Application of Artificial Intelligence in Early Detection of Eye Complications in Diabetics: A Randomized Clustered Trial in Hail, Saudi Arabia
Trial Snapshot
- Phase
- Not Applicable
- Status
- Not yet recruiting
- Sponsor
- Enrollment
- 440
- Primary Endpoint
- The detection rate of macular oedema in the intervention group vs. control group.
Study Overview
Brief Summary
The goal of this pragmatic trial is to test the benefit of using artificial intelligence-based eye screening i.e, a fundus camera device in the early detection of eye complications in diabetics. The main questions it aims to answer are:
To what extent does the application of artificial intelligence-based eye care at primary care clinics work well in achieving early detection of eye complications such as macular oedema? To what extent does the application of artificial intelligence-based eye care at primary care clinics work well in achieving early detection of eye complications such as retinopathy? Participants will be asked to participate in the screening for eye complications at primary care centres, and a fundus camera will be used for screening.
Researchers will compare the proportion of detected cases with early signs of eye complication among those using artificial intelligence-based eye screening i.e., fundus camera, to the proportion of detected cases among those using routine eye care clinics at the primary care centre.
Early detection of eye complications in diabetics prevents the risk of blindness.
Detailed Description
In the era of artificial inelegance(AI), a shift from tertiary to secondary and primary care when caring for a patient with diabetic retinopathy is highly recommended.
Due to low operation, AI could be used in the early detection and screening of diabetic retinopathy by application of the service across a mass population and resource-limited areas with a scarcity of eye care services.
AI-based eye care in terms of screening for diabetic retinopathy will make the screening process more effective and cheap and could be delegated to technicians, practitioners, and/or even home-based self-screening.
Recognizing the high prevalence of type 2 diabetes mellitus (T2DM) among adults, the use of a nonmydriatic fundus camera with AI is effective in eye exams as it improves adult adherence to eye screening.
The primary aim of the trial will be to assess the effectiveness of the application of AI devices in terms of fundus cameras in the early detection of diabetic retinopathy and macular oedema among diabetic patients attending primary care centres.
Study Design
- Study Type
- Interventional
- Allocation
- Randomized
- Intervention Model
- Parallel
- Primary Purpose
- Screening
- Masking
- None
Eligibility Criteria
- Ages
- 18 Years to 90 Years (Adult, Older Adult)
- Sex
- All
- Accepts Healthy Volunteers
- Yes
Inclusion Criteria
- •Diabetic patients aged 18-90
Exclusion Criteria
- •Severely ill patient or patient with cancer
Outcomes
Primary Outcomes
The detection rate of macular oedema in the intervention group vs. control group.
Time Frame: 6 month from the start of the study
The proportion of the individuals who screened positive for macular oedema in the intervention group vs. control group.
The detection rate of diabetic retinopathy in the intervention group vs. control group
Time Frame: 6 month from the start of the study
The proportion of the detected cases of diabetic retinopathy in the intervention group vs. control group
Secondary Outcomes
- The screening rate for retinopathy(6 months after the start of the study)
- The screening rate for macular odema(6 months after the start of the study)