recalibrate scores across diverse populations, and the risk of increasing referrals beyond local ophthalmic capacity.