Cited by 45Retinal Imaging and AnalysisRetinal Diseases and TreatmentsOphthalmology and Visual Health Research

Real-Time Ultrawide Field Image Evaluation of Retinopathy in a Diabetes Telemedicine Program

Silva, Paolo S., Cavallerano, Jerry D., Tolson, Ann M., Rodriguez, Jessica, Rodriguez, Sashida, Ajlan, Radwan, Tolls, Dorothy, Patel, Bina +4 more·2015·Diabetes Care

Abstract

Objective To evaluate the ability of trained nonphysician retinal imagers to perform diabetic retinopathy (DR) evaluation at the time of ultrawide field retinal (UWF) imaging in a teleophthalmology program. Research design and methods Clinic patients with diabetes received Joslin Vision Network protocol retinal imaging as part of their standard medical care. Retinal imagers evaluated UWF images for referable DR at the time of image capture. Training of the imagers included 4 h of standardized didactic lectures and 12 h of guided image review. Real-time evaluations were compared with standard masked gradings performed at a centralized reading center. Results A total of 3,978 eyes of 1,989 consecutive patients were imaged and evaluated. By reading center evaluation, 3,769 eyes (94.7%) were gradable for DR, 1,376 (36.5%) had DR, and 580 (15.3%) had referable DR. Compared with the reading center, real-time image evaluation had a sensitivity and specificity for identifying more than minimal DR of 0.95 (95% CI 0.94-0.97) and 0.84 (0.82-0.85), respectively, and 0.99 (0.97-1.00) and 0.76 (0.75-0.78), respectively, for detecting referable DR. Only three patients with referable DR were not identified by imager evaluation. Conclusions Point-of-care evaluation of UWF images by nonphysician imagers following standardized acquisition and evaluation protocols within an established teleophthalmology program had good sensitivity and specificity for detection of DR and for identification of re…

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Crossref · 10.2337/dc15-0161

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  • Retinal imaging features are critical for diabetic retinopathy.

    “Comparative analyses across complications reveal differing key predictors: retinal imaging features are critical for DR [154], renal function indicators are highly specific to DN [155], while hypertension and dyslipidemia serve as strong predictors for CVD [156] but also overlap with DR and DN [157].”

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References 15 · Cited by 45

Authors
Silva, P. S., Cavallerano, J. D., Tolson, A. M., Rodriguez, J., Rodriguez, S., Ajlan, R., Tolls, D., Patel, B., Sehizadeh, M., Thakore, K., Sun, J. K., & Aiello, L. P.
Affiliations
Joslin Diabetes Center (US)
Corresponding author
Silva, Paolo S.
Venue
Diabetes Care
Published
2015-06-01
Volume
38
Issue
9
Pages
1643-1649
ISSN
  • 0149-5992 (ISSN-L)
  • 1935-5548
OpenAlex
W1947168587
Cited by
45
References
15
Citations by year
2026: 3 · 2025: 1 · 2024: 1 · 2023: 3 · 2022: 6 · 2021: 3 · 2020: 6 · 2019: 3 · 2018: 6 · 2017: 6 · 2016: 5 · 2015: 2
FWCI
5.39
Type
journal article
Language
en
Open access
closed
Locations
  • Diabetes Care (publishedVersion)
  • PubMed (publishedVersion)
Funders
Center of Integration of Medicine and Innovative Technology
Topics
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Retinal Imaging and Analysis
  • Health Sciences › Medicine › Ophthalmology › Retinal Diseases and Treatments
  • Health Sciences › Medicine › Ophthalmology › Ophthalmology and Visual Health Research
Keywords
diabetic retinopathy, teleophthalmology
MeSH terms
Adolescent, Adult, Aged, Aged, 80 and over, Computer Systems, Diabetic Retinopathy, Diagnostic Imaging, Female, Humans, Male, Middle Aged, Retrospective Studies, Sensitivity and Specificity, Telemedicine, Point-of-Care Systems, Young Adult

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