Central Serous Chorioretinopathy is Associated with Increased Cardiovascular Risk: An Artificial Intelligence-Based Retinal Analysis.

PURPOSE The association between central serous chorioretinopathy (CSC) and cardiovascular disease (CVD) risk is debated. We aimed to investigate this link using a novel artificial intelligence (AI)-based retinal biomarker. METHODS This retrospective study included 109 CSC patients and 1028 non-CSC controls without pre-existing CVD. A validated AI software (Dr.Noon CVD) analyzed retinal images to generate a five-year CVD risk score. We used inverse probability of treatment weighting (IPTW) to balance for age and sex, and compared scores using a weighted t-test and multivariable linear regression. RESULTS After IPTW, the mean AI-derived Dr.Noon CVD score was significantly higher in the CSC group than in the control group (32.26 ± 8.09 vs. 29.87 ± 9.92; p = 0.024). In the weighted multivariable regression model, CSC was independently associated with a 2.14-point increase in the Dr.Noon CVD score (p < 0.001) after adjusting for age and gender. CONCLUSION CSC is associated with a higher AI-derived cardiovascular risk score. These findings support the concept of CSC as an ocular manifestation of systemic vascular pathology and suggest that its diagnosis warrants a broader assessment of a patient's cardiovascular health.