December 2021, Volume 71, Issue 12

Primary Care Diabetes

Screening for diabetic retinopathy in primary care: Future prospects in low-middle income countries

Deepthi Elizabeth Kurian  ( Department of Ophthalmology, Schell eye hospital, Christian Medical College, Vellore ,India )
Sanjay Kalra  ( Department of Endocrinology, Bharti Hospital, Karnal, India. )
Nitin Kapoor  ( Department of Endocrinology, Diabetes and Metabolism, Christian Medical College, Vellore (TN) -632004, India, and Non Communicable Disease Unit, Melbourne School of Population and Global Health, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Victoria, Australia. )

Abstract

Diabetic retinopathy (DR) is an urgent public health concern, and it is prudent to prevent DR than face the burden of blindness arising from it.  This requires committed physicians, ophthalmologists, patients as well as policy makers. Blindness rate due to DR has shown a decline in developed countries which is not only due to advanced and accessible tertiary care, but also large-scale screening programmes. Currently, the most common method of screening in low- and middle-income countries is still an opportunistic model. A more practical, cost-effective and systematic screening model is needed, utilizing advances in telemedicine and artificial intelligence.

Keywords: Diabetic Retinopathy, Screening the eye, South Asian perspective.

 

Introduction

 

Diabetic retinopathy (DR) is the leading cause of blindness and visual impairment in the working age group. Screening for DR is a mode of secondary prevention that involves preventing sight threatening DR by regular follow-up, early diagnosis, prompt referral as well as emphasising systemic disease control.1,2 Tertiary prevention on the other hand comprises laser photocoagulation, anti vascular endothelial growth factor (anti-VEGF), vitrectomy etc. With the newer techniques for tertiary prevention there has been a definite decline in blindness but the absolute number of individuals with no DR has not reduced. This requires the focus to be shifted from tertiary prevention to primary and secondary prevention, the need being greatest in the low middle income countries (LMIC).

 

Global prevalence and need for screening

 

Diabetes mellitus (DM) is a global epidemic, which disproportionately affects LMIC. Two-thirds of those with type 2 DM and 90% of those with type 1 DM are thought to develop diabetic retinopathy (DR). In spite of this, 70% of patients with diabetes are unaware of their retinopathy status. One in ten patients with DR have vision threatening diabetic retinopathy (VTDR), i.e.  proliferative diabetic retinopathy (PDR) or diabetic macular oedema (DME) and without treatment 50% of those may become blind within 5 years.3,4  However, blindness can be reduced ten-fold with prompt referral for VTDR and early intervention.5  Apart from the high prevalence of DR, the long latent phase, the sensitive examination techniques and the enormous benefit early intervention can make DR an ideal disease for screening.6

 

Screening models

 

Nationwide screening programmes have increased coverage in many developed countries, but faced with limitations such as lack of resources and infrastructure in developing countries. A unique identification for all patients with diabetes, linked to electronic medical records (EMR) would be ideal for tracking referral and continuum of care. Although there is a transition in the recent past from paper to EMR system, it will be a while before there is a complete electronic registry in LMIC. Along with the registry, pathways for referral and patient information should be in place. Global Diabetic Retinopathy Advocacy Initiative group recommends 4 integrated models (Table).

 

3  Currently, most screening programmes in developing countries are still opportunistic. The gold standard technique for DR screening assessment using a mydriatic seven field stereoscopic retinal colour photography.7  Although this provided for better standardisation, it is time-consuming and needs expert interpretation. In recent years there is a move towards telemedicine using ultrawide-field (UWF) non-mydriatic fundus photography which takes less than half the time as standard seven field images and closely matched clinical examination for level of DR and DME.8,9  The acceptance of telemedicine has been shown to be comparable to or even higher than face to face examinations.10  Here, retinal photos taken at point-of-care are transmitted to a web cloud which is accessed and read by trained image readers who send them back to the primary contact. This has enabled larger coverage, faster screening and better cost-effectiveness. There are attempts to attach optical coherence tomography (OCT) with the UWF images to reduce the false positive referrals for macular oedema. The future will also see the use of many smart phone based retinal photography applications for image acquisition as well as reporting.

The International Council of Ophthalmology lays out screening guidelines for both high resource settings as well as low/intermediate resource settings.11  National DR task force has shared a set of practical guidelines for DR screening that delineates the criteria to be followed for screening personnel, fundus camera, number of fields to be captured, pupillary dilatation or not, image storage, image graders, criteria for referral as well as handling of unreadable images.12  Having skill based criteria for trained personnel involved ensures quality as there is international consensus that screening programmes for DR should achieve at least 80% sensitivity and 95% specificity.10

Artificial intelligence (AI) is being used to decipher images without a physician's input and help identify referable DR13. IDx-DR is the first AI device that received FDA approval. With these models there is scope for risk stratification, personalized screening intervals, improved adherence, and optimised resource utility.

 

Conclusion

 

Screening for DR and setting up effective referral pathways is an urgent need. Telemedicine models have gained wide acceptance and proven cost-effective. These should be resource specific and customised as per national demands while adhering to the global guidelines for quality control.

 

References

 

1.       UK Prospective Diabetes Study Group. Tight blood pressure control and risk of macrovascular and microvascular complications in type 2 diabetes: UKPDS 38. UK Prospective Diabetes Study Group. BMJ. 1998;317:703-13. Erratum in: BMJ 1999; 318(7175):29.

2.       Intensive blood-glucose control with sulphonylureas or insulin compared with conventional treatment and risk of complications in patients with type 2 diabetes (UKPDS 33). UK Prospective Diabetes Study (UKPDS) Group. Lancet. 1998; 352:837-53. Erratum in: Lancet 1999; 354(9178):602.

3.       Wong TY, Sabanayagam C. Strategies to Tackle the Global Burden of Diabetic Retinopathy: From Epidemiology to Artificial Intelligence. Ophthalmologica. 2020;243:9-20.

4.       Wild S, Roglic G, Green A, Sicree R, King H. Global prevalence of diabetes: estimates for the year 2000 and projections for 2030. Diabetes Care. 2004; 27:1047-53.

5.       Ferris FL 3rd. Results of 20 years of research on the treatment of diabetic retinopathy. Prev Med. 1994; 23:740-2.

6.       Vashist P, Singh S, Gupta N, Saxena R. Role of early screening for diabetic retinopathy in patients with diabetes mellitus: an overview. Indian J Community Med. 2011; 36:247-52. doi: 10.4103/0970-0218.91324.

7.       Early Treatment Diabetic Retinopathy Study Research Group. Grading Diabetic Retinopathy from Stereoscopic Color Fundus Photographs - An Extension of the Modified Airlie House Classification: ETDRS Report Number 10. Ophthalmology. 2020; 127:S99-S119.

8.       Cavallerano JD, Aiello LP, Cavallerano AA, Katalinic P, Hock K, Kirby R, et al; Joslin Vision Network Clinical Team. Nonmydriatic digital imaging alternative for annual retinal examination in persons with previously documented no or mild diabetic retinopathy. Am J Ophthalmol. 2005; 140:667-73.

9.       Silva PS, Cavallerano JD, Sun JK, Noble J, Aiello LM, Aiello LP. 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. 2012; 154:549-559.e2.

10.    Huemer J, Wagner SK, Sim DA. The Evolution of Diabetic Retinopathy Screening Programmes: A Chronology of Retinal Photography from 35 mm Slides to Artificial Intelligence. Clin Ophthalmol. 2020; 14:2021-2035.

11.    Wong TY, Sun J, Kawasaki R, Ruamviboonsuk P, Gupta N, Lansingh VC, 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; 125:1608-1622.

12.     Kumar A, Agarwal D, Kumar A. Diabetic retinopathy screening and management in India: Challenges and possible solutions. Indian J Ophthalmol. 2021; 69:479-481.

13.     Abràmoff MD, Folk JC, Han DP, Walker JD, Williams DF, Russell SR, et al. Automated analysis of retinal images for detection of referable diabetic retinopathy. JAMA Ophthalmol. 2013; 131:351-7.

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