Artificial Intelligence-Aided Screening for Patients With Diabetic Retinopathy and Age-related Macular Degeneration in Family Medicine and Geriatric Medicine Outpatient Clinics

National Taiwan University

Status: Enrolling

Conditions: Diabetic Retinopathy (DR); Age-Related Macular Degeneration (AMD)

Treatments: Other: Standard fundus photography with physician interpretation; Other: VeriSee AI-assisted screening tools for diabetic retinopathy and age-related macular degeneration

Study type: Interventional

Funder types: Other

Identifiers

NCT07069647

FJUH114483 (Registry Identifier)

CIRB2025003 (Registry Identifier)

202505015DINE

Details and patient eligibility

About

Diabetic retinopathy (DR) and age-related macular degeneration (AMD) are leading causes of vision loss, with rising incidence due to aging populations and increasing diabetes prevalence. However, delayed diagnoses are common due to low disease literacy and lack of dedicated screening tools in internal medicine. This multi-center RCT at National Taiwan University Hospital evaluates the clinical effectiveness and cost-effectiveness of the VeriSee AI-assisted diagnostic software for DR and AMD screening. Participants include adults with diabetes and individuals aged 50 and above meeting AMD screening criteria, randomized to AI-assisted screening with immediate physician explanation or standard physician-only screening. Primary outcomes include detection rates of DR and AMD, ophthalmology referral outcomes, and patient/physician satisfaction. Data collection will occur from April 2025 to December 2027. This study aims to provide evidence on the clinical utility of AI-assisted ophthalmic screening in improving early detection, facilitating timely treatment, and reducing severe visual impairment and healthcare burdens in real-world clinical settings.

Full description

Background Diabetic retinopathy (DR) and age-related macular degeneration (AMD) are major cause of vision impairment. With an aging population and the increasing prevalence of diabetes, the incidence of both DR and AMD continue to rise. However, due to limited disease literacy and lack of dedicated fundus screening tools in department of internal medicine, many patients are diagnosed and treated at a late stage of the disease. This study aims to evaluate the clinical value of VeriSee artificial intelligence (AI) - assisted diagnostic software among patients with diabetes and the elderly population, focusing on their screening effectiveness and feasibility.

Objective This study aims to evaluate the effectiveness of the VeriSee - an AI-assisted diagnostic software for DR and AMD - in improving the screening rates of macular degeneration, diabetic retinopathy and glaucoma, as well as reducing the incidence of severe visual impairment and lowering overall healthcare burdens. Simultaneously, the investigators will conduct and cost-effectiveness assessment of the VeriSee AI-assisted diagnostic software.

Methods This study is a multicenter, two-arm, parallel-group, open-label, individual-level randomized controlled trial (RCT) conducted at the main branch and Bei-Hu branch of National Taiwan University Hospital. Study participants include: (1) individuals aged 50 and above who meet the screening criteria for AMD; and (2) individuals aged 20 and above with diabetes who meet the screening criteria for DR. Participants are randomized into two groups: (1) the intervention group (AI-assisted screening) in which participants will receive the AI-assisted image analysis followed by immediate explanation of results by a physicians, with ophthalmology referral as needed; and (2) the control group (physician only screening), in which participants undergo standard fundus photography interpreted by physicians, with results discussed during a subsequent visit. During the trial, the ophthalmology referral rates and subsequent diagnostic outcomes will be tracked to evaluate the effectiveness of the AI-assisted diagnostic approach.

Results The study was funded in September 2024. Data collection is expected to last from April 2025 to December 2027. The primary outcome of this study is the detection rate of DR and AMD using the AI-assisted diagnostic software and its impact on diagnosis and treatment following the referral. Referral outcomes will be tracked through electronic medical records (EMR), and both patient and physician satisfaction survey will be conducted to evaluate the feasibility and acceptability of AI implementation in clinical settings.

Conclusions This study is expected to provide evidence on the clinical effectiveness and application value of AI-assisted ophthalmic screening, while also exploring its impact on healthcare procedures and patient care. By enhancing the detection rate of retinal diseases among individuals with diabetes and the elderly, AI-assisted technologies may facilitate earlier diagnosis and timely treatment, potentially improving the visual health and overall quality of life.

Enrollment: 4,300 estimated patients

Sex: All

Ages: 20+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• VeriSee AMD is used in non-retinal subspecialty ophthalmology clinics for adults aged 50 and above.
• VeriSee DR is used in non-retinal subspecialty clinics for diabetic patients aged 20 and above.

Exclusion criteria

• The patient does not agree to participate in the trial or is unable to provide informed consent.

Trial design

Primary purpose: Screening

Allocation: Randomized

Interventional model: Parallel Assignment

Masking: None (Open label)

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4,300 participants in 2 patient groups

AI-Assisted Screening

Experimental group

Description:

Intervention group (physicians assisted by AI): After the fundus photography is completed, the AI software (VeriSee AMD and VeriSee DR) will automatically retrieve and analyze the image data from Picture Archiving and Communication System (PACS) to generate the results. The research team will immediately provide the AI-generate results to physicians, enabling participants to receive their reports and results during the same visit. If any abnormalities are detected, the physicians will refer the participants for further ophthalmologic evaluation.

Treatment:

Other: VeriSee AI-assisted screening tools for diabetic retinopathy and age-related macular degeneration

Standard Physician Screening

Active Comparator group

Description:

Control group (physicians diagnosing without AI assistance): After the fundus photography is completed, participants will need to schedule a follow-up appointment with the attending physicians to receive their report and have preliminary assessment of the possibility of DR or AMD. If the physician detects any abnormalities, the physicians will refer the participants for further ophthalmologic evaluation.

Treatment:

Other: Standard fundus photography with physician interpretation