Lipid-lowering medication is associated with decreased risk of diabetic retinopathy and the need for treatment in patients with type 2 diabetes: A real-world observational analysis of a health claims database

2018 ◽  
Vol 20 (10) ◽  
pp. 2351-2360 ◽  
Author(s):  
Ryo Kawasaki ◽  
Tsuneo Konta ◽  
Kohji Nishida
Keyword(s):  
Type 2 Diabetes ◽  
Diabetic Retinopathy ◽  
Real World ◽  
Health Claims ◽  
Lipid Lowering ◽  
Claims Database ◽  
Observational Analysis ◽  
Need For Treatment

scholarly journals Diabetic Retinopathy Screening Using Artificial Intelligence and Handheld Smartphone-Based Retinal Camera

2021 ◽  
pp. 193229682098556
Author(s):  
Fernando Korn Malerbi ◽  
Rafael Ernane Andrade ◽  
Paulo Henrique Morales ◽  
José Augusto Stuchi ◽  
Diego Lencione ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Type 2 Diabetes ◽  
Diabetic Retinopathy ◽  
Diagnostic Accuracy ◽  
Real World ◽  
False Negative ◽  
Portable Devices ◽  
High Burden ◽  
Screening Programs

Background: Portable retinal cameras and deep learning (DL) algorithms are novel tools adopted by diabetic retinopathy (DR) screening programs. Our objective is to evaluate the diagnostic accuracy of a DL algorithm and the performance of portable handheld retinal cameras in the detection of DR in a large and heterogenous type 2 diabetes population in a real-world, high burden setting. Method: Participants underwent fundus photographs of both eyes with a portable retinal camera (Phelcom Eyer). Classification of DR was performed by human reading and a DL algorithm (PhelcomNet), consisting of a convolutional neural network trained on a dataset of fundus images captured exclusively with the portable device; both methods were compared. We calculated the area under the curve (AUC), sensitivity, and specificity for more than mild DR. Results: A total of 824 individuals with type 2 diabetes were enrolled at Itabuna Diabetes Campaign, a subset of 679 (82.4%) of whom could be fully assessed. The algorithm sensitivity/specificity was 97.8 % (95% CI 96.7-98.9)/61.4 % (95% CI 57.7-65.1); AUC was 0·89. All false negative cases were classified as moderate non-proliferative diabetic retinopathy (NPDR) by human grading. Conclusions: The DL algorithm reached a good diagnostic accuracy for more than mild DR in a real-world, high burden setting. The performance of the handheld portable retinal camera was adequate, with over 80% of individuals presenting with images of sufficient quality. Portable devices and artificial intelligence tools may increase coverage of DR screening programs.

scholarly journals Association between spousal diabetes status and diabetic retinopathy in Chinese patients with type 2 diabetes

2019 ◽  
Vol 16 (5) ◽  
pp. 474-477
Author(s):  
Mei Yang ◽  
Yu Liu ◽  
Cuihong Wen ◽  
Beirui Wu ◽  
Xu Wan ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Diabetic Retinopathy ◽  
Confidence Interval ◽  
Odds Ratio ◽  
Chinese Patients ◽  
Lipid Lowering ◽  
Fundus Photography ◽  
Cross Sectional ◽  
Diabetes Status

Purpose: To evaluate the association between spousal diabetes status and the prevalence of diabetic retinopathy in Chinese patients with type 2 diabetes. Methods: A cross-sectional community-based study was performed in 1510 patients with type 2 diabetes in Shanghai, China. Non-mydriatic digital fundus photography was used to detect diabetic retinopathy. Spousal diabetes status was assessed using a standardised interview questionnaire. Results: The prevalence of diabetic retinopathy was significantly lower in patients who had diabetic spouses, compared with those who did not (20.2% vs 29.1%, p ⩽ 0.01). The fully adjusted odds ratio for diabetic retinopathy in those had diabetic spouses was decreased by 36% (odds ratio = 0.64, 95% confidence interval = 0.42–1.00, p = 0.048). The negative correlation between spousal diabetes status and diabetic retinopathy was presented in patients with the duration of diabetes ⩾ 10 years, those with HbA1c ⩾ 7% and those not using lipid-lowering drugs (odds ratio = 0.31, 95% confidence interval = 0.13–0.74, p = 0.0082; odds ratio = 0.50, 95% confidence interval = 0.27–0.94, p = 0.031; odds ratio = 0.58, 95% confidence interval = 0.37–0.92, p = 0.021, respectively). Conclusion: We demonstrated that spousal diabetes was associated with a lower diabetic retinopathy prevalence in Chinese patients with type 2 diabetes.

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