Retinopathy Signs Improved Prediction and Reclassification of Cardiovascular Disease Risk in Diabetes: A prospective cohort study.
CVD risk prediction in diabetics is imperfect, as risk models are derived mainly from the general population. We investigate whether the addition of retinopathy and retinal vascular caliber improve CVD prediction beyond established risk factors in persons with diabetes. We recruited participants from the Singapore Malay Eye Study (SiMES, 2004-2006) and Singapore Prospective Study Program (SP2, 2004-2007), diagnosed with diabetes but no known history of CVD at baseline. Retinopathy and retinal vascular (arteriolar and venular) caliber measurements were added to risk prediction models derived from Cox regression model that included established CVD risk factors and serum biomarkers in SiMES, and validated this internally and externally in SP2. We found that the addition of retinal parameters improved discrimination compared to the addition of biochemical markers of estimated glomerular filtration rate (eGFR) and high-sensitivity C-reactive protein (hsCRP). This was even better when the retinal parameters and biomarkers were used in combination (C statistic 0.721 to 0.774, p = 0.013), showing improved discrimination, and overall reclassification (NRI = 17.0%, p = 0.004). External validation was consistent (C-statistics from 0.763 to 0.813, p = 0.045; NRI = 19.11%, p = 0.036). Our findings show that in persons with diabetes, retinopathy and retinal microvascular parameters add significant incremental value in reclassifying CVD risk, beyond established risk factors.
Singapore Eye Research Institute, Singapore National Eye Center, Duke-NUS Medical School, 168751, Singapore.
Henrietta
H
Ho
Singapore Eye Research Institute, Singapore National Eye Center, Duke-NUS Medical School, 168751, Singapore.|Chinese University of Hong Kong Eye Centre, Department of Ophthalmology and Visual Sciences, Hong Kong.
Carol Y
CY
Cheung
Singapore Eye Research Institute, Singapore National Eye Center, Duke-NUS Medical School, 168751, Singapore.
Charumathi
C
Sabanayagam
Singapore Eye Research Institute, Singapore National Eye Center, Duke-NUS Medical School, 168751, Singapore.
Wanfen
W
Yip
Singapore Eye Research Institute, Singapore National Eye Center, Duke-NUS Medical School, 168751, Singapore.
Mohammad Kamran
MK
Ikram
Singapore Eye Research Institute, Singapore National Eye Center, Duke-NUS Medical School, 168751, Singapore.
Peng Guan
PG
Ong
Centre for Vision Research, University of Sydney, New South Wales 2006, Australia.
Paul
P
Mitchell
Health Promotion Board, National Registry of Diseases Office, 168937, Singapore.
Khuan Yew
KY
Chow
Singapore Eye Research Institute, Singapore National Eye Center, Duke-NUS Medical School, 168751, Singapore.
Ching Yu
CY
Cheng
National University Hospital Singapore, Division of Endocrinology, 119074, Singapore.
E Shyong
ES
Tai
Singapore Eye Research Institute, Singapore National Eye Center, Duke-NUS Medical School, 168751, Singapore.
Tien Yin
TY
Wong
D015415:Biomarkers / Q000097:blood; D002318:Cardiovascular Diseases / Q000097:blood / Q000453:epidemiology*; D003930:Diabetic Retinopathy / Q000097:blood / Q000150:complications*; D005260:Female; D006801:Humans; D008297:Male; D055806:Microvessels / Q000473:pathology; D008875:Middle Aged; D011446:Prospective Studies; D015203:Reproducibility of Results; D012171:Retinal Vessels / Q000473:pathology; D012307:Risk Factors
D015415:Biomarkers