A prospective study was carried out from August 2010 to August 2014 in the community of Fengyutan (China). Six hundred and twenty two T2D subjects were collected. The incidence density of diabetic retinopathy (DR) was 1.81% person-year (95% confidence interval, CI: 1.21–2.43% person-year). After a Cox regression model analysis and adjusted confounding factors, independent predictors related to the incidence of DR including male gender (adjusted hazard ratios, aHR: 1.47, 95% CI: 1.21–1.62), with hypertension (aHR: 1.49, 95%: 1.12–1.73), duration of diabetes > 10 years (aHR: 2.28, 95%: 2.05–2.42), uncontrolled diabetes (aHR: 1.76, 95%: 1.41–2.01), total cholesterol ≥ 200 mg/dL (aHR: 1.54, 95%: 1.34–1.72) and HbA1c ≥ 7% (mmol/mol) (aHR: 2.12, 95%: 1.87–2.32). Duration of T2D revealed the significantly dose-response relationship to the onset of DR. The incidence density of DR in the Chinese community was relatively low in comparison with other studies. More attention should be paid to the T2D patients, especially of male gender, with hypertension, longer duration of diabetes, uncontrolled diabetes, total cholesterol ≥ 200mg/dL and HbA1c ≥ 7% (mmol/mol).
ObjectiveTo describe the telescreening model and assess the prevalence of ocular fundus pathology in patients with type 2 diabetes within a Chinese urban community.DesignCommunity-based cross-sectional study.SettingHealthcare centre of Fengyutan Community, Shenyang, China.ParticipantsA total 528 patients (287 females) with type 2 diabetes mellitus (DM) were randomly recruited using health files from the healthcare centre of Fengyutan community between 8 October and 20 November 2012.Main outcome measuresSigns of any diabetic retinopathy (DR), signs of glaucoma and signs of age-related macular degeneration (AMD).ResultsThe main ocular fundus pathologies were DR (75 patients, 14.20%), 65 (86.67%) cases of which were newly detected, AMD (57 patients, 10.79%) and glaucoma (63 patients, 11.93%). The risk factors for fundus pathology were long duration of diabetes (OR 2.31, 95% CI 1.87 to 2.56), and higher fasting plasma glucose (OR 3.64, 95% CI 1.81 to 5.21) and glycated haemoglobin (HbA1c) levels (OR 3.83, 95% CI 1.87 to 6.35).ConclusionsThere was a high prevalence of fundus pathology among patients with type 2 diabetes, and in most of the cases, this was newly detected. Community screening for fundus pathology among patients with a long duration of type 2 diabetes and high fasting plasma glucose and HbA1c levels using a telescreening model will provide an effective strategy for the prevention and treatment of fundus pathology.
ObjectiveTo investigate the relationship between metabolic syndrome (MS) and the prevalence of retinopathy.DesignA cross-sectional study was carried out from August 2013 to September 2014 in Fengyutan Sub-District.Primary and secondary outcome measuresA total of 1163 eligible participants attended. All the participants were subjected to stereo fundus photography to detect retinopathy. The discrepancy of prevalence of retinopathy in different participants was described.ResultsThe prevalence of retinopathy was 9.64% in patients with MS and 3.91% in patients without MS. A higher prevalence of retinopathy with proliferative diabetic retinopathy was found in patients with MS. In multiple logistic regression analysis, independent risk factors for any retinopathy in patients with MS were longer diabetes duration (OR 1.07; 95% CI 1.04 to 1.10, per year increase), higher systolic blood pressure (SBP) (OR 1.16; 95% CI 1.09 to 1.29, per 10 mm Hg increase), higher diastolic blood pressure (DBP) (OR 1.24; 95% CI 1.12 to 1.35, per 10 mm Hg increase), higher fasting plasma glucose (OR 1.07; 95% CI 1.02 to 1.11, per 10 mg/dL increase), higher 2 h postprandial plasma glucose (OR 1.17; 95% CI 1.12 to 1.21, per 10 mg/dL increase), and higher haemoglobin A1c (HbA1c) (OR 1.23; 95% CI 1.13 to 1.34, per % increase). Similar independent risk factors, except for DBP, were found for any retinopathy in patients without MS.ConclusionsThe presence of MS components, hyperglycaemia (fasting glucose and HbA1c) and hypertension (SBP and DBP), are significantly associated with the prevalence of retinopathy.
In order to induce the shift in consumer behavior necessary for the mitigation of diet-related diseases, front-of-package labels (FoPL) such as the Nutri-Score that support consumers in their efforts to identify nutritionally valuable products during grocery shopping have been found to be effective; however, they remain non-compulsory in most regions. Counter-intuitively, a similar stream of research on digital web-based FoPL does not yet exist, even though such digital labels hold several advantages over physical labels. Digital FoPL can provide scalable and personalized interventions, are easier to implement than physical labels, and are especially timely due to the recent increase in online grocery shopping. The goal of this study was to demonstrate the technical feasibility and intervention potential of novel, scalable, and passively triggered health behavior interventions distributed via easy-to-install web browser extensions designed to support healthy food choices via the inclusion of digital FoPL in online supermarkets. To that end, we developed a Chrome web browser extension for a real online supermarket and evaluated the effect of this digital food label intervention (i.e., display of the Nutri-Score next to visible products) on the nutritional quality of individuals’ weekly grocery shopping in a randomized controlled laboratory trial (N = 135). Compared to the control group, individuals exposed to the intervention chose products with a higher nutritional quality (e.g., 8% higher healthy trolley index (HETI), 3.3% less sugar, 7.5% less saturated fat). In particular, users with low food literacy seemed to benefit from the digital FoPL (e.g., 11% higher HETI, 10.5% less sugar, 5.5% less saturated fat). Furthermore, participants exposed to the food label advocated its introduction more strongly than the control group (p = 0.081). Consumers worldwide could easily install such applications to display digital food labels on their end devices, and would thus not have to wait for stakeholders in the food industry to eventually reach consensus on mandatory food label introduction.
Recent studies have demonstrated the potential of OCTA retinal imaging for the discovery of biomarkers of vascular disease of the eye and other organs. Furthermore, advances in deep learning have made it possible to train algorithms for the automated detection of such biomarkers. However, two key limitations of this approach are the need for large numbers of labeled images to train the algorithms, which are often not met by the typical single-centre prospective studies in the literature, and the lack of interpretability of the features learned during training. In the current study, we developed a network analysis framework to characterise retinal vasculature where geometric and topological information are exploited to increase the performance of classifiers trained on tens of OCTA images. We demonstrate our approach in two different diseases with a retinal vascular footprint: diabetic retinopathy (DR) and chronic kidney disease (CKD). Our approach enables the discovery of previously unreported retinal vascular morphological differences in DR and CKD, and demonstrate the potential of OCTA for automated disease assessment.
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