» Articles » PMID: 33411671

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

Overview
Publisher JMIR Publications
Date 2021 Jan 7
PMID 33411671
Citations 8
Authors
Affiliations
Soon will be listed here.
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.

Citing Articles

Prevalence of diabetic retinopathy and its associated risk factors among adults in Ethiopia: a systematic review and meta-analysis.

Wondmeneh T, Mohammed J Sci Rep. 2024; 14(1):28266.

PMID: 39550444 PMC: 11569147. DOI: 10.1038/s41598-024-78596-9.


Diagnostic and prognostic value of triglyceride glucose index: a comprehensive evaluation of meta-analysis.

Nayak S, Kuriyakose D, Polisetty L, Patil A, Ameen D, Bonu R Cardiovasc Diabetol. 2024; 23(1):310.

PMID: 39180024 PMC: 11344391. DOI: 10.1186/s12933-024-02392-y.


Follow-up in a point-of-care diabetic retinopathy program in Pittsburgh: a non-concurrent retrospective cohort study.

Bonilla-Escobar F, Eibel M, Le L, Gallagher D, Waxman E BMC Ophthalmol. 2024; 24(1):356.

PMID: 39164678 PMC: 11334608. DOI: 10.1186/s12886-024-03581-9.


Investigation of the reasons for delayed presentation in proliferative diabetic retinopathy patients.

Zhao M, Chandra A, Liu L, Zhang L, Xu J, Li J PLoS One. 2024; 19(2):e0291280.

PMID: 38421962 PMC: 10903851. DOI: 10.1371/journal.pone.0291280.


Association between the triglyceride glucose index and diabetic retinopathy in type 2 diabetes: a meta-analysis.

Zhou J, Zhu L, Li Y Front Endocrinol (Lausanne). 2023; 14:1302127.

PMID: 38130393 PMC: 10733479. DOI: 10.3389/fendo.2023.1302127.


References
1.
Perrier M, Boucher M, Angioi K, Gresset J, Olivier S . Comparison of two, three and four 45 degrees image fields obtained with the Topcon CRW6 nonmydriatic camera for screening for diabetic retinopathy. Can J Ophthalmol. 2004; 38(7):569-74. DOI: 10.1016/s0008-4182(03)80110-2. View

2.
Gupta V, Bansal R, Gupta A, Bhansali A . Sensitivity and specificity of nonmydriatic digital imaging in screening diabetic retinopathy in Indian eyes. Indian J Ophthalmol. 2014; 62(8):851-6. PMC: 4185162. DOI: 10.4103/0301-4738.141039. View

3.
Quellec G, Bazin L, Cazuguel G, Delafoy I, Cochener B, Lamard M . Suitability of a Low-Cost, Handheld, Nonmydriatic Retinograph for Diabetic Retinopathy Diagnosis. Transl Vis Sci Technol. 2016; 5(2):16. PMC: 4849542. DOI: 10.1167/tvst.5.2.16. View

4.
Thapa R, Twyana S, Paudyal G, Khanal S, van Nispen R, Tan S . Prevalence and risk factors of diabetic retinopathy among an elderly population with diabetes in Nepal: the Bhaktapur Retina Study. Clin Ophthalmol. 2018; 12:561-568. PMC: 5870654. DOI: 10.2147/OPTH.S157560. View

5.
Khairallah M, Kahloun R, Bourne R, Limburg H, Flaxman S, Jonas J . Number of People Blind or Visually Impaired by Cataract Worldwide and in World Regions, 1990 to 2010. Invest Ophthalmol Vis Sci. 2015; 56(11):6762-9. DOI: 10.1167/iovs.15-17201. View