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NCT Number: NCT07149142

Pediatric Artificial Intelligence for Retinopathy Screening 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.

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Key information

Conditions

Type 1 Diabetes Mellitus Autoimmune Diseases Cardiovascular Diseases Diabetes Complications Diabetes Mellitus Diabetes Mellitus, Type 1 Diabetic Angiopathies Diabetic Neuropathies Diabetic Retinopathy Endocrine System Diseases Eye Diseases Glucose Metabolism Disorders Immune System Diseases Metabolic Diseases Nervous System Diseases Neuromuscular Diseases Nutritional and Metabolic Diseases Peripheral Nervous System Diseases Retinal Diseases Vascular Diseases

Age range

11 year–19 year

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

University Hospital Motol

Prague, Prague 5, 15006, Czechia

Location status: Recruiting

Location contact

Vit Neuman, MD, PhD

CONTACT

[email protected]

+420224432090

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • 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 criteria

  • Unwillingness to sign a written informed consent by both the CwD and their parent/caregiver

Treatment and study plan

Non-mydriatic fundus camera photography

Diagnostic Test

Non-mydriatic fundus camera photography assessed by artificial intelligence software

Fundus ophtalmoscopy

Diagnostic Test

Fundus opthalmoscopy assessed by an experienced ophtalmologist

Optic coherence tomography

Diagnostic Test

Optic coherence tomography assessed by an experienced ophtalmologist

Confocal microscopy of the retina

Diagnostic Test

In a subset of participants over 18 years of age, confocal microscopy of the retina will be performed to assess the presence of diabetic neuropathy

Primary outcomes

  1. Feasibility of AI for retinopathy screening

    Time frame: Through study completion, on average 6 months.

    The primary objective of this study is to test whether performing the diabetic retinopathy screening using the non-mydriatic fundus camera with AI software is feasible. The exact outcome is the percent of participants who will agree to undergo the procedure and will obtain a valid result (either positive or negative).

Secondary outcomes

  1. Examination satisfaction

    Time frame: Through study completion, on average 6 months.

    Participant and caregiver reported examination satisfaction assessed by a structured questionnaire on a Lickert scale from 1 to 5.

  2. Prevalence of diabetic retinopathy

    Time frame: Through study completion, on average 6 months.

    Prevalence of diabetic retinopathy among CwD in a single center with favorable glucose control

  3. Prevalence of diabetic neuropathy

    Time frame: Through study completion, on average 6 months.

    Prevalence of diabetic neuropathy in young people with diabetes (over 18 years) in a single center with favorable glucose control

Study contacts

Contact information is provided by the study sponsor or research team.

Vit Neuman, MD, PhD

CONTACT

[email protected]

+420 224 432 090

Sponsors and collaborators

Lead sponsor

University Hospital, Motol

Other

Registry information

Official study title

Feasibility and Effectiveness of Diabetic Retinopathy Screening Using Artificial Intelligence in Children With Type 1 Diabetes

Acronym: PAIRS-T1D

Important dates

Study start
2026
Primary completion
2027
Study completion
2029
First posted
Aug 29, 2025
Registry last updated
Jul 20, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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