Stop Blindness in Coastal Bangladesh: Testing the Effectiveness of Community-Based, Artificial Intelligence-Assisted Eye Disease Screening in Coastal Bangladesh
Led by Data Yakka, Inc. · Updated on 2025-08-22
20000
Participants Needed
1
Research Sites
26 weeks
Total Duration
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AI-Summary
Brief Title
Who Can Participate
AI-Screening
Your Study Journey
Trial Site Locations
Research Team
How is the study designed?
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Frequently Asked Questions
Research Publications
Sponsors
D
Data Yakka, Inc.
Lead Sponsor
B
Bangladesh Disaster Preparedness Centre
Collaborating Sponsor
AI-Summary
What this Trial Is About
Eye disease affects billions worldwide, causing vision problems that impact daily life and productivity. This research focuses on eye health in coastal Bangladesh, a region with high poverty, limited healthcare access, and environmental risks that increase eye disease prevalence. The study evaluates a community-based eye screening program using Artificial Intelligence (AI) to detect conditions like diabetic retinopathy, glaucoma, cataracts, and age-related macular degeneration, aiming to improve early diagnosis and care in underserved areas.
The program offers a twelve-step eye screening process supported by AI-assisted fundus imaging, combined with partnerships among local organizations and healthcare providers. Screening includes community outreach, vision tests, blood pressure and glucose checks, optometrist evaluations, and selective AI imaging for higher-risk individuals based on age, diabetes, hypertension, or symptoms. Patients diagnosed with severe cataracts are offered surgery through local or regional services. The approach integrates data collection, AI analysis, clinical examinations, counseling, and referrals to support comprehensive eye care.
Participants aged 35 and older from the Char Fasson sub-district undergo screening and follow-up over several months. The study collects demographic, clinical, and imaging data securely, with informed consent for storing fundus images. Researchers monitor the number of individuals screened and the prevalence of eye diseases. Safety and data privacy are maintained using encrypted systems and compliance with ethical standards. The program's feasibility, cost, and effectiveness in improving eye care accessibility are assessed throughout the study.
CONDITIONS
Brief Title
"My Eyes, My Light": Amar Chokh, Amar Alo
Who Can Participate
Age: 35Years +
All Genders
Healthy Volunteers
Eligibility Criteria
You may qualify if you...
Age 35+ years
Residing in the Sub-District of Char Fasson in the Bhola District
You will not qualify if you...
Known eye disease diagnosis
AI-Screening
AI-Powered Screening
Complete this quick 3-step screening to check your eligibility
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Your Study Journey
Screening
Duration - 2 to 4 weeks
Participants are screened for eligibility to participate in the trial.
1 visit (in-person)
Diagnostic Evaluation
Duration - Up to 10 months
Participants undergo a multimodal eye disease screening process which includes community awareness, registration, blood pressure and blood glucose measurement, vision test, optometrist evaluation, informed consent for imaging, fundus imaging for eligible participants, AI-based disease detection, ophthalmologist examination, specialist review, counseling, and referral as needed.
Multiple visits depending on participant eligibility for imaging and follow-up
Treatment
Duration - Variable depending on surgery scheduling
Participants diagnosed with high-grade cataracts and visual impairment are offered cataract surgery through local or regional vision services.
1 to 2 visits depending on surgical care
Long-term Monitoring
Duration - Up to 6 months or longer after intervention
Participants who receive screening and/or surgery may be monitored for eye health outcomes and ongoing care needs.
Causes of blindness and vision impairment in 2020 and trends over 30 years, and prevalence of avoidable blindness in relation to VISION 2020: the Right to Sight: an analysis for the Global Burden of Disease Study.
GBD 2019 Blindness and Vision Impairment Collaborators, Vision Loss Expert Group of the Global Burden of Disease Study