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Analysis of yield of retinal imaging in a rural diabetes eye care model

PURPOSE: The aim of this study is to analyze the yield of retinal images obtained in a rural diabetes eye care model. METHODS: An analysis of a sample of nonmydriatic fundus photography (NMFP) of posterior segment ophthalmic images, obtained by an indigenous equipment (3 nethra-Forus Royal), was don...

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Autores principales: Rani, Padmaja Kumari, Bhattarai, Yashaswee, Sheeladevi, Sethu, ShivaVaishnavi, K, Ali, Md Hasnat, Babu, J Ganesh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Medknow Publications & Media Pvt Ltd 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5819102/
https://www.ncbi.nlm.nih.gov/pubmed/29380765
http://dx.doi.org/10.4103/ijo.IJO_500_17
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author Rani, Padmaja Kumari
Bhattarai, Yashaswee
Sheeladevi, Sethu
ShivaVaishnavi, K
Ali, Md Hasnat
Babu, J Ganesh
author_facet Rani, Padmaja Kumari
Bhattarai, Yashaswee
Sheeladevi, Sethu
ShivaVaishnavi, K
Ali, Md Hasnat
Babu, J Ganesh
author_sort Rani, Padmaja Kumari
collection PubMed
description PURPOSE: The aim of this study is to analyze the yield of retinal images obtained in a rural diabetes eye care model. METHODS: An analysis of a sample of nonmydriatic fundus photography (NMFP) of posterior segment ophthalmic images, obtained by an indigenous equipment (3 nethra-Forus Royal), was done in a district-wide rural diabetic retinopathy (DR) screening program; a trained optometrist did the initial image grading. DR and diabetic macular edema (DME) were classified based on international DR and DME severity scale. The agreement between the optometrist and retina specialist was very good (κ = 0.932; standard error = 0.030; 95% confidence interval = 0.874–0.991). RESULTS: Posterior segment images of 2000 eyes of 1000 people with diabetes mellitus (DM) were graded. The mean age of the participants was 55.7 ± 11.5 standard deviation years. Nearly 42% of the screened participants (n = 420/1000) needed referral. The most common referable posterior segment abnormality was DR (8.2%). The proportion of people with any form of DR was seen in 110/1225 eyes, and sight-threatening DR was seen in 35/1225 eyes. About 62% of posterior segment images were gradable. The reasons for ungradable posterior segment images (34%) were small pupil, unfocused/partially available field of images, and cataract. CONCLUSION: A NMFP model was able to detect referable posterior segment abnormalities in a rural diabetes eye care program. Reasons found for ungradability of images in the present study can be addressed while designing future DR screening programs in the rural areas.
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spelling pubmed-58191022018-02-22 Analysis of yield of retinal imaging in a rural diabetes eye care model Rani, Padmaja Kumari Bhattarai, Yashaswee Sheeladevi, Sethu ShivaVaishnavi, K Ali, Md Hasnat Babu, J Ganesh Indian J Ophthalmol Original Article PURPOSE: The aim of this study is to analyze the yield of retinal images obtained in a rural diabetes eye care model. METHODS: An analysis of a sample of nonmydriatic fundus photography (NMFP) of posterior segment ophthalmic images, obtained by an indigenous equipment (3 nethra-Forus Royal), was done in a district-wide rural diabetic retinopathy (DR) screening program; a trained optometrist did the initial image grading. DR and diabetic macular edema (DME) were classified based on international DR and DME severity scale. The agreement between the optometrist and retina specialist was very good (κ = 0.932; standard error = 0.030; 95% confidence interval = 0.874–0.991). RESULTS: Posterior segment images of 2000 eyes of 1000 people with diabetes mellitus (DM) were graded. The mean age of the participants was 55.7 ± 11.5 standard deviation years. Nearly 42% of the screened participants (n = 420/1000) needed referral. The most common referable posterior segment abnormality was DR (8.2%). The proportion of people with any form of DR was seen in 110/1225 eyes, and sight-threatening DR was seen in 35/1225 eyes. About 62% of posterior segment images were gradable. The reasons for ungradable posterior segment images (34%) were small pupil, unfocused/partially available field of images, and cataract. CONCLUSION: A NMFP model was able to detect referable posterior segment abnormalities in a rural diabetes eye care program. Reasons found for ungradability of images in the present study can be addressed while designing future DR screening programs in the rural areas. Medknow Publications & Media Pvt Ltd 2018-02 /pmc/articles/PMC5819102/ /pubmed/29380765 http://dx.doi.org/10.4103/ijo.IJO_500_17 Text en Copyright: © 2018 Indian Journal of Ophthalmology http://creativecommons.org/licenses/by-nc-sa/3.0 This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as the author is credited and the new creations are licensed under the identical terms.
spellingShingle Original Article
Rani, Padmaja Kumari
Bhattarai, Yashaswee
Sheeladevi, Sethu
ShivaVaishnavi, K
Ali, Md Hasnat
Babu, J Ganesh
Analysis of yield of retinal imaging in a rural diabetes eye care model
title Analysis of yield of retinal imaging in a rural diabetes eye care model
title_full Analysis of yield of retinal imaging in a rural diabetes eye care model
title_fullStr Analysis of yield of retinal imaging in a rural diabetes eye care model
title_full_unstemmed Analysis of yield of retinal imaging in a rural diabetes eye care model
title_short Analysis of yield of retinal imaging in a rural diabetes eye care model
title_sort analysis of yield of retinal imaging in a rural diabetes eye care model
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5819102/
https://www.ncbi.nlm.nih.gov/pubmed/29380765
http://dx.doi.org/10.4103/ijo.IJO_500_17
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