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NCT03112005

Assessment of EyeArt as an Automated Diabetic Retinopathy Screening Tool

Completed Last updated 30 July 2018
What this trial tests

trial testing Color fundus photography in Diabetic Retinopathy in 942 participants. Completed in 31 May 2018.

Timeline
17 April 2017
Primary endpoint
31 May 2018
31 May 2018

Quick facts

Lead sponsorEyenuk, Inc.
StatusCompleted
Study typeOBSERVATIONAL
Enrollment942
Start date17 April 2017
Primary completion31 May 2018
Estimated completion31 May 2018
Sites1 location across United States

Drugs / interventions tested

Conditions studied

Sponsor

Eyenuk, Inc. — full company profile →

Who can join

18 and older, any sex, with Diabetic Retinopathy or Diabetic Eye Problems. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

More than 29 million people in the US are living with diabetes, many of whom will develop diabetic retinopathy (DR) or diabetic macular edema (DME) collectively known as diabetic eye disease (DED), the leading cause of vision loss and blindness in working-age adults. Annual eye screening is recommended for all diabetic patients since vision loss can be prevented with laser photocoagulation and anti-VEGF treatment if DR is diagnosed in its early stages. Currently, the number of clinical personnel trained for DR screening is orders of magnitude smaller than that needed to screen the large, growing diabetic population. Therefore, to meet this large unmet need for DR screening, a fully-automated computerized DR screening system is necessary. EyeArt is an automated screening device designed automatically analyze color fundus photographs of diabetic patients to identify patients with referable or vision threatening DED. This study is designed to assess the safety and efficacy of EyeArt.

Publications & conference data

2 peer-reviewed publications reference this trial (live from Europe PMC):

  1. Pivotal Evaluation of an Artificial Intelligence System for Autonomous Detection of Referrable and Vision-Threatening Diabetic Retinopathy.
    Ipp E, Liljenquist D, Bode B, Shah VN, et al · · 2021 · cited 146× · PMID 34779843 · DOI 10.1001/jamanetworkopen.2021.34254
  2. Artificial Intelligence Detection of Diabetic Retinopathy: Subgroup Comparison of the EyeArt System with Ophthalmologists' Dilated Examinations.
    Lim JI, Regillo CD, Sadda SR, Ipp E, et al · · 2023 · cited 80× · PMID 36345378 · DOI 10.1016/j.xops.2022.100228

Verify or expand the search:

Other trials of Color fundus photography

Trials testing the same drug.

Other recruiting trials for Diabetic Retinopathy

Currently open trials in the same condition.

Other Eyenuk, Inc. trials

Trials by the same sponsor.

Verify against primary sources

Data sources for this page

Drug Landscape aggregates and links these public records for informational use only. Always verify against the primary source before clinical or regulatory decisions. Canonical URL: https://druglandscape.com/trial/NCT03112005.

Primary sources · FDA · ClinicalTrials.gov · EMA · SEC EDGAR · ChEMBL · Wikidata · full sourcing