TY - JOUR
T1 - Eye Disease in Patients with Diabetes Screened with Telemedicine
AU - Park, Dong Wouk
AU - Mansberger, Steven L.
N1 - Publisher Copyright:
© Copyright 2017, Mary Ann Liebert, Inc. 2017.
PY - 2017/2
Y1 - 2017/2
N2 - Background: Telemedicine with nonmydriatic cameras can detect not only diabetic retinopathy but also other eye disease. Objective: To determine the prevalence of eye diseases detected by telemedicine in a population with a high prevalence of minority and American Indian/Alaskan Native (AI/AN) ethnicities. Subjects and Methods: We recruited diabetic patients 18 years and older and used telemedicine with nonmydriatic cameras to detect eye disease. Two trained readers graded the images for diabetic retinopathy, age-related macular degeneration (ARMD), glaucomatous features, macular edema, and other eye disease using a standard protocol. We included both eyes for analysis and excluded images that were too poor to grade. Results: We included 820 eyes from 424 patients with 72.3% nonwhite ethnicity and 50.3% AI/AN heritage. While 283/424 (66.7%) patients had normal eye images, 120/424 (28.3%) had one disease identified; 15/424 (3.5%) had two diseases; and 6/424 (1.4%) had three diseases in one or both eyes. After diabetic retinopathy (104/424, 24.5%), the most common eye diseases were glaucomatous features (44/424, 10.4%) and dry ARMD (24/424, 5.7%). Seventeen percent (72/424, 17.0%) showed eye disease other than diabetic retinopathy. Conclusions: Telemedicine with nonmydriatic cameras detected diabetic retinopathy, as well as other visually significant eye disease. This suggests that a diabetic retinopathy screening program needs to detect and report other eye disease, including glaucoma and macular disease.
AB - Background: Telemedicine with nonmydriatic cameras can detect not only diabetic retinopathy but also other eye disease. Objective: To determine the prevalence of eye diseases detected by telemedicine in a population with a high prevalence of minority and American Indian/Alaskan Native (AI/AN) ethnicities. Subjects and Methods: We recruited diabetic patients 18 years and older and used telemedicine with nonmydriatic cameras to detect eye disease. Two trained readers graded the images for diabetic retinopathy, age-related macular degeneration (ARMD), glaucomatous features, macular edema, and other eye disease using a standard protocol. We included both eyes for analysis and excluded images that were too poor to grade. Results: We included 820 eyes from 424 patients with 72.3% nonwhite ethnicity and 50.3% AI/AN heritage. While 283/424 (66.7%) patients had normal eye images, 120/424 (28.3%) had one disease identified; 15/424 (3.5%) had two diseases; and 6/424 (1.4%) had three diseases in one or both eyes. After diabetic retinopathy (104/424, 24.5%), the most common eye diseases were glaucomatous features (44/424, 10.4%) and dry ARMD (24/424, 5.7%). Seventeen percent (72/424, 17.0%) showed eye disease other than diabetic retinopathy. Conclusions: Telemedicine with nonmydriatic cameras detected diabetic retinopathy, as well as other visually significant eye disease. This suggests that a diabetic retinopathy screening program needs to detect and report other eye disease, including glaucoma and macular disease.
KW - E-health
KW - Ophthalmology
KW - Telehealth
KW - Telemedicine
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U2 - 10.1089/tmj.2016.0034
DO - 10.1089/tmj.2016.0034
M3 - Article
C2 - 27328169
AN - SCOPUS:85012083446
SN - 1530-5627
VL - 23
SP - 113
EP - 118
JO - Telemedicine and e-Health
JF - Telemedicine and e-Health
IS - 2
ER -