Comparing Artificial Intelligence for Assisted Diagnosis of Diabetic Retinopathy
A Comparative Analysis of the Diagnostic Outcomes of Artificial Intelligence-assisted Fundus Photography for Diabetic Retinopathy and Diabetic Macular Edema Versus Other Imaging Devices in Ophthalmology: A Controlled Trial
1 other identifier
observational
1,000
1 country
1
Brief Summary
This study plans to compare the accuracy of artificial intelligence (AI)-assisted fundus images with other ophthalmic devices such as optical coherence tomography (OCT) and fundus fluorescence angiography (FFA) in the diagnosis of diabetic retinopathy and diabetic macular edema.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for all trials
Started Jul 2024
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
May 9, 2024
CompletedFirst Posted
Study publicly available on registry
May 21, 2024
CompletedStudy Start
First participant enrolled
July 10, 2024
CompletedPrimary Completion
Last participant's last visit for primary outcome
September 1, 2025
CompletedStudy Completion
Last participant's last visit for all outcomes
December 31, 2025
CompletedJuly 9, 2024
July 1, 2024
1.1 years
May 9, 2024
July 4, 2024
Conditions
Keywords
Outcome Measures
Primary Outcomes (1)
The accuracy
Detection of DR accuracy using fundus photography, optical coherence tomography, and fundus fluorescence angiography
Baseline-Month 12
Secondary Outcomes (1)
The accuracy
Baseline-Month 12
Study Arms (3)
artificial intelligence-assisted fundus photography
Artificial intelligence-assisted fundus photography in patients with diabetic retinopathy
optical coherence tomography
optical coherence tomography in patients with diabetic retinopathy
fundus fluorescence angiography
fundus fluorescence angiography in patients with diabetic retinopathy
Interventions
using artificial intelligence to identify diabetic retinopathy using fundus photography
detect diabetic retinopathy and diabetic macular edema by optical coherence tomography
detect diabetic retinopathy by fundus fluorescence angiography
Eligibility Criteria
It is planned to include 1,000 participants in the study, all of whom will undergo fundus photography, 500 additional patients will undergo fundus fluorescence angiography, and 500 additional patients will undergo optical coherence tomography. All participants met inclusion and exclusion criteria.
You may qualify if:
- Diagnostic for diabetes: Type 1 diabetes of a lest 5 years of evolution; or Type 2 diabetes;
- Obtaining informed consent;
- Patient age 18 or above.
You may not qualify if:
- Patients under 18 years of age;
- Failure to Obtain informed consent;
- Presence of other retinal diseases;
- A patient who has already undergone the treatment.
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
The Second Affiliated Hospital Zhejiang University School of Medicine
Hangzhou, Zhejiang, 310000, China
MeSH Terms
Conditions
Interventions
Condition Hierarchy (Ancestors)
Intervention Hierarchy (Ancestors)
Central Study Contacts
Study Design
- Study Type
- observational
- Observational Model
- COHORT
- Time Perspective
- PROSPECTIVE
- Sponsor Type
- OTHER
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- Director
Study Record Dates
First Submitted
May 9, 2024
First Posted
May 21, 2024
Study Start
July 10, 2024
Primary Completion
September 1, 2025
Study Completion
December 31, 2025
Last Updated
July 9, 2024
Record last verified: 2024-07
Data Sharing
- IPD Sharing
- Will not share