We searched PubMed and Google Scholar for articles published in English from database inception up to Nov 10, 2019, using the search terms “diabetic retinopathy”, “screening of diabetic retinopathy”, “retinal imaging”, “retinal neurodegeneration”, “tele-ophthalmology”, “artificial intelligence”, “diabetic complications”, “diabetic retinopathy and cardiovascular disease”, and “diabetic retinopathy and dementia” (alone and in combination). We also searched the reference lists of original research
ReviewScreening for diabetic retinopathy: new perspectives and challenges
Introduction
Diabetic retinopathy remains the leading cause of vision loss and preventable blindness in adults aged 20–74 years, particularly in middle-income and high-income countries.1 In a meta-analysis of 35 studies done worldwide between 1980 and 2008, researchers estimated an overall prevalence of 34·6% (95% CI 34·5–34·8) for any diabetic retinopathy, 6·96% (6·87–7·04) for proliferative diabetic retinopathy, 6·81% (6·74–6·89) for diabetic macular oedema, and 10·2% (10·1–10·3) for vision-threatening diabetic retinopathy among people with diabetes.2 Prevalence of any diabetic retinopathy and proliferative diabetic retinopathy was higher in people with type 1 diabetes than in people with type 2 diabetes.2
Although the proportion of people with diabetes developing proliferative diabetic retinopathy and severe visual loss has been declining between 1980 and 2008 in populations with improved diabetes control,3 the crude prevalence of visual impairment and blindness caused by diabetic retinopathy increased substantially between 1990 and 2015 according to the latest report of the Vision Loss Expert Group of the Global Burden of Disease Study,4 largely because of the increasing prevalence of type 2 diabetes in low-income and middle-income countries. Thus, the number of people affected by blindness due to diabetic retinopathy increased from 0·2 million to 0·4 million, and moderate to severe vision impairment increased from 1·4 million to 2·6 million.4 Furthermore, it has been estimated that the number of people with diabetes affected by any diabetic eye disease in Europe will increase from 6·4 million in 2019 to 8·6 million in 2050, and that 30% of affected individuals will require close monitoring or treatment.5
Few population-based studies examining the incidence of diabetic retinopathy have been done since 2000. The incidence of diabetic retinopathy was higher in studies from before 2000 than in those reported after 2000.6 However, contemporary studies that include more data from low-income and middle-income countries are needed.
Screening for diabetic retinopathy is necessary to detect referable cases that need timely full ophthalmic examination and treatment to avoid permanent visual loss. However, the resources for nationwide screening programmes are not sufficient in many countries. The new technologies based on artificial intelligence, which permit to implement personalised predictive models, the use of telemedicine, and portable imaging devices, are changing the screening strategies and are improving the cost-effectiveness of screening. In this Review, these new tools—which are changing the landscape of screening strategies—will be analysed. In addition, we will comment on the possibility of using retinal examination to identify patients at risk of cardiovascular disease and cognitive impairment, thus expanding the role of the screening of diabetic retinopathy.
Section snippets
Risk factors for diabetic retinopathy
The most relevant risk factors for the development of diabetic retinopathy are the duration of diabetes, poor glycaemic control (high HbA1c and the presence of hypertension. Notably, blood glucose control has a stronger effect than blood pressure control on the risk of developing diabetic retinopathy.7, 8, 9, 10
Other risk factors for diabetic retinopathy include dyslipidaemia, high BMI, puberty, pregnancy, and cataract surgery.2 However, clinical studies on patients living with diabetes have
The cost-effectiveness of screening
Several studies from different countries around the world have been done to investigate the cost-effectiveness of screening for diabetic retinopathy, especially vision-threatening retinopathy.17, 18, 19 Cost-effectiveness of population-based screening programmes is heavily dependent on the frequency of retinal examinations and retinal imaging.20 Extending the screening interval from annual to every 2 or 3 years in patients with diabetes who had no evidence of any retinopathy at first eye
Current guidelines and procedures
The most recent guidelines and procedures for diabetic retinopathy screening were reported by the International Council of Ophthalmology in 2018 as part of their guidelines for diabetic eye care,33 and by the American Diabetes Association in the same year as part of their position statement on diabetic retinopathy.34 The American Diabetes Association recommends a well-defined first eye examination with different timing depending on the type of diabetes, supported by a moderate level (level B)
Novel methods of retinal imaging for ocular telehealth programmes
Recent technological advances in diabetic retinopathy screening fall into three categories: image capture, image analysis, and risk assessment. Novel methods of image capture include the use of scanning (laser) confocal ophthalmoscope-based cameras with ultrawide field imaging or conventional cameras with improvements, such as the use of handheld mobile devices. Automated image analysis and use of artificial intelligence can make an important contribution in teleophthalmology not only for the
Retinopathy screening and other diabetes complications
Apart from retinal neurovascular disease, the presence of diabetic retinopathy means that microcirculation has already been damaged by the diabetic milieu. Therefore, diabetic retinopathy can be considered a reliable marker of the deleterious effects of diabetes in an individual. Accordingly, diabetic retinopathy identifies a subset of the population with diabetes that is at a high risk of developing not only other microangiopathic complications (diabetic nephropathy and diabetic neuropathy,
Conclusions
Health-care affordability, quality, and accessibility for diabetic retinopathy screening are important factors in the prevention of blindness in populations at risk. The combination of automated retinal image analysis and telemedicine has the potential to substantially improve how diabetes eye care is delivered by providing automated real-time assessment in a more personalised way. Additionally, the introduction of new technologies for diabetic retinopathy screening will improve its
Search strategy and selection criteria
References (111)
- et al.
Diabetic retinopathy
Lancet
(2010) - et al.
Global causes of blindness and distance vision impairment 1990-2020: a systematic review and meta-analysis
Lancet Glob Health
(2017) - et al.
Incidence and progression of diabetic retinopathy: a systematic review
Lancet Diabetes Endocrinol
(2019) - et al.
The effects of medical management on the progression of diabetic retinopathy in persons with type 2 diabetes: the Action to Control Cardiovascular Risk in Diabetes (ACCORD) Eye Study
Ophthalmology
(2014) - et al.
Fasting plasma glucose variability levels and risk of adverse outcomes among patients with type 2 diabetes: a systematic review and meta-analysis
Diabetes Res Clin Pract
(2019) - et al.
Cost-effectiveness of a national telemedicine diabetic retinopathy screening program in Singapore
Ophthalmology
(2016) - et al.
The cost-utility of telemedicine to screen for diabetic retinopathy in India
Ophthalmology
(2013) - et al.
A decade-long telemedicine screening program for diabetic retinopathy in the north-east of Italy
J Diabetes Complications
(2017) - et al.
Peripheral lesions identified on ultrawide field imaging predict increased risk of diabetic retinopathy progression over 4 years
Ophthalmology
(2015) - et al.
Guidelines on diabetic eye care: the International Council of Ophthalmology recommendations for screening, follow-up, referral, and treatment based on resource settings
Ophthalmology
(2018)
Comparison of 1-field, 2-fields, and 3-fields fundus photography for detection and grading of diabetic retinopathy
J Diabetes Complications
Effectiveness and safety of screening for diabetic retinopathy with two nonmydriatic digital images compared with the seven standard stereoscopic photographic fields
Can J Ophthalmol
Stereo nonmydriatic digital-video color retinal imaging compared with Early Treatment Diabetic Retinopathy Study seven standard field 35-mm stereo color photos for determining level of diabetic retinopathy
Ophthalmology
Screening for diabetic retinopathy: 1 and 3 nonmydriatic 45-degree digital fundus photographs vs 7 standard early treatment diabetic retinopathy study fields
Am J Ophthalmol
Single-field fundus photography for diabetic retinopathy screening: a report by the American Academy of Ophthalmology
Ophthalmology
Screening of diabetic retinopathy: effect of field number and mydriasis on sensitivity and specificity of digital fundus photography
Diabetes Metab
Peripheral lesions identified by mydriatic ultrawide field imaging: distribution and potential impact on diabetic retinopathy severity
Ophthalmology
Global perspectives on the provision of diabetic retinopathy screening and treatment: survey of health care professionals in 41 countries
Diabetes Res Clin Pract
Equity of uptake of a diabetic retinopathy screening programme in a geographically and socio-economically diverse population
Public Health
Nonmydriatic ultrawide field retinal imaging compared with dilated standard 7-field 35-mm photography and retinal specialist examination for evaluation of diabetic retinopathy
Am J Ophthalmol
Identification of diabetic retinopathy and ungradable image rate with ultrawide field imaging in a national teleophthalmology program
Ophthalmology
Artificial intelligence in diabetic eye disease screening
Asia Pac J Ophthalmol (Phila)
An overview of deep learning in medical imaging focusing on MRI
Z Med Phys
Screening for diabetic retinopathy using computer based image analysis and statistical classification
Comput Methods Programs Biomed
An ophthalmologist's guide to deciphering studies in artificial intelligence
Ophthalmology
Comparison of smartphone ophthalmoscopy with slit-lamp biomicroscopy for grading diabetic retinopathy
Am J Ophthalmol
The role of teleophthalmology in the management of diabetic retinopathy
Asia Pac J Ophthalmol (Phila)
Neurodegeneration in the diabetic eye: new insights and therapeutic perspectives
Trends Endocrinol Metab
Global prevalence and major risk factors of diabetic retinopathy
Diabetes Care
Rates of progression in diabetic retinopathy during different time periods: a systematic review and meta-analysis
Diabetes Care
Prevalence, incidence and future projection of diabetic eye disease in Europe: a systematic review and meta-analysis
Eur J Epidemiol
Effect of glycemic exposure on the risk of microvascular complications in the diabetes control and complications trial—revisited
Diabetes
Intensive blood-glucose control with sulphonylureas or insulin compared with conventional treatment and risk of complications in patients with type 2 diabetes (UKPDS 33)
Lancet
Persistent effects of intensive glycemic control on retinopathy in type 2 diabetes in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) follow-on study
Diabetes Care
Association of time in range, as assessed by continuous glucose monitoring, with diabetic retinopathy in type 2 diabetes
Diabetes Care
Heritability of the severity of diabetic retinopathy: the FIND-Eye study
Invest Ophthalmol Vis Sci
Heritability of proliferative diabetic retinopathy
Diabetes
Familial aggregation of severity of diabetic retinopathy in Mexican Americans from Starr County, Texas
Diabetes Care
Familial risk factors for microvascular complications and differential male-female risk in a large cohort of American families with type 1 diabetes
J Clin Endocrinol Metab
Update on screening for sight-threatening diabetic retinopathy
Ophthalmic Res
Screening intervals for diabetic retinopathy and implications for care
Curr Diab Rep
Incidence and progression of diabetic retinopathy during 17 years of a population-based screening program in England
Diabetes Care
Adopting 3-year screening intervals for sight-threatening retinal vascular lesions in type 2 diabetic subjects without retinopathy
Diabetes Care
Predicted impact of extending the screening interval for diabetic retinopathy: the Scottish Diabetic Retinopathy Screening programme
Diabetologia
Individualised risk assessment for diabetic retinopathy and optimisation of screening intervals: a scientific approach to reducing healthcare costs
Br J Ophthalmol
A simple risk stratification for time to development of sight-threatening diabetic retinopathy
Diabetes Care
An observational study to assess if automated diabetic retinopathy image assessment software can replace one or more steps of manual imaging grading and to determine their cost-effectiveness
Health Technol Assess
Validation of automated screening for referable diabetic retinopathy with the IDx-DR device in the Hoorn Diabetes Care System
Acta Ophthalmol
Advances in retinal imaging and applications in diabetic retinopathy screening: a review
Ophthalmol Ther
Cost-effectiveness of digital surveillance clinics with optical coherence tomography versus hospital eye service follow-up for patients with screen-positive maculopathy
Eye (Lond)
Cited by (303)
Diagnostic Accuracy of Artificial Intelligence-Based Automated Diabetic Retinopathy Screening in Real-World Settings: A Systematic Review and Meta-Analysis
2024, American Journal of OphthalmologyTreatment of diabetic retinopathy with herbs for tonifying kidney and activating blood circulation: A review of pharmacological studies
2024, Journal of EthnopharmacologyEvaluation of an experiment in ophthalmology telemedicine
2024, Journal Francais d'Ophtalmologie