Tests AI screening for eye damage in children with type 1 diabetes
Tests AI software on eye photos to screen children with type 1 diabetes for retinopathy.
Plain-language title generated from the registry record
Registry title: Pediatric Artificial Intelligence for Retinopathy Screening in Children With Type 1 Diabetes
Key facts
- Where
- Prague, CzechiaSee the site
Could this be for you?
Answer for yourself. This is not a decision: only the study team can say whether you can take part.
- Are you between 11 and 19 years old?
Source: NCT07149142, who can take part
Where in Czechia
- University Hospital MotolPrague, CzechiaTaking people
Questions to ask the study team
- How often do I need to come in, and for how long each time?
- Are travel costs paid?
- Can I keep my own doctor?
- What happens if I want to stop?
Trial details
- Who runs it
- University Hospital, Motol
- Trial code
- NCT07149142
- Record updated
- 20 July 2026
- Original description
The proposed project is a clinical intervention trial testing the feasibility and effectiveness of diabetic retinopathy screening evaluated by artificial intelligence (AI) based software in children with type 1 diabetes (CwD). Another novel method, the confocal microscopy of the retina will be used to assess the early stages of diabetic neuropathy. In parallel, we aim to assess the prevalence of diabetic retinopathy and neuropathy in a well-controlled population of CwD at a tertiary diabetes care center.Read full original descriptionShow less
Feasibility and Effectiveness of Diabetic Retinopathy Screening Using Artificial Intelligence in Children With Type 1 Diabetes
The proposed project is a clinical intervention trial testing the feasibility and effectiveness of diabetic retinopathy screening evaluated by artificial intelligence (AI) based software in children with type 1 diabetes (CwD). Another novel method, the confocal microscopy of the retina will be used to assess the early stages of diabetic neuropathy. In parallel, we aim to assess the prevalence of diabetic retinopathy and neuropathy in a well-controlled population of CwD at a tertiary diabetes care center.
Each participant will undergo an examination of diabetic retinopathy using the non-mydriatic fundus camera. The resulting photography will be evaluated by AI driven software. The participant will then follow this examinaton with fundus ophtalmoscopy in arteficial mydriasis as a standard method of diabetic retinopathy assessment. Another method, the optic coherence tomography (OCT), which is considered as the most sensitive method for diabetic retinopathy assessment, will be performed after that. The results of these methods will be compared to assess the sensitivity of each. The examination-satisfaction questionnaire will be given to the participants.
In subjects over 18 years, a confocal microscopy of the retina examination will be performed to assess the status of the corneal sub-basal nerve plexus and the presence of diabetic neuropathy will be noted.
The prevalence of diabetic retinopathy and neuropathy in this group of children with diabetes will be assessed based on the results.
Inclusion: Type 1 diabetes diagnosed according to the ADA criteria; Age over 11.0 years or duration of diabetes over 2 years; Signed written informed consent by both the CwD and their parent/caregiver.
Exclusion: Unwillingness to sign a written informed consent by both the CwD and their parent/caregiver.