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A new nomogram-based tool predicts retinopathy risk using clinical data from a multi-ethnic cohort of 2,447 adults without retinopathy at baseline.
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Over a mean follow-up of just over three years, 5.9% of participants developed retinopathy, indicating risk extends beyond traditional diabetic populations.
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The combination model achieved better discrimination (AUC 0.75) compared to the baseline model (AUC 0.64), improving sensitivity and specificity.
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Key predictors of retinopathy included body mass index, waist-to-hip ratio, triglyceride levels, blood pressure, and hypertension history.
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The study highlights ethnic variations in retinopathy incidence, suggesting the need for tailored screening approaches in diverse populations.
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