Comparing Artificial Intelligence for Assisted Diagnosis of Diabetic Retinopathy

NCT ID: NCT06423274

Last Updated: 2024-07-09

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

NOT_YET_RECRUITING

Total Enrollment

1000 participants

Study Classification

OBSERVATIONAL

Study Start Date

2024-07-10

Study Completion Date

2025-12-31

Brief Summary

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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.

Detailed Description

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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.

This study was conducted as a prospective study. Participants meeting eligibility criteria will be recruited from sites staffed by trained photographers. After assessing eligibility and obtaining informed consent, fundus photographs will be taken using a non-dilated fundus camera. And optical coherence tomography or fundus fluorescence angiography will be performed.

Conditions

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Diabetic Retinopathy Diabetic Macular Edema

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Study Groups

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artificial intelligence-assisted fundus photography

Artificial intelligence-assisted fundus photography in patients with diabetic retinopathy

fundus photography

Intervention Type DIAGNOSTIC_TEST

using artificial intelligence to identify diabetic retinopathy using fundus photography

optical coherence tomography

optical coherence tomography in patients with diabetic retinopathy

optical coherence tomography

Intervention Type DIAGNOSTIC_TEST

detect diabetic retinopathy and diabetic macular edema by optical coherence tomography

fundus fluorescence angiography

fundus fluorescence angiography in patients with diabetic retinopathy

fundus fluorescence angiography

Intervention Type DIAGNOSTIC_TEST

detect diabetic retinopathy by fundus fluorescence angiography

Interventions

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fundus photography

using artificial intelligence to identify diabetic retinopathy using fundus photography

Intervention Type DIAGNOSTIC_TEST

optical coherence tomography

detect diabetic retinopathy and diabetic macular edema by optical coherence tomography

Intervention Type DIAGNOSTIC_TEST

fundus fluorescence angiography

detect diabetic retinopathy by fundus fluorescence angiography

Intervention Type DIAGNOSTIC_TEST

Eligibility Criteria

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Inclusion Criteria

1. Diagnostic for diabetes: Type 1 diabetes of a lest 5 years of evolution; or Type 2 diabetes;
2. Obtaining informed consent;
3. Patient age 18 or above.

Exclusion Criteria

1. Patients under 18 years of age;
2. Failure to Obtain informed consent;
3. Presence of other retinal diseases;
4. A patient who has already undergone the treatment.
Minimum Eligible Age

18 Years

Maximum Eligible Age

90 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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Zhejiang University

OTHER

Sponsor Role lead

Responsible Party

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Wu Hongkang

Director

Responsibility Role PRINCIPAL_INVESTIGATOR

Locations

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The Second Affiliated Hospital Zhejiang University School of Medicine

Hangzhou, Zhejiang, China

Site Status

Countries

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China

Central Contacts

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Hongkang Wu, MMS

Role: CONTACT

+8618969978676

Facility Contacts

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Hongkang Wu, MMS

Role: primary

18969978676

Other Identifiers

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DR artificial intelligence

Identifier Type: -

Identifier Source: org_study_id

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