Clinic-Based Eye Disease Screening Using Non-Expert Fundus Photo Graders at the Point of Screening: Diagnostic Validity and Yield.
Somanguan Ausayakhun, Blake M Snyder, Sakarin Ausayakhun, Onnisa Nanegrungsunk, Atitaya Apivatthakakul, Chanusnun Narongchai, Jason S Melo, Jeremy D Keenan
Summary
Non-expert eye disease screening in health clinics may be a useful model for detection of eye disease in resource-limited settings.
Abstract
PURPOSE
The intent of this study was to determine the diagnostic accuracy of several diagnostic tests for age-related macular degeneration (AMD), diabetic retinopathy (DR), glaucoma, and cataract, as well as the proportions of patients with eye disease from each of 3 enrolling clinics.
DESIGN
Diagnostic accuracy study.
METHODS
Patients ≥50 years old in a diabetes, thyroid, and general medicine clinic were screened using visual acuity, tonometry, and fundus photography. Photographs were graded at the point-of-screening by non-ophthalmic personnel. Participants with positive screening test results in either eye and a 10% random sample with negative results in both eyes were referred for an in-person, reference-standard ophthalmology examination.
RESULTS
Of 889 participants enrolled, 229 participants failed at least 1 test in either eye, of which 189 presented for an ophthalmic examination. An additional 76 participants with completely normal screening test results were referred for examination, of which 50 attended. Fundus photography screening had the highest yield for DR (sensitivity: 67%; 95% confidence interval [CI]: 39%-87%), visual acuity screening for cataract (sensitivity: 89%; 95%
CI
86%-92%), and intraocular pressure screening for glaucoma or suspected glaucoma (sensitivity: 25%; 95%
CI
14%-40%). The burden of disease was relatively high in all 3 clinics, with at least 1 of the diseases of interest (ie, AMD, DR, glaucoma or suspected glaucoma, or cataract) detected in 25% of participants (95%
CI
17-35%) from the diabeteses clinic, 34% (95%
CI
22%-49%) from the thyroid clinic, and 21% (95%
CI
13%-32%) from the general clinic.
CONCLUSIONS
Non-expert eye disease screening in health clinics may be a useful model for detection of eye disease in resource-limited settings.
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Discussion
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