Using AI to screen for diabetic eye diseases at CHUM
The Use of Artificial Intelligence in the Early Detection and the Follow-Up of Diabetic Retinopathy of Diabetic Patients Followed at the CHUM: Evaluation of NeoRetina Automated Algorithm (DIAGNOS Inc.)
This study is testing if an AI tool can help find diabetic eye diseases earlier than regular eye exams for people with diabetes.
Quick facts
| Phase | Not applicable |
|---|---|
| Study type | Interventional |
| Enrollment | 630 (estimated) |
| Ages | 18 Years and up |
| Sex | All |
| Sponsor | Centre hospitalier de l'Université de Montréal (CHUM) Academic / other |
| Locations | 1 site (Montreal, Quebec) |
| Trial ID | NCT04699864 on ClinicalTrials.gov |
What this trial studies
This prospective study aims to validate the NeoRetina artificial intelligence algorithm developed by DIAGNOS Inc. for the automatic detection and grading of diabetic retinopathy (DR) through the analysis of eye fundus photographs. With over 880,000 individuals in Quebec suffering from diabetes, early detection of DR is crucial to prevent blindness, yet the public healthcare system struggles to provide timely ophthalmological evaluations. The study will compare the screening results from NeoRetina with routine evaluations conducted by ophthalmologists at the Centre hospitalier de l'Université de Montréal (CHUM). The goal is to assess whether AI can effectively facilitate early detection and follow-up of diabetic retinopathy.
Who should consider this trial
Good fit: Ideal candidates include adults aged 18 and older with a diagnosis of Type 1 or Type 2 diabetes who are being followed by a physician at CHUM.
Not a fit: Patients under 18 years old or those who have already received treatment for retinal conditions will not benefit from this study.
Why it matters
Potential benefit: If successful, this approach could significantly enhance early detection and management of diabetic retinopathy, potentially reducing the risk of blindness in diabetic patients.
How similar studies have performed: Other studies have shown promise in using AI for screening diabetic retinopathy, indicating that this approach is both innovative and supported by preliminary evidence.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: 1. Patients of 18 years old and older; 2. Ability to provide informed consent; 3. Diagnostic for diabetes : 3a) Type 1 diabetes of a lest 5 years of evolution; or 3b) Type 2 diabetes; 4. Diabetic patient followed and refered by a physician of the Centre hospitalier de l'Université de Montréal (CHUM) : 4a) followed by an endocrinologist of the CHUM; or 4b) hospitalized at the CHUM; or 4c) on the waiting list of the Ophthalmology Clinic of the CHUM for the evaluation of DR. Exclusion Criteria: 1. Patients less than 18 years old; 2. Inability to provide informed consent; 3. Patient who already had a treatment (surgery, laser, injection, etc.) for any retinal condition : Age-related macular degeneration (AMD), retinal vascular occlusion (RVO); etc.
Where this trial is running
Montreal, Quebec
- Centre hospitalier de l'Université de Montréal — Montreal, Quebec, Canada (Recruiting)
Study contacts
- Principal investigator: Karim Hammamji, MD — Centre hospitalier de l'Université de Montréal (CHUM)
- Study coordinator: Marie-Catherine Tessier, MSc
- Email: marie-catherine.tessier.chum@ssss.gouv.qc.ca
- Phone: 514-890-8000
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.