Literature DB >> 34708764

Commentary: Targeted screening for effective detection of vision threatening diabetic retinopathy.

Anantharaman Giridhar1.   

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Year:  2021        PMID: 34708764      PMCID: PMC8725111          DOI: 10.4103/ijo.IJO_2643_21

Source DB:  PubMed          Journal:  Indian J Ophthalmol        ISSN: 0301-4738            Impact factor:   1.848


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Various techniques of retinal examination and different types of screening programs have been devised over the last decade for detection of diabetic retinopathy (DR).[1] The success of any such program is based on how effective it has been in detecting and treating vision threatening diabetic retinopathy (VTDR) and thereby reducing the blinding complication of DR. In this context, the article by Sagnik et al.[2] is very relevant and informative and should help us to devise new strategies for effective screening of DR. The authors performed a subgroup analysis of the data on all enrolled participants above the age of 40 years from four major population-based studies from India.[3456] They concluded that persons with diabetes between the age of 50–69 years and those with systolic blood pressure ≥140 mm Hg have a higher risk of VTDR. Therefore, targeted screening of this vulnerable population alone can result in identifying 93% of all patients with VTDR among persons with diabetic retinopathy. However, the authors did not look into both micro and macroalbuminuria, two important risk factors for presence of retinopathy and severity of retinopathy.[7] How do we change our strategy and approach to screening programs based on these observations? The diabetic retinopathy screening guidelines in India should emphasize and give importance to identification of VTDR and to target the vulnerable population. The present guidelines fail to address this issue.[8] Similarly, the National Task Force on Diabetic Retinopathy should create awareness among primary care physicians and endocrinologists on the importance of identifying the vulnerable population and getting them examined for treatable diabetic retinopathy. All major departments of internal medicine in district hospitals, medical colleges, and large multispecialty hospitals including dedicated diabetic centers should have facilities for remote screening of diabetic retinopathy either through telemedicine or through the cloud format. Remote screening refers to the transmission of images to a central reading center using a network. A recent report from Japan demonstrates how successful remote screening is in detecting treatable diabetic retinopathy using nonmydriatic wide-field imaging.[9] Finally, the rapid development of artificial intelligence and deep learning algorithms for detection of diabetic retinopathy may make it easier to identify patients at a higher risk of losing vision.[10]’
  10 in total

1.  Screening for vision-threatening diabetic retinopathy in South India: comparing portable non-mydriatic and standard fundus cameras and clinical exam.

Authors:  S Sengupta; M D Sindal; C G Besirli; S Upadhyaya; R Venkatesh; L M Niziol; A L Robin; M A Woodward; P A Newman-Casey
Journal:  Eye (Lond)       Date:  2017-09-15       Impact factor: 3.775

2.  Prevalence of diabetic retinopathy in urban India: the Chennai Urban Rural Epidemiology Study (CURES) eye study, I.

Authors:  Mohan Rema; Sundaram Premkumar; Balaji Anitha; Raj Deepa; Rajendra Pradeepa; Viswanathan Mohan
Journal:  Invest Ophthalmol Vis Sci       Date:  2005-07       Impact factor: 4.799

3.  Remote screening of diabetic retinopathy using ultra-widefield retinal imaging.

Authors:  Aki Kato; Keiichiro Fujishima; Kazuhisa Takami; Naomi Inoue; Noriaki Takase; Norihiro Suzuki; Katsuya Suzuki; Soichiro Kuwayama; Akiko Yamada; Katsuhisa Sakai; Ryosuke Horita; Miho Nozaki; Munenori Yoshida; Yoshio Hirano; Tsutomu Yasukawa; Yuichiro Ogura
Journal:  Diabetes Res Clin Pract       Date:  2021-06-06       Impact factor: 5.602

4.  Prevalence of diabetic retinopathy in India: Sankara Nethralaya Diabetic Retinopathy Epidemiology and Molecular Genetics Study report 2.

Authors:  Rajiv Raman; Padmaja Kumari Rani; Sudhir Reddi Rachepalle; Perumal Gnanamoorthy; Satagopan Uthra; Govindasamy Kumaramanickavel; Tarun Sharma
Journal:  Ophthalmology       Date:  2008-12-12       Impact factor: 12.079

5.  Prevalence and risk factors for diabetic retinopathy: a population-based assessment from Theni District, south India.

Authors:  P Namperumalsamy; R Kim; T P Vignesh; N Nithya; J Royes; T Gijo; R D Thulasiraj; V Vijayakumar
Journal:  Postgrad Med J       Date:  2009-12       Impact factor: 2.401

6.  Detection of Diabetic Retinopathy from Ultra-Widefield Scanning Laser Ophthalmoscope Images: A Multicenter Deep Learning Analysis.

Authors:  Fangyao Tang; Phoomraphee Luenam; An Ran Ran; Ahmed Abdul Quadeer; Rajiv Raman; Piyali Sen; Rehana Khan; Anantharaman Giridhar; Swathy Haridas; Matias Iglicki; Dinah Zur; Anat Loewenstein; Hermino P Negri; Simon Szeto; Bryce Ka Yau Lam; Clement C Tham; Sobha Sivaprasad; Matthew Mckay; Carol Y Cheung
Journal:  Ophthalmol Retina       Date:  2021-02-01

7.  Albuminuria and Diabetic Retinopathy in Type 2 Diabetes Mellitus Sankara Nethralaya Diabetic Retinopathy Epidemiology And Molecular Genetic Study (SN-DREAMS, report 12).

Authors:  Padmaja K Rani; Rajiv Raman; Aditi Gupta; Swakshyar S Pal; Vaitheeswaran Kulothungan; Tarun Sharma
Journal:  Diabetol Metab Syndr       Date:  2011-05-25       Impact factor: 3.320

8.  Prevalence and risk factors for diabetic retinopathy in rural India. Sankara Nethralaya Diabetic Retinopathy Epidemiology and Molecular Genetic Study III (SN-DREAMS III), report no 2.

Authors:  Rajiv Raman; Suganeswari Ganesan; Swakshyar Saumya Pal; Vaitheeswaran Kulothungan; Tarun Sharma
Journal:  BMJ Open Diabetes Res Care       Date:  2014-06-06

9.  Diabetic retinopathy screening guidelines in India: All India Ophthalmological Society diabetic retinopathy task force and Vitreoretinal Society of India Consensus Statement.

Authors:  Rajiv Raman; Kim Ramasamy; Ramachandran Rajalakshmi; Sobha Sivaprasad; S Natarajan
Journal:  Indian J Ophthalmol       Date:  2021-03       Impact factor: 1.848

10.  Identification of risk factors for targeted diabetic retinopathy screening to urgently decrease the rate of blindness in people with diabetes in India.

Authors:  Sagnik Sen; Kim Ramasamy; T P Vignesh; Naresh B Kannan; Sobha Sivaprasad; Ramachandran Rajalakshmi; Rajiv Raman; Viswanathan Mohan; Taraprasad Das; Iswarya Mani
Journal:  Indian J Ophthalmol       Date:  2021-11       Impact factor: 1.848

  10 in total

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