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Diabetic Retinopathy Screening: Current Advances and Future Options

A special issue of Journal of Clinical Medicine (ISSN 2077-0383). This special issue belongs to the section "Ophthalmology".

Deadline for manuscript submissions: 31 October 2025 | Viewed by 323

Special Issue Editors


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Guest Editor
iHealthScreen Inc., Richmond Hill, NY 11418, USA
Interests: artificial intelligence; machine learning; retinal imaging and image based diagnosis; optical coherence tomography imaging; diabetic retinopathy; macular degeneration; retinal degenerations; telemedicine; neuro-ophthalmology; AI for cardiovascular disease prediction
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
New York Eye and Ear Infirmary, The Mount Sinai Hospital, New York, NY 10003, USA
Interests: retinal imaging; optical coherence tomography imaging (OCT); diabetic retinopathy; image analysis; artificial intelligence; telemedicine; age-related macular degeneration
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Diabetic retinopathy (DR) is a common complication of diabetes and remains a leading cause of severe vision loss and blindness, thus representing a significant economic burden for healthcare systems. Existing research on DR has delved into its histopathology in order to understand the associated tissue changes. In addition, imaging modalities such as fundus photography and OCT have been used for screening and evaluation, with screening guidelines being employed to determine when and who to screen. Studies on the progression of DR progression and the socio-economic effects on DR progression are also underway, while AI-based screening is emerging as a useful approach.

Future efforts will focus on advancing imaging technology, improving the accuracy of AI, developing personalized treatments, exploring preventive measures, and assessing long-term patient outcomes.

This Special Issue aims to present studies that address DR screening and evaluation using existing imaging modalities; assess DR screening and the prediction of DR progression using AI-based approaches; provide comprehensive reviews of current advances; and evaluate the adoption of DR screening tools in the primary care physician (PCP) setting, the cost effectiveness of DR screening using public health data, and the future directions of DR screening.

Dr. Alauddin Bhuiyan
Prof. Dr. Roland Theodore Smith
Guest Editors

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Keywords

  • diabetic retinopathy
  • diabetic retinopathy screening
  • retinal imaging
  • age-related macular degeneration
  • artificial intelli-gence
  • image analysis
  • color fundus photography
  • optical coherence tomography imaging
  • telemedicine

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Published Papers (1 paper)

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Research

11 pages, 808 KiB  
Article
Performance and Effectiveness of Diabetic Retinopathy Screening in Portugal: An Outcome-Based Evaluation
by Inês Coelho-Costa, Amanda Silva-Pereira, Pedro Mota-Moreira, Pedro Marques-Couto, Rita Teixeira-Martins, Carolina Maia, Manuel Falcão and Rita Laiginhas
J. Clin. Med. 2025, 14(10), 3344; https://doi.org/10.3390/jcm14103344 - 12 May 2025
Viewed by 195
Abstract
Background/Objectives: Diabetic retinopathy (DR) is the leading cause of preventable blindness among working-age adults. Early detection through screening programs is essential for managing the condition and preventing visual impairment. In Portugal, the national DR screening program (DR SP) targets diabetic patients, aiming [...] Read more.
Background/Objectives: Diabetic retinopathy (DR) is the leading cause of preventable blindness among working-age adults. Early detection through screening programs is essential for managing the condition and preventing visual impairment. In Portugal, the national DR screening program (DR SP) targets diabetic patients, aiming to detect DR at an early stage and refer patients requiring intervention for an ophthalmology appointment. This study aims to assess the effectiveness of the Portuguese DR SP by analyzing patients referred for a hospital appointment following a positive screening result. Methods: An observational retrospective cohort study was conducted at Unidade Local de Saúde de São João (ULS-SJ), including patients referred to a DR SP hospital appointment between January 2020 and December 2023. Data were collected from hospital records upon approval by the Hospital Ethics Committee. Screening and hospital diagnoses were compared for agreement. The Chi-Square test and Cohen’s Kappa were used to assess the association between screening and hospital diagnoses. Results: A total of 1126 patients (2251 retinographies) were analyzed. The median time from screening to hospital consultation was 63 days (Interquartile Range = 39–99), though referral times varied widely within the same classifications (ranging from 8 to 354 days). The most common screening classifications were R2 (pre-proliferative DR, 47.8%) and M1 (maculopathy, 24.6%). In eyes with DR, agreement between screening and hospital diagnoses was highest for R2 (40.1%) and M1 (32.3%), while proliferative DR (R3) showed 30% agreement. The positive predictive value (PPV) of the screening program was 55.9%, with a false positive rate of 44.1%. A statistically significant association between screening and hospital diagnoses was observed (p < 0.001, Chi-Square test), though Cohen’s Kappa values (0.167 Right Eye, 0.157 Left eye) indicated only slight agreement. Conclusions: Our study found that DR SP effectively identifies patients needing ophthalmologic evaluation with moderate diagnostic agreement and a relatively high false positive rate, leading to unnecessary referrals. While this ensures that sight-threatening cases are not missed, improvements in grader training, classification protocols, and Optical Coherence Tomography (OCT) integration could improve results. Strengthening screening adherence and optimizing referral pathways would further improve the program’s impact on early DR detection and management. Full article
(This article belongs to the Special Issue Diabetic Retinopathy Screening: Current Advances and Future Options)
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