ArticleScientific reports2017
Retinopathy Signs Improved Prediction and Reclassification of Cardiovascular Disease Risk in Diabetes: A prospective cohort study.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed, 41 citations in OpenAlex.
- Development and validation of a predictive risk model based on retinal geometry for an early assessment of diabetic retinopathy.Frontiers in endocrinology · 2022Trial
- Machine learning derived retinal pigment score from ophthalmic imaging shows ethnicity is not biology.Nature communications · 2025Article
- Non-Invasive Retinal Vessel Analysis as a Predictor for Cardiovascular Disease.Journal of personalized medicine · 2024Review
- Prognostic potentials of AI in ophthalmology: systemic disease forecasting via retinal imaging.Eye and vision (London, England) · 2024Review
- Screening of Moyamoya Disease From Retinal Photographs: Development and Validation of Deep Learning Algorithms.Stroke · 2024Observational
- Urinary N-acetyl-β-d-glucosaminidase-creatine ratio is a valuable predictor for advanced diabetic kidney disease.Journal of clinical laboratory analysis · 2023Article
- Diabetic Retinopathy and Cardiovascular Disease: A Literature Review.Diabetes, metabolic syndrome and obesity : targets and therapy · 2023Review
- Deep learning-based fundus image analysis for cardiovascular disease: a review.Therapeutic advances in chronic disease · 2023Review
- Association of monocyte-lymphocyte ratio and proliferative diabetic retinopathy in the U.S. population with type 2 diabetes.Journal of translational medicine · 2022Article
- Retinal arteriolar tortuosity and fractal dimension are associated with long-term cardiovascular outcomes in people with type 2 diabetes.Diabetologia · 2021Article
- Impact of type 2 diabetes and microvascular complications on mortality and cardiovascular outcomes in a multiethnic Asian population.BMJ open diabetes research & care · 2021Article
- A deep-learning system for the assessment of cardiovascular disease risk via the measurement of retinal-vessel calibre.Nature biomedical engineering · 2021Article
- Detection of diabetic retinopathy using a fusion of textural and ridgelet features of retinal images and sequential minimal optimization classifier.PeerJ. Computer science · 2021Article
- Clinical and predictive significance of Plasma Fibrinogen Concentrations combined Monocyte-lymphocyte ratio in patients with Diabetic Retinopathy.International journal of medical sciences · 2021Observational
- Article
- Insights into Systemic Disease through Retinal Imaging-Based Oculomics.Translational vision science & technology · 2020Review
- Beyond the Lungs: Systemic Manifestations of Pulmonary Arterial Hypertension.American journal of respiratory and critical care medicine · 2020Review
- Thyroid stimulating hormone and free triiodothyronine are valuable predictors for diabetic nephropathy in patient with type 2 diabetes mellitus.Annals of translational medicine · 2018Article
- Clinical Significance of Hemostatic Parameters in the Prediction for Type 2 Diabetes Mellitus and Diabetic Nephropathy.Disease markers · 2018Article
Corrections and comments
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Authors and funding
11 authors at 6 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.