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Recruiting NCT05704491

NCT05704491 AI Screening for Diabetic Retinopathy

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Plain-language summary for patients
Clinical Trial Summary
NCT ID NCT05704491
Status Recruiting
Phase
Sponsor West German Center of Diabetes and Health
Condition Diabetes Mellitus
Study Type OBSERVATIONAL
Enrollment 100 participants
Start Date 2023-01-30
Primary Completion 2024-12-31

Eligibility & Interventions

Sex All sexes
Min Age 18 Years
Max Age N/A
Study Type OBSERVATIONAL
Interventions
artificial intelligence (AI) algorithm of the MONA DR model

Eligibility Fast-Check

Enter your details for a quick preliminary check. This does not replace medical advice.

What to Expect as a Participant

This is an observational study. You will not receive an experimental treatment; researchers will collect data based on your existing condition or standard treatment.

This trial targets 100 participants in total. It began in 2023-01-30 with a primary completion date of 2024-12-31.

⚠ This information is for research awareness only. Always consult your physician before joining any clinical trial. Participation is voluntary and you may withdraw at any time.

Brief Summary

The increasing prevalence of diabetes mellitus represents a major health problem, especially since around 40% of diabetic patients develop diabetic retinopathy, which severely impairs vision and can lead to blindness. This development could be prevented by annual check-ups and timely referral for treatment. However, there are major differences in the quality of examinations and bottlenecks in examination appointments. A solution to the problem could be the use of artificial intelligence (AI), especially deep learning. Initial studies have shown that deep learning algorithms can be used successfully to detect diabetic retinopathy. However, it remains to be clarified whether the use of AI can achieve a sufficiently high level of accuracy in the detection of retinopathies. Therefore, in the present study, the positive predictive value (PPV), the negative predictive value (NPV), the sensitivity (SEN) and the specificity (SPEZ) of the AI algorithm 'MONA-DR-Model' in the detection of diabetic retinopathy should be measured. In addition, it is to be examined how well the classification into mild and severe retinopathy corresponds and how well this new examination method is accepted by the patients.

Eligibility Criteria

Inclusion Criteria: * Diagnosis of diabetes mellitus * Diabetes duration ≥ 5 years * Age \> 18 years old * Patient is able to give informed consent * Fluent in written and spoken German, or interpreter present Exclusion Criteria: * History of laser treatment * Contraindication to the fundus imaging systems used in the study

Contact & Investigator

Central Contact

Stephan Martin, MD

✉ stephan.martin@uni-duesseldorf.de

📞 +49-2115660360

Frequently Asked Questions

Who can join the NCT05704491 clinical trial?

This trial is open to participants of all sexes, aged 18 Years or older, studying Diabetes Mellitus. Full inclusion and exclusion criteria are listed in the Eligibility Criteria section. Always confirm your eligibility with the research team before applying.

Is NCT05704491 currently recruiting?

Yes, NCT05704491 is actively recruiting participants. Contact the research team at stephan.martin@uni-duesseldorf.de for enrollment information.

Where is the NCT05704491 trial being conducted?

This trial is being conducted at Düsseldorf, Germany.

Who is sponsoring the NCT05704491 clinical trial?

NCT05704491 is sponsored by West German Center of Diabetes and Health. The trial plans to enroll 100 participants.

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ClinicalMetric — Independent clinical trial intelligence platform. Not affiliated with NIH, ClinicalTrials.gov, the U.S. FDA, or any pharmaceutical company, hospital, or clinical research organization. Trial data is sourced from ClinicalTrials.gov for informational purposes only and does not constitute medical advice. Do not make any treatment, enrollment, or health decisions based solely on information found here — always consult a qualified healthcare professional. Full Disclaimer  ·  Last Reviewed: April 2026  ·  Data Methodology