Incidence of interventions for diabetic retinopathy and serious lower-limb complications and its related factors in patients with type 2 diabetes using a real-world large claims database

2022 ◽  
Author(s):  
Ayako Yanagisawa-Sugita ◽  
Takehiro Sugiyama ◽  
Noriko Ihana-Sugiyama ◽  
Hirokazu Tanaka ◽  
Kenjiro Imai ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Diabetic Retinopathy ◽  
Real World ◽  
Lower Limb ◽  
Related Factors ◽  
Claims Database

scholarly journals Retinal venular tortuosity and fractal dimension predict incident retinopathy in adults with type 2 diabetes: the Edinburgh Type 2 Diabetes Study

Diabetologia ◽  
2021 ◽  
Author(s):  
Rachel B. Forster ◽  
◽  
Emmanuel Sandoval Garcia ◽  
Anniek J. Sluiman ◽  
Sheila M. Grecian ◽  
...  
Keyword(s):  
Risk Factors ◽  
Type 2 Diabetes ◽  
Diabetic Retinopathy ◽  
Fractal Dimension ◽  
Statistical Significance ◽  
Fractal Dimensions ◽  
Retinal Vessel ◽  
Related Factors ◽  
Discriminative Ability

Abstract Aims/hypothesis Our aim was to determine whether a range of prespecified retinal vessel traits were associated with incident diabetic retinopathy in adults with type 2 diabetes. Methods In the prospective observational cohort Edinburgh Type 2 Diabetes Study of 1066 adults with type 2 diabetes, aged 60–75 years at recruitment, 718 were free from diabetic retinopathy at baseline. Baseline retinal traits including vessel widths, tortuosity (curvature) and fractal dimensions (network complexity), were quantified using fundus camera images and semiautomated software, and analysed using logistic regression for their association with incident diabetic retinopathy over 10 years. Results The incidence of diabetic retinopathy was 11.4% (n = 82) over 10 years. After adjustment for a range of vascular and diabetes-related risk factors, both increased venular tortuosity (OR 1.51; 95% CI 1.15, 1.98; p = 0.003) and decreased fractal dimension (OR 0.75; 95% CI 0.58, 0.96; p = 0.025) were associated with incident retinopathy. There was no evidence of an association with arterial tortuosity, and associations between measurements of vessel widths and retinopathy lost statistical significance after adjustment for diabetes-related factors and vascular disease. Adding venular tortuosity to a model including established risk factors for diabetic retinopathy (HbA1c, BP and kidney function) improved the discriminative ability (C statistic increased from 0.624 to 0.640, p = 0.013), but no such benefit was found with fractal dimension. Conclusions/interpretation Increased retinal venular tortuosity and decreased fractal dimension are associated with incident diabetic retinopathy, independent of classical risk factors. There is some evidence that venular tortuosity may be a useful biomarker to improve the predictive ability of models based on established retinopathy risk factors, and its inclusion in further risk prediction modelling is warranted. Graphical abstract

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 Oxidative Stress and Its Related Factors in Latent Autoimmune Diabetes in Adults

2021 ◽  
Vol 2021 ◽  
pp. 1-6
Author(s):  
Jinjin Li ◽  
Yuan Zhang ◽  
Jingyun Zhang ◽  
Rongna Dong ◽  
Juanjuan Guo ◽  
...  
Keyword(s):  
Oxidative Stress ◽  
Blood Pressure ◽  
Type 2 Diabetes ◽  
Diabetic Retinopathy ◽  
Healthy Volunteers ◽  
Autoimmune Diabetes ◽  
Short Term ◽  
Related Factors ◽  
Latent Autoimmune Diabetes

Aims. Few research was reported to explore oxidative stress in individuals with latent autoimmune diabetes in adults (LADA). Therefore, our goal is to study oxidative stress and related factors in LADA patients. Methods. In this study, 250 Chinese inpatients were diagnosed with LADA ( n = 110 ) and type 2 diabetes mellitus ( n = 140 ) and 140 healthy volunteers were recruited. Moreover, individuals with LADA were followed for 6 months to evaluate whether short-term glycemic control during hospitalization can improve oxidative stress. Clinical and laboratory measurements of height, weight, blood pressure, glycosylated hemoglobin (HbA1c), blood lipids, 8-isoprostaglandin F2α (8-iso-PGF2α), and superoxide dismutase (SOD) were performed. Stepwise multiple regression analyses were used to assess factors that related to oxidative stress in individuals with LADA. Results. Compared with patients with type 2 diabetes, individuals with LADA have better oxidative stress and worse oxidative stress than healthy volunteers. After multiple regression analyses, systolic blood pressure, HbA1c, duration of diabetes, and diabetic retinopathy were associated with 8-iso-PGF2α and HbA1c. Diabetic retinopathy and diabetic ketosis were associated with SOD in individuals with LADA. Our results also revealed that, after 6 months of follow-up, oxidative stress was improved to some extent in persons with LADA. Conclusions. Our results show that compared with type 2 diabetes, LADA means less oxidative stress, and compared with healthy volunteers, it means more oxidative stress. Systolic blood pressure, HbA1c, duration of diabetes, diabetic retinopathy, and ketosis were associated with oxidative stress in individuals with LADA. Furthermore, short-term glycemic control can improve oxidative stress to some extent in individuals with LADA.

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