Begum T, Rahman A, Nomani D, Mamun A, Adams A, Islam S, Khair Z, Khair Z, Anwar I. Diagnostic Accuracy of Detecting Diabetic Retinopathy by Using Digital Fundus Photographs in the Peripheral Health Facilities of Bangladesh: Validation Study.
JMIR Public Health Surveill 2021;
7:e23538. [PMID:
33411671 PMCID:
PMC7988391 DOI:
10.2196/23538]
[Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2020] [Revised: 11/01/2020] [Accepted: 12/16/2020] [Indexed: 11/13/2022] Open
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.
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