Abstract 10113: Validation of a Deep-Learning-Based Retinal Biomarker in the Prediction of Cardiovascular Disease: Data From UK Biobank

Introduction: Currently in the United Kingdom, cardiovascular disease (CVD) risk assessment is based on the QRISK3 score, with a benchmark of 10% for 10-year CVD risk determining clinical intervention. Yet, effects on clinical practice are limited and the barriers call for a simple, non-invasive risk stratification tool. Retinal photography is becoming increasingly acceptable as a non-invasive imaging tool for CVD. Previously, we developed a novel CVD risk stratification system based on retinal photographs predicting future CVD risk. This study aimed to further validate our biomarker, Reti-CVD, 1) to detect risk group of ≥10% in 10-year CVD risk and 2 ) enhance risk assessment in individuals with QRISK3 of 7.5%-10% (termed as borderline-QRISK3 group) using the UK Biobank. Methods: RetiCVD scores were calculated and stratified into three risk groups based on optimized cut-off values from the UK Biobank. We used Cox proportional-hazards models to evaluate the ability of RetiCVD to predict CVD events in the general population. C-statistics was used to assess the prognostic value of adding RetiCVD to QRISK3 in borderline-QRISK3 group and three vulnerable subgroups. Results: Among 45,233 participants with no history of CVD, 6.7% had CVD events during the 11-year follow-up. RetiCVD was associated with an increased risk of CVD (adjusted hazard ratio [HR] 1.34 (95% confidence interval [CI], 1.26-1.42) with a 14.7% (95% CI, 13.6-15.9%) 10-year CVD risk in RetiCVD-high-risk group. The 10-year CVD risk of the borderline-QRISK3 group was greater than 10% in RetiCVD-high-risk group (12.8% in non-statin cohort [n=16240], 11.5% in stage 1 hypertension cohort [n=5102], and 14.9% in middle-aged cohort [n=11,474]). C statistics increased by 0.013 (0.010-0.017) in non-statin cohort, 0.017 (0.010-0.024) in stage 1 hypertension cohort, and 0.022 (0.017-0.027) in middle-aged cohort for CVD event prediction after adding RetiCVD to QRISK3. Conclusion: RetiCVD has the potential to identify individuals with ≥10% 10-year CVD risk who are likely to benefit from earlier, upstream preventative CVD interventions. For borderline-QRISK3 individuals, RetiCVD could be used as a risk enhancer tool to help improve discernment accuracy, especially in early vulnerable adult groups.