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The worldwide epidemic of diabetic retinopathy

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Abstract

Diabetic retinopathy (DR), a major microvascular complication of diabetes, has a significant impact on the world's health systems. Globally, the number of people with DR will grow from 126.6 million in 2010 to 191.0 million by 2030, and we estimate that the number with vision-threatening diabetic retinopathy (VTDR) will increase from 37.3 million to 56.3 million, if prompt action is not taken. Despite growing evidence documenting the effectiveness of routine DR screening and early treatment, DR frequently leads to poor visual functioning and represents the leading cause of blindness in working-age populations. DR has been neglected in health-care research and planning in many low-income countries, where access to trained eye-care professionals and tertiary eye-care services may be inadequate. Demand for, as well as, supply of services may be a problem. Rates of compliance with diabetes medications and annual eye examinations may be low, the reasons for which are multifactorial. Innovative and comprehensive approaches are needed to reduce the risk of vision loss by prompt diagnosis and early treatment of VTDR.
Current Ophthalmology
The worldwide epidemic of diabetic retinopathy
Yingfeng Zheng1,2, Mingguang He1, Nathan Congdon1
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www.ijo.in
DOI:
10.4103/0301-4738.100542
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
       



   


    
     


   


      

    



What is the Incidence of Diabetic
Retinopathy?

       
      
        
      

     



      


Has there been a Decline in the Prevalence/
Incidence of Diabetic Retinopathy among
those with Diabetes?







  
Zheng, et al.: Worldwide epidemic of diabetic retinopathy








     

  

      
        

What are the Risk Factors Associated with
Diabetic Retinopathy?

       
   

      
      

   


      

Is there a Socioeconomic Gradient in
Prevalence of Diabetic Retinopathy?
       
      
     

     
     


      
     
      
      



 


What are the Consequences of Diabetic
Retinopathy?
        
   
     
        
   

       
        



     

       










Challenges and Opportunities
Capacity
       
  
      
 

  



   





  
     
        
    
    



     


  
       
   


Sustainability




  
  


  
 
   
   
 

   




   


 
     
       


     

       
    
    
  





   
      




      

Key performance indicators

     




       
    




  
      
     
   

        

      
        







       


 
       
     


Physician-patient relationship
   


  
   
    
      


       
      
    


      






      
 


     

   
       
       

     
    
       


    

   


  
Zheng, et al.: Worldwide epidemic of diabetic retinopathy
The Way Forward




     


   


    
    


      






References
   

 
et al

 et al
    

        
    

 et al

 
 

        
et al  

  
et al

     

 
et al


        et al


 

           



           



 
et al
    

  

 
  
et al

 
 

    
  




      

 
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Cite this article as: Zheng Y, He M, Congdon N. The worldwide epidemic of
diabetic retinopathy. Indian J Ophthalmol 2012;60:428-31.
Source of Support: Dr. Zheng is supported by National Natural
Science Foundation of China 81100686. Dr. He is supported by National
Natural Science Foundation of China 30772393. Dr. Congdon is
supported by a Thousand Man grant from the Chinese government.
Conict of Interest: None declared.
Reproducedwithpermissionof thecopyrightowner.Further reproductionprohibitedwithoutpermission.
... The prevalence of diabetes is rising, and consequently, the concern for the complication of diabetic retinopathy (DR) has also increased (Zheng et al., 2012;Bandello et al., 2017). Globally, the number of people with DR is estimated to grow yearly, from 126.6 million in 2010 to 191.0 million by 2030, Zheng et al. (2012). ...
... The prevalence of diabetes is rising, and consequently, the concern for the complication of diabetic retinopathy (DR) has also increased (Zheng et al., 2012;Bandello et al., 2017). Globally, the number of people with DR is estimated to grow yearly, from 126.6 million in 2010 to 191.0 million by 2030, Zheng et al. (2012). Diabetic macular edema (DME) is one of the leading causes of vision loss in the working-age population (Klein, 2007). ...
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Background: Antiangiogenic therapy with anti-vascular endothelial growth factor (VEGF) is commonly used to treat diabetic macular edema (DME), which can reduce edema, improve vision, and prevent further visual loss. There is little head-to-head trial data to guide the selection of an individual VEGF inhibitor. Therefore, we aimed to investigate the efficacy and safety of anti-VEGF for patients with DME and to assess the differences between clinically relevant options by using network meta-analysis (NMA). Methods: MEDLINE, Embase, the Cochrane Library, Web of Science, Chinese Biomedical Literature Database, Wanfang, China National Knowledge Infrastructure, and VIP databases were searched for published randomized controlled trials (RCTs) from their inception to November 2020. We included RCTs of anti-VEGF drugs (intravitreal aflibercept (IVT-AFL), intravitreal ranibizumab (IVR), and intravitreal conbercept (IVC)) treating adult patients who were diagnosed with DME, regardless of stage or duration of the disease. We estimated summary odds ratios (ORs) and mean differences (MDs) with 95% credible intervals (CrIs) using a Bayesian NMA. This study’s registration number is CRD42021259335. Results: We identified 43 RCTs comprising 8,234 patients. Beneficial effects were observed in patients who used IVT-AFL compared with those who used other anti-VEGF therapies at 1-year follow-up on corrected visual acuity (BCVA) improvements (all patients: versus IVR: MD 2.83, 95% CrIs 1.64, 4.01, versus IVC: MD 2.41, 95% CrIs −0.52, 5.32; patients with worse baseline visual acuity (VA): versus IVR: MD 3.39, 95% CrIs 1.89, 4.9, versus IVC: MD 3.49, 95% CrIs 0.49, 6.44) and the proportion of patients with a gain of at least 15 Early Treatment Diabetic Retinopathy Study (ETDRS) letters (all patients: versus IVR: OR 1.55, 95% CrIs 1.11, 2.17, versus IVC: OR 2.78, 95% CrIs 1.23, 6.04; patients with worse baseline VA: versus IVR: OR 2.05, 95% CrIs 1.18, 3.58, versus IVC: OR 2.85, 95% CrIs 1.24, 6.41). The effect of improvement in BCVA was identified for IVT-AFL compared to intravitreal bevacizumab. Based on the surface under the cumulative ranking curve (SUCRA), IVT-AFL had the highest probability of being the most effective option (99.9% and 99.5% in terms of the two primary outcomes, respectively). At the 2-year follow-up, numerical differences were identified favoring IVT-AFL; however, they did not reach statistical significance when comparing IVT-AFL to IVR. In the analysis of adverse events, IVT-AFL showed a lower risk of incidence of ocular adverse events compared to other anti-VEGF therapies at 1-year follow-up (versus IVR: OR 0.45, 95% CrIs 0.28, 0.7; versus IVC: OR 0.36, 95% CrIs 0.21, 0.63). Conclusion: IVT-AFL resulted in greater beneficial effects on BCVA and a higher proportion of patients with a gain of at least 15 ETDRS letters compared to IVR or IVC one year after treatment (especially in DME patients with worse baseline VA). In addition, fewer ocular adverse events occurred in the IVT-AFL group compared to the IVR or IVC groups. After two years, there was insufficient evidence to identify which anti-VEGF has superior efficacy or safety. Clinical Trial Registration: https://www.crd.york.ac.uk/prospero/, PROSPERO; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021259335, CRD42021259335
... Another disease for which CAD systems can help by providing accurate early detection is diabetic retinopathy (DR). This condition is a typical development of diabetes, affecting the retina's small blood vessels, leading to vision deterioration [20]. The research described in [21] studies the offloading footwear to prevent and lower mortality rates in high-risk diabetic feet. ...
... The research described in [21] studies the offloading footwear to prevent and lower mortality rates in high-risk diabetic feet. A recent study has reported that DR affects the vision of 2.6 million people in the world [20,22]. Several retinal imaging systems can be utilized to detect the indication of diabetic retinopathy, including color fundus photography, fluorescein angiography, B-scan ultrasonography, and optical coherence tomography [23]. ...
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Deep learning approaches play a crucial role in computer-aided diagnosis systems to support clinical decision-making. However, developing such automated solutions is challenging due to the limited availability of annotated medical data. In this study, we proposed a novel and computationally efficient deep learning approach to leverage small data for learning generalizable and domain invariant representations in different medical imaging applications such as malaria, diabetic retinopathy, and tuberculosis. We refer to our approach as Incremental Modular Network Synthesis (IMNS), and the resulting CNNs as Incremental Modular Networks (IMNets). Our IMNS approach is to use small network modules that we call SubNets which are capable of generating salient features for a particular problem. Then, we build up ever larger and more powerful networks by combining these SubNets in different configurations. At each stage, only one new SubNet module undergoes learning updates. This reduces the computational resource requirements for training and aids in network optimization. We compare IMNets against classic and state-of-the-art deep learning architectures such as AlexNet, ResNet-50, Inception v3, DenseNet-201, and NasNet for the various experiments conducted in this study. Our proposed IMNS design leads to high average classification accuracies of 97.0%, 97.9%, and 88.6% for malaria, diabetic retinopathy, and tuberculosis, respectively. Our modular design for deep learning achieves the state-of-the-art performance in the scenarios tested. The IMNets produced here have a relatively low computational complexity compared to traditional deep learning architectures. The largest IMNet tested here has 0.95 M of the learnable parameters and 0.08 G of the floating-point multiply–add (MAdd) operations. The simpler IMNets train faster, have lower memory requirements, and process images faster than the benchmark methods tested.
... Providing care for people living with diabetes (PLWD) thus requires balancing diabetes management with management of its chronic complications. Diabetic retinopathy (DR) is the major ocular morbidity in diabetes, and there is strong epidemiologic evidence that its prevalence is increasing [5,6]. In common with other chronic diseases, the management of both conditions requires: promotion of healthy lifestyle, early detection, compliance to treatment, regular monitoring of treatment outcomes, active involvement of the patient and family in the care. ...
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Background: Good diabetes mellitus (diabetes) and diabetic retinopathy (DR) management depends on the strength of the health system, prompting us to conduct a health system assessment for diabetes and DR in Kenya. We used diabetes and DR as tracer conditions to assess the strengths and weaknesses in the health system, and potential interventions to strengthen the health system. In this paper, we report on the need and relevance of integration to strengthen diabetes and DR care. This theme emerged from the health system assessment. Methods: Using a mixed methods study design, we collected data from service providers in diabetes clinics and eye clinics in three counties, from key informants at national and county level, and from documents review. Results: There is interest in integration of diabetes and DR services to address discontinuity of care. We report the findings describing the context of integration, why integration is a goal and how these services can be integrated. We use the results to develop a conceptual framework for implementation. Conclusions: The principal rationale for integrated service provision is to address service gaps and to prevent complications of diabetes and DR. The stakeholder interest and the existing infrastructure can be leveraged to improve these health outcomes.
... The studies conducted from 2012 to 2020 estimate that, by 2040, diabetes will affect about 642 million adults overall the world. To that end, DR will affect one from every three people with diabetes [2,3]. ...
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Diabetic retinopathy (DR) is a serious disease that may cause vision loss unawares without any alarm. Therefore, it is essential to scan and audit the DR progress continuously. In this respect, deep learning techniques achieved great success in medical image analysis. Deep convolution neural network (CNN) architectures are widely used in multi-label (ML) classification. It helps in diagnosing normal and various DR grades: mild, moderate, and severe non-proliferative DR (NPDR) and proliferative DR (PDR). DR grades are formulated by appearing multiple DR lesions simultaneously on the color retinal fundus images. Many lesion types have various features that are difficult to segment and distinguished by utilizing conventional and hand-crafted methods. Therefore, the practical solution is to utilize an effective CNN model. In this paper, we present a novel hybrid, deep learning technique, which is called E-DenseNet. We integrated EyeNet and DenseNet models based on transfer learning. We customized the traditional EyeNet by inserting the dense blocks and optimized the resulting hybrid E-DensNet model’s hyperparameters. The proposed system based on the E-DenseNet model can accurately diagnose healthy and different DR grades from various small and large ML color fundus images. We trained and tested our model on four different datasets that were published from 2006 to 2019. The proposed system achieved an average accuracy (ACC), sensitivity (SEN), specificity (SPE), Dice similarity coefficient (DSC), the quadratic Kappa score (QKS), and the calculation time (T) in minutes (m) equal $$91.2\%$$ 91.2 % , $$96\%$$ 96 % , $$69\%$$ 69 % , $$92.45\%$$ 92.45 % , 0.883, and 3.5 m respectively. The experiments show promising results as compared with other systems. Graphical abstract
... Diabetic Retinopathy (DR) is a serious and dangerous disease and since the prevalence of DR is directly related to the increasing prevalence of diabetes, it is growing rapidly in different societies [1]. DR can damage the retinal blood vessels and ultimately leads to blindness. ...
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Diabetic Retinopathy (DR) caused by diabetes occurs as a result of changes in the retinal vessels and causes visual impairment. Microaneurysms (MAs) are the early clinical signs of DR, whose timely diagnosis can help detecting DR in the early stages of its development. It has been observed that MAs are more common in the inner retinal layers compared to the outer retinal layers in eyes suffering from DR. Optical Coherence Tomography (OCT) is a noninvasive imaging technique that provides a cross-sectional view of the retina and it has been used in recent years to diagnose many eye diseases. As a result, in this paper has attempted to identify areas with MA from normal areas of the retina using OCT images. This work is done using the dataset collected from FA and OCT images of 20 patients with DR. In this regard, firstly Fluorescein Angiography (FA) and OCT images were registered. Then the MA and normal areas were separated and the features of each of these areas were extracted using the Bag of Features (BOF) approach with Speeded-Up Robust Feature (SURF) descriptor. Finally, the classification process was performed using a multilayer perceptron network. For each of the criteria of accuracy, sensitivity, specificity, and precision, the obtained results were 96.33%, 97.33%, 95.4%, and 95.28%, respectively. Utilizing OCT images to detect MAsautomatically is a new idea and the results obtained as preliminary research in this field are promising .
... Other risk factors for diabetic retinopathy include dyslipidemia, a higher body mass index, puberty, pregnancy, and cataract surgery. Despite the importance of glycemic control in diminishing the progression of diabetic retinopathy, intensive glycemic control appeared to increase mortality among participants in the Action to Control Cardiovascular Risk in Diabetes trial, which raises concerns over the care of persons with type-2 diabetes who are at high risk of cardiovascular events, and highlights the need for close collaboration between diabetologists and ophthalmologists [13,[16][17][18][19][20]. ...
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Diabetes, a global health concern, affects the health of more than 500 million adults. The absence of Notch protein can cause an imbalance in the retinal vascular environment and cause retinal vascular disease. Long noncoding RNA (lncRNA) is known to be involved in the regulation of many signaling pathways. We hope to understand the specific mechanism of apoptosis in retinal vascular endothelial cells (RVECs) by exploring the regulatory effect of lncRNA on the Notch pathway. In this study, we found that RVECs treated with glucose showed increased levels of Notch transcript and protein expression. The lentiviral interference with Notch RNAi reversed this response. When Notch activity decreased, oxidative stress also decreased, accompanied by increased levels of Caspase-9 and Caspase-3 and an increased rate of apoptosis. Therefore, we believe that Notch is involved in the development of diabetic retinopathy and loss of expression promotes apoptosis of human RVECs. By inhibiting the Notch pathway, lncRNA promotes apoptosis of human RVECs in a high-glucose environment.
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Automatic diabetic retinopathy diagnostic methods are proposed to facilitate the examination process and act as the physician’s helper. Most of the traditional convolution neural network (CNN) algorithms use only spatial features for image category recognition. This approach may not be optimal for the screening diabetic retinopathy because the retinal images have generally the same feature maps with minor differences in spatial domain. We propose a new high level image understanding using a modified CNN architecture mixed with modified support vector domain description (SVDD) as a classifier. This new innovative architecture uses two pathways extracting features of the retinal images in both spatial and spectral domains. The standard pre-trained AlexNet is chosen for modification to avoid the time complexity of the training algorithms. In spite the advantages of the modified AlexNet with two pathways configuration and standard SVDD classification, the different SVDD kernel functions affect the performance of the proposed algorithm. By using the appropriate transformed data into two or three dimensional feature spaces, the proposed SVDD can obtain more flexible and more accurate image descriptions. Also, we compared the performance of our approach with that of the commonly used as classification methods such as K-Means, subtractive and FCM clustering. Our proposed architecture achieves more than 98% precision and sensitivity for two class classification.
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Diabetic retinopathy (DR) is characterized by microvascular changes including ischemia. Degradation and metabolic changes of various retinal cells occur during ischemia. Ischemic region containing more cells will lead to greater metabolic impairment. We analyzed the non-perfusion region (NPR) by integrating histologic mapping with ultra-widefield fluorescein angiography (UWF FA) images. We also investigated the correlations of the weighted ischemic index (ISI) considering the regional distribution of retinal cells with cytokines, macular edema (ME), and neovascularization (NV). In this study, 32 patients with treatment-naïve DR and 21 age-matched control participants were included. The difference between the non-weighted and weighted ISI of NPR with leakage was greatest at the posterior region. The weighted ISI of NPR with leakage was correlated with MCP-1, IL-8, IL-6, PlGF, and VEGF-A levels, while the non-weighted ISI of NPR with leakage was correlated with IL-8 and IL-6 levels. The presence of baseline ME or NV in patients with DR was associated with the weighted ISI, with a stronger association when cones and rods were weighted. The weighted ISI reflecting both metabolic activity and cell distribution demonstrated a better correlation with clinical features and was more valuable in NPR with leakage than non-weighted ISI, which previous studies conventionally used.
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Background Previous studies have shown that T-helper 17 (Th17) cell-related cytokines are significantly increased in the vitreous of proliferative diabetic retinopathy (PDR), suggesting that Th17 cells play an important role in the inflammatory response of diabetic retinopathy (DR), but its cell infiltration and gene correlation in the retina of DR, especially in diabetic macular edema (DME), have not been studied. Methods The dataset GSE160306 was downloaded from the Gene Expression Omnibus (GEO) database, which contains 9 NPDR samples and 10 DME samples. ImmuCellAI algorithm was used to estimate the abundance of Th17 cells in 24 kinds of infiltrating immune cells. The differentially expressed Th17 related genes (DETh17RGs) between NPDR and DME were documented by difference analysis and correlation analysis. Through aggregate analyses such as gene ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway enrichment analysis, a protein-protein interaction (PPI) network was constructed to analyze the potential function of DETh17RGs. CytoHubba plug-in algorithm, Lasso regression analysis and support vector machine recursive feature elimination (SVM-RFE) were implemented to comprehensively identify Hub DETh17RGs. The expression archetypes of Hub DETh17RGs were further verified in several other independent datasets related to DR. The Th17RG score was defined as the genetic characterization of six Hub DETh17RGs using the GSVA sample score method, which was used to distinguish early and advanced diabetic nephropathy (DN) as well as normal and diabetic nephropathy. Finally, real-time quantitative PCR (qPCR) was implemented to verify the transcription levels of Hub DETh17RGs in the STZ-induced DR model mice (C57BL/6J). Results 238 DETh17RGs were identified, of which 212 genes were positively correlated while only 26 genes were negatively correlated. Six genes (CD44, CDC42, TIMP1, BMP7, RHOC, FLT1) were identified as Hub DETh17RGs. Because DR and DN have a strong correlation in clinical practice, the verification of multiple independent datasets related to DR and DN proved that Hub DETh17RGs can not only distinguish PDR patients from normal people, but also distinguish DN patients from normal people. It can also identify the initial and advanced stages of the two diseases (NPDR vs DME, Early DN vs Advanced DN). Except for CDC42 and TIMP1, the qPCR transcription levels and trends of other Hub DETh17RGs in STZ-induced DR model mice were consistent with the human transcriptome level in this study. Conclusion This study will improve our understanding of Th17 cell-related molecular mechanisms in the progression of DME. At the same time, it also provides an updated basis for the molecular mechanism of Th17 cell crosstalk in the eye and kidney in diabetes.
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Background: We investigated whether intensive glycemic control, combination therapy for dyslipidemia, and intensive blood-pressure control would limit the progression of diabetic retinopathy in persons with type 2 diabetes. Previous data suggest that these systemic factors may be important in the development and progression of diabetic retinopathy. Methods: In a randomized trial, we enrolled 10,251 participants with type 2 diabetes who were at high risk for cardiovascular disease to receive either intensive or standard treatment for glycemia (target glycated hemoglobin level, <6.0% or 7.0 to 7.9%, respectively) and also for dyslipidemia (160 mg daily of fenofibrate plus simvastatin or placebo plus simvastatin) or for systolic blood-pressure control (target, <120 or <140 mm Hg). A subgroup of 2856 participants was evaluated for the effects of these interventions at 4 years on the progression of diabetic retinopathy by 3 or more steps on the Early Treatment Diabetic Retinopathy Study Severity Scale (as assessed from seven-field stereoscopic fundus photographs, with 17 possible steps and a higher number of steps indicating greater severity) or the development of diabetic retinopathy necessitating laser photocoagulation or vitrectomy. Results: At 4 years, the rates of progression of diabetic retinopathy were 7.3% with intensive glycemia treatment, versus 10.4% with standard therapy (adjusted odds ratio, 0.67; 95% confidence interval [CI], 0.51 to 0.87; P=0.003); 6.5% with fenofibrate for intensive dyslipidemia therapy, versus 10.2% with placebo (adjusted odds ratio, 0.60; 95% CI, 0.42 to 0.87; P=0.006); and 10.4% with intensive blood-pressure therapy, versus 8.8% with standard therapy (adjusted odds ratio, 1.23; 95% CI, 0.84 to 1.79; P=0.29). Conclusions: Intensive glycemic control and intensive combination treatment of dyslipidemia, but not intensive blood-pressure control, reduced the rate of progression of diabetic retinopathy. (Funded by the National Heart, Lung, and Blood Institute and others; ClinicalTrials.gov numbers, NCT00000620 for the ACCORD study and NCT00542178 for the ACCORD Eye study.)
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To examine the global prevalence and major risk factors for diabetic retinopathy (DR) and vision-threatening diabetic retinopathy (VTDR) among people with diabetes. A pooled analysis using individual participant data from population-based studies around the world was performed. A systematic literature review was conducted to identify all population-based studies in general populations or individuals with diabetes who had ascertained DR from retinal photographs. Studies provided data for DR end points, including any DR, proliferative DR, diabetic macular edema, and VTDR, and also major systemic risk factors. Pooled prevalence estimates were directly age-standardized to the 2010 World Diabetes Population aged 20-79 years. A total of 35 studies (1980-2008) provided data from 22,896 individuals with diabetes. The overall prevalence was 34.6% (95% CI 34.5-34.8) for any DR, 6.96% (6.87-7.04) for proliferative DR, 6.81% (6.74-6.89) for diabetic macular edema, and 10.2% (10.1-10.3) for VTDR. All DR prevalence end points increased with diabetes duration, hemoglobin A(1c), and blood pressure levels and were higher in people with type 1 compared with type 2 diabetes. There are approximately 93 million people with DR, 17 million with proliferative DR, 21 million with diabetic macular edema, and 28 million with VTDR worldwide. Longer diabetes duration and poorer glycemic and blood pressure control are strongly associated with DR. These data highlight the substantial worldwide public health burden of DR and the importance of modifiable risk factors in its occurrence. This study is limited by data pooled from studies at different time points, with different methodologies and population characteristics.
Article
To examine the global prevalence and major risk factors for diabetic retinopathy (DR) and vision-threatening diabetic retinopathy (VTDR) among people with diabetes. A pooled analysis using individual participant data from population-based studies around the world was performed. A systematic literature review was conducted to identify all population-based studies in general populations or individuals with diabetes who had ascertained DR from retinal photographs. Studies provided data for DR end points, including any DR, proliferative DR, diabetic macular edema, and VTDR, and also major systemic risk factors. Pooled prevalence estimates were directly age-standardized to the 2010 World Diabetes Population aged 20-79 years. A total of 35 studies (1980-2008) provided data from 22,896 individuals with diabetes. The overall prevalence was 34.6% (95% CI 34.5-34.8) for any DR, 6.96% (6.87-7.04) for proliferative DR, 6.81% (6.74-6.89) for diabetic macular edema, and 10.2% (10.1-10.3) for VTDR. All DR prevalence end points increased with diabetes duration, hemoglobin A(1c), and blood pressure levels and were higher in people with type 1 compared with type 2 diabetes. There are approximately 93 million people with DR, 17 million with proliferative DR, 21 million with diabetic macular edema, and 28 million with VTDR worldwide. Longer diabetes duration and poorer glycemic and blood pressure control are strongly associated with DR. These data highlight the substantial worldwide public health burden of DR and the importance of modifiable risk factors in its occurrence. This study is limited by data pooled from studies at different time points, with different methodologies and population characteristics.
Chapter
Over the past 25 years, there have been dramatic changes in the management of diabetes and its complications resulting from the application of evidence from randomized controlled clinical trials showing the efficacy of photocoagulation treatment (e.g., Diabetic Retinopathy Study [DRS], Early Treatment Diabetic Retinopathy Study [ETDRS]), and glycemic and blood pressure control (e.g., Diabetes Control and Complications Trial [DCCT], United Kingdom Prospective Diabetes Study [UKPDS]) (1–6). Translation of these findings to clinical care have resulted in changes in the incidence and progression of retinopathy and resultant visual loss in persons with diabetes. The purpose of this chapter is to review the epidemiology of diabetic retinopathy over this period of change. Key WordsDiabetic retinopathy–epidemiology–incidence–risk factors
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To assess the use of eye care and its predictors among diabetic patients in Indonesia. Diabetic patients aged 18 years and older were recruited consecutively from a university clinic and 2 community clinics in Jakarta, Indonesia. Information obtained by questionnaire and record review included demographic and socioeconomic status, knowledge about diabetic retinopathy, and ocular and medical history. The main outcome was self-reported or record history of an eye examination by an eye care professional with dilation of the pupil within the preceding year. Among 196 participants (mean [SD] age, 58.4 [9.4] years; 61.5% female), 166 (84.7%) had not undergone ocular examination in the last year, including 100 of 119 patients (84.0%) at the university clinic. Fewer than half (82 of 166 [49.4%]) of all patients reported being told of the need for eye examinations by their physician. In regression analyses, factors associated with having an eye examination were higher diabetic retinopathy knowledge score (odds ratio = 1.52; P = .01) and years since being diagnosed as having diabetes (odds ratio = 1.71 for third vs first tertile; P = .02). Education, income, health insurance status, and diagnosis of diabetic retinopathy were not predictive of examination. The most common reasons given by subjects for not having had eye examinations concerned lack of knowledge about the need for care (97 of 160 subjects [60.6%]), while financial barriers were cited by only 22 of 160 subjects (13.8%). The low proportion of diabetic subjects receiving recommended annual eye examinations in Indonesia might be improved through patient and physician education.