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Barriers and Determinants of Referral Adherence in AI-Enabled Diabetic Retinopathy Screening for Older Adults in Northern India During the COVID-19 Pandemic: Mixed Methods Pilot Study

Barriers and Determinants of Referral Adherence in AI-Enabled Diabetic Retinopathy Screening for Older Adults in Northern India During the COVID-19 Pandemic: Mixed Methods Pilot Study

Diabetic retinopathy (DR) is a prevalent and severe microvascular complication of diabetes mellitus (DM) [1]. In India, 10.9% (7.2%‐16.3%) of individuals aged 65 years and above with diabetes have DR, with 2.3% (1.2%‐4.4%) suffering from vision-threatening diabetic retinopathy (VTDR) [1], characterized by severe retinopathy or macular edema [2]. DR is typically asymptomatic in its early stages, and it can lead to visual impairment or blindness if left untreated [3].

Anshul Chauhan, Anju Goyal, Ritika Masih, Gagandeep Kaur, Lakshay Kumar, ­ Neha, Harsh Rastogi, Sonam Kumar, Bidhi Lord Singh, Preeti Syal, Vishali Gupta, Luke Vale, Mona Duggal

JMIR Form Res 2025;9:e67047

Evaluation of Artificial Intelligence Algorithms for Diabetic Retinopathy Detection: Protocol for a Systematic Review and Meta-Analysis

Evaluation of Artificial Intelligence Algorithms for Diabetic Retinopathy Detection: Protocol for a Systematic Review and Meta-Analysis

Diabetic retinopathy (DR) has a profound presence in medicine and ophthalmology. It is one of the most common complications of diabetes mellitus (DM), attacking many areas of the body and causing issues like end-stage renal disease and cardiovascular illness [1].

Jaime Angeles Sesgundo III, David Collin Maeng, Jumelle Aubrey Tukay, Maria Patricia Ascano, Justine Suba-Cohen, Virginia Sampang

JMIR Res Protoc 2024;13:e57292

Diagnostic Accuracy of Detecting Diabetic Retinopathy by Using Digital Fundus Photographs in the Peripheral Health Facilities of Bangladesh: Validation Study

Diagnostic Accuracy of Detecting Diabetic Retinopathy by Using Digital Fundus Photographs in the Peripheral Health Facilities of Bangladesh: Validation Study

This classification divides the diagnosis of diabetic retinopathy into 5 stages: no diabetic retinopathy, mild nonproliferative diabetic retinopathy, moderate nonproliferative diabetic retinopathy, severe nonproliferative diabetic retinopathy, and proliferative diabetic retinopathy.

Tahmina Begum, Aminur Rahman, Dilruba Nomani, Abdullah Mamun, Alayne Adams, Shafiqul Islam, Zara Khair, Zareen Khair, Iqbal Anwar

JMIR Public Health Surveill 2021;7(3):e23538

Dermatologists’ Adherence to the Latest Recommendations for Screening of Hydroxychloroquine Retinopathy in Saudi Arabia: Cross-Sectional Study

Dermatologists’ Adherence to the Latest Recommendations for Screening of Hydroxychloroquine Retinopathy in Saudi Arabia: Cross-Sectional Study

However, retinopathy debatably remains HCQ’s most feared adverse effect. The mechanism of HCQ-induced retinopathy is not fully known, but buildup in the retinal pigment epithelium could cause this condition [8]. Recently, the prevalence of HCQ-induced retinopathy was estimated to be higher than that assumed earlier (7.5%) [9].

Nouf Talal Mleeh, Nujood Abdulwahed Alzahrani, Jehad Osama Hariri, Hatan Hisham Mortada, Mohammed Ridha Algethami

Interact J Med Res 2019;8(4):e15218