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Various models for diabetic retinopathy screening that can be applied to India
Author(s) -
Ramachandran Rajalakshmi,
Vijayaraghavan Prathiba,
Padmaja Kumari Rani,
Viswanathan Mohan
Publication year - 2021
Publication title -
indian journal of ophthalmology/indian journal of ophthalmology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.542
H-Index - 51
eISSN - 1998-3689
pISSN - 0301-4738
DOI - 10.4103/ijo.ijo_1145_21
Subject(s) - medicine , diabetic retinopathy , optometry , fundus photography , referral , fundus (uterus) , eye examination , retinopathy , ophthalmology , diabetes mellitus , retinal , family medicine , visual acuity , fluorescein angiography , endocrinology
The increased burden of diabetes in India has resulted in an increase in the complications of diabetes including sight-threatening diabetic retinopathy (DR). Visual impairment and blindness due to DR can be prevented by early detection and management of sight-threatening DR. Life-long evaluation by repetitive retinal screening of people with diabetes is an essential strategy as DR has an asymptomatic presentation. Fundus examination by trained ophthalmologists and fundus photography are established modes of screening. Various modes of opportunistic screening have been followed in India. Hospital-based screening (diabetes care/eye care) and community-based screening are the common modes. Tele-ophthalmology programs based on retinal imaging, remote interpretation, and grading of DR by trained graders/ophthalmologists have facilitated greater coverage of DR screening and enabled timely referral of those with sight-threatening DR. DR screening programs use nonmydriatic or mydriatic fundus cameras for retinal photography. Hand-held/smartphone-based fundus cameras that are portable, less expensive, and easy to use in remote places are gaining popularity. Good retinal image quality and accurate diagnosis play an important role in reducing unnecessary referrals. Recent advances like nonmydriatic ultrawide field fundus photography can be used for DR screening, though likely to be more expensive. The advent of artificial intelligence and deep learning has raised the possibility of automated detection of DR. Efforts to increase the awareness regarding DR is essential to ensure compliance to regular follow-up. Cost-effective sustainable models will ensure systematic nation-wide DR screening in the country.

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