Literature DB >> 33411671

Diagnostic Accuracy of Detecting Diabetic Retinopathy by Using Digital Fundus Photographs in the Peripheral Health Facilities of Bangladesh: Validation Study.

Tahmina Begum1, Aminur Rahman2, Dilruba Nomani2, Abdullah Mamun1, Alayne Adams3, Shafiqul Islam4, Zara Khair5, Zareen Khair5, Iqbal Anwar2.   

Abstract

BACKGROUND: Diabetic retinopathy can cause blindness even in the absence of symptoms. Although routine eye screening remains the mainstay of diabetic retinopathy treatment and it can prevent 95% of blindness, this screening is not available in many low- and middle-income countries even though these countries contribute to 75% of the global diabetic retinopathy burden.
OBJECTIVE: The aim of this study was to assess the diagnostic accuracy of diabetic retinopathy screening done by non-ophthalmologists using 2 different digital fundus cameras and to assess the risk factors for the occurrence of diabetic retinopathy.
METHODS: This validation study was conducted in 6 peripheral health facilities in Bangladesh from July 2017 to June 2018. A double-blinded diagnostic approach was used to test the accuracy of the diabetic retinopathy screening done by non-ophthalmologists against the gold standard diagnosis by ophthalmology-trained eye consultants. Retinal images were taken by using either a desk-based camera or a hand-held camera following pupil dilatation. Test accuracy was assessed using measures of sensitivity, specificity, and positive and negative predictive values. Overall agreement with the gold standard test was reported using the Cohen kappa statistic (κ) and area under the receiver operating curve (AUROC). Risk factors for diabetic retinopathy occurrence were assessed using binary logistic regression.
RESULTS: In 1455 patients with diabetes, the overall sensitivity to detect any form of diabetic retinopathy by non-ophthalmologists was 86.6% (483/558, 95% CI 83.5%-89.3%) and the specificity was 78.6% (705/897, 95% CI 75.8%-81.2%). The accuracy of the correct classification was excellent with a desk-based camera (AUROC 0.901, 95% CI 0.88-0.92) and fair with a hand-held camera (AUROC 0.710, 95% CI 0.67-0.74). Out of the 3 non-ophthalmologist categories, registered nurses and paramedics had strong agreement with kappa values of 0.70 and 0.85 in the diabetic retinopathy assessment, respectively, whereas the nonclinical trained staff had weak agreement (κ=0.35). The odds of having retinopathy increased with the duration of diabetes measured in 5-year intervals (P<.001); the odds of having retinopathy in patients with diabetes for 5-10 years (odds ratio [OR] 1.81, 95% CI 1.37-2.41) and more than 10 years (OR 3.88, 95% CI 2.91-5.15) were greater than that in patients with diabetes for less than 5 years. Obesity was found to have a negative association (P=.04) with diabetic retinopathy.
CONCLUSIONS: Digital fundus photography is an effective screening tool with acceptable diagnostic accuracy. Our findings suggest that diabetic retinopathy screening can be accurately performed by health care personnel other than eye consultants. People with more than 5 years of diabetes should receive priority in any community-level retinopathy screening program. In a country like Bangladesh where no diabetic retinopathy screening services exist, the use of hand-held cameras can be considered as a cost-effective option for potential system-wide implementation. ©Tahmina Begum, Aminur Rahman, Dilruba Nomani, Abdullah Mamun, Alayne Adams, Shafiqul Islam, Zara Khair, Zareen Khair, Iqbal Anwar. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 09.03.2021.

Entities:  

Keywords:  Bangladesh; diabetes; diabetic retinopathy; diagnostic accuracy; digital fundus photograph; opthalmology; retina; retinopathy

Year:  2021        PMID: 33411671      PMCID: PMC7988391          DOI: 10.2196/23538

Source DB:  PubMed          Journal:  JMIR Public Health Surveill        ISSN: 2369-2960


  38 in total

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2.  Diagnostic accuracy of direct ophthalmoscopy for detection of diabetic retinopathy using fundus photographs as a reference standard.

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3.  Comparison of two, three and four 45 degrees image fields obtained with the Topcon CRW6 nonmydriatic camera for screening for diabetic retinopathy.

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4.  Number of People Blind or Visually Impaired by Cataract Worldwide and in World Regions, 1990 to 2010.

Authors:  Moncef Khairallah; Rim Kahloun; Rupert Bourne; Hans Limburg; Seth R Flaxman; Jost B Jonas; Jill Keeffe; Janet Leasher; Kovin Naidoo; Konrad Pesudovs; Holly Price; Richard A White; Tien Y Wong; Serge Resnikoff; Hugh R Taylor
Journal:  Invest Ophthalmol Vis Sci       Date:  2015-10       Impact factor: 4.799

Review 5.  Current epidemiology of diabetic retinopathy and diabetic macular edema.

Authors:  Jie Ding; Tien Yin Wong
Journal:  Curr Diab Rep       Date:  2012-08       Impact factor: 4.810

6.  Sensitivity and specificity of nonmydriatic digital imaging in screening diabetic retinopathy in Indian eyes.

Authors:  Vishali Gupta; Reema Bansal; Amod Gupta; Anil Bhansali
Journal:  Indian J Ophthalmol       Date:  2014-08       Impact factor: 1.848

7.  Sensitivity, Specificity, and Predictive Values: Foundations, Pliabilities, and Pitfalls in Research and Practice.

Authors:  Robert Trevethan
Journal:  Front Public Health       Date:  2017-11-20

8.  Diagnostic test accuracy of diabetic retinopathy screening by physician graders using a hand-held non-mydriatic retinal camera at a tertiary level medical clinic.

Authors:  Mapa Mudiyanselage Prabhath Nishantha Piyasena; Jennifer L Y Yip; David MacLeod; Min Kim; Venkata S Murthy Gudlavalleti
Journal:  BMC Ophthalmol       Date:  2019-04-08       Impact factor: 2.086

9.  Suitability of a Low-Cost, Handheld, Nonmydriatic Retinograph for Diabetic Retinopathy Diagnosis.

Authors:  Gwenolé Quellec; Loïc Bazin; Guy Cazuguel; Ivan Delafoy; Béatrice Cochener; Mathieu Lamard
Journal:  Transl Vis Sci Technol       Date:  2016-04-20       Impact factor: 3.283

10.  Prevalence and risk factors of diabetic retinopathy among an elderly population with diabetes in Nepal: the Bhaktapur Retina Study.

Authors:  Raba Thapa; Shankha N Twyana; Govinda Paudyal; Shankar Khanal; Ruth van Nispen; Stevie Tan; Suman S Thapa; Ghmb van Rens
Journal:  Clin Ophthalmol       Date:  2018-03-23
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1.  Validation of an Automated Screening System for Diabetic Retinopathy Operating under Real Clinical Conditions.

Authors:  Soledad Jimenez-Carmona; Pedro Alemany-Marquez; Pablo Alvarez-Ramos; Eduardo Mayoral; Manuel Aguilar-Diosdado
Journal:  J Clin Med       Date:  2021-12-21       Impact factor: 4.241

Review 2.  Diabetic retinopathy screening in the public sector in India: What is needed?

Authors:  Vivek Gupta; Shorya Vardhan Azad; Praveen Vashist; Suraj S Senjam; Atul Kumar
Journal:  Indian J Ophthalmol       Date:  2022-03       Impact factor: 2.969

  2 in total

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