Detection and Optimization of Treatment of Severe Cases of Dry Eye Disease

What this Trial Is About

Researchers are evaluating the use of an artificial intelligence (AI) algorithm to screen for severe cases of dry eye disease (DED) in the community. The study focuses on improving primary care providers' confidence in identifying patients who need specialist care by using an image-based screening system alongside or instead of a simple symptom questionnaire called DEQ-5. This approach aims to reduce unnecessary referrals and manage dry eye more effectively outside of hospitals. The study involves analyzing corneal images taken after dye staining to detect patients with severe dry eye who may benefit from prescription eyedrops, particularly cyclosporine eyedrops for those with significant corneal staining. The AI screening tool, developed with data scientists, has shown promising accuracy in preliminary data from over 1000 images. Participants will be assessed using the AI algorithm with or without the DEQ-5 questionnaire to determine the best screening method. Participants diagnosed with dry eye will undergo eye examinations and complete questionnaires as part of the study. Researchers will measure the effectiveness of the AI screening tool in identifying severe dry eye cases requiring specialist care over a period of three years. The study also aims to support community management for less severe cases using treatments like artificial tears and eyelid warming, with plans for rescreening at later times to monitor progress.

Detection and Optimization of Treatment of Severe Cases of Dry Eye Disease