NCT07404657

Brief Summary

This study is being done to evaluate the performance of a software that uses artificial intelligence to analyze photographs of the retina to help detect diabetic retinopathy. The study will also assess the safety of the software in combination with a fundus camera already available on the market. This software analyzes retinal photographs to detect more than mild diabetic retinopathy in adults with diabetes. The results will be compared to expert human evaluations.

Trial Health

35
At Risk

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Trial has exceeded expected completion date
Enrollment
198

participants targeted

Target at P50-P75 for all trials

Timeline
Completed

Started Feb 2026

Shorter than P25 for all trials

Status
not yet recruiting

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

Study Start

First participant enrolled

February 1, 2026

Completed
4 days until next milestone

First Submitted

Initial submission to the registry

February 5, 2026

Completed
6 days until next milestone

First Posted

Study publicly available on registry

February 11, 2026

Completed
2 months until next milestone

Primary Completion

Last participant's last visit for primary outcome

April 1, 2026

Completed
Same day until next milestone

Study Completion

Last participant's last visit for all outcomes

April 1, 2026

Completed
Last Updated

February 11, 2026

Status Verified

February 1, 2026

Enrollment Period

2 months

First QC Date

February 5, 2026

Last Update Submit

February 5, 2026

Conditions

Diabetic Retinopathy (DR)

Outcome Measures

Primary Outcomes (1)

  • Number of subjects whose results provided by the automatic AI-based tool match the reading center grading for the identification of referable diabetic eye disease (more than mild DR).

    1-day visit

Secondary Outcomes (1)

  • percentage of eyes for which the AI-based automatic tool produced a result

    1-day visit

Interventions

automatic analysis of fundus images performed by the software tool based on artificial intelligenceDEVICE

the duration of the intervention is the analysis performed by the software tool based on fundus images acquired

Eligibility Criteria

Age22 Years+
Sexall
Healthy VolunteersNo
Age GroupsAdult (18-64), Older Adult (65+)
Sampling MethodNon-Probability Sample
Study Population

population attending a primary-care facility with diagnosis of diabetes mellitus and/or past diagnosis of diabetic retinopathy

You may qualify if:

  • years old or older
  • diabetes or diabetic retinopathy
  • understand the study information and able to sign a consent form

You may not qualify if:

  • cannot tolerate eye imaging tests
  • laser treatment or injections
  • eye surgery, except for simple cataract surgery
  • currently involved in another study
  • pregnant
  • cannot or do not want to have your eyes dilated
  • photodynamic therapy within the last 90 days

Contact the study team to confirm eligibility.

Sponsors & Collaborators

MeSH Terms

Conditions

Diabetic Retinopathy

Condition Hierarchy (Ancestors)

Retinal DiseasesEye DiseasesDiabetic AngiopathiesVascular DiseasesCardiovascular DiseasesDiabetes ComplicationsDiabetes MellitusEndocrine System Diseases

Central Study Contacts

Rui

CONTACT

00393357442593chiara.rui@icare-world.com

Rumiato

CONTACT

ra.imaging@icare-world.com

Study Design

Study Type
observational
Observational Model
CASE ONLY
Time Perspective
CROSS SECTIONAL
Sponsor Type
INDUSTRY
Responsible Party
SPONSOR

Study Record Dates

First Submitted

February 5, 2026

First Posted

February 11, 2026

Study Start

February 1, 2026

Primary Completion

April 1, 2026

Study Completion

April 1, 2026

Last Updated

February 11, 2026

Record last verified: 2026-02