Journal Article
Research Support, Non-U.S. Gov't
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Retinal vascular profile in predicting incident cardiometabolic diseases among individuals with diabetes.

OBJECTIVE: To determine the longitudinal associations between retinal vascular profile (RVP) and four major cardiometabolic diseases; and to quantify the predictive improvements when adding RVP beyond traditional risk factors in individuals with diabetes.

METHODS: Subjects were enrolled from the Singapore Epidemiology of Eye Disease (SEED) study, a multi-ethnic population-based cohort. Four incident cardiometabolic diseases, calculated over a ~ 6-year period, were considered: cardiovascular disease (CVD), hypertension (HTN), diabetic kidney disease (DKD), and hyperlipidemia (HLD). The RVP-vessel tortuosity, branching angle, branching coefficient, fractal dimension, vessel caliber, and DR status-was characterized at baseline using a computer-assisted program. Traditional risk factors at baseline included age, gender, ethnicity, smoking, blood pressure (BP), HbA1c, estimated glomerular filtration rate (eGFR), or cholesterol. The improvements in predictive performance when adding RVP (compared with only traditional risk factors) was calculated using several metrics including area under the receiver operating characteristics curve (AUC) and net reclassification improvement (NRI).

RESULTS: Among 1770 individuals with diabetes, incidences were 6.3% (n = 79/1259) for CVD, 48.7% (n = 166/341) for HTN, 14.6% (n = 175/1199) for DKD, and 59.4% (n = 336/566) for HLD. DR preceded the onset of CVD (RR 1.85[1.14;3.00]) and DKD (1.44 [1.06;1.96]). Narrower arteriolar caliber preceding the onset of HTN (0.84 [0.72;0.99]), and changes in arteriolar branching angle preceded the onset of CVD (0.78 [0.62;0.98]) and HTN (1.15 [1.03;1.29]). The largest predictive improvement was found for HTN with AUC increment of 3.4% (p = .027) and better reclassification of 11.4% of the cases and 4.6% of the controls (p = .008).

CONCLUSION: We found that RVPs improved the prediction of HTN in individuals with diabetes, but add limited information for CVD, DKD, and HLD predictions.

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