Type 1 Diabetes Mellitus
Conditions
Keywords
Diabetic Retinopathy, Diabetic Neuropathy, Artificial Intelligence
Brief summary
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.
Interventions
DIAGNOSTIC_TESTNon-mydriatic fundus camera photography
Non-mydriatic fundus camera photography assessed by artificial intelligence software
DIAGNOSTIC_TESTFundus ophtalmoscopy
Fundus opthalmoscopy assessed by an experienced ophtalmologist
DIAGNOSTIC_TESTOptic coherence tomography
Optic coherence tomography assessed by an experienced ophtalmologist
DIAGNOSTIC_TESTConfocal microscopy of the retina
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
Sponsors
University Hospital, Motol
Study design
Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
DIAGNOSTIC
Masking
NONE
Eligibility
Sex/Gender
ALL
Age
11 Years to 19 Years
Healthy volunteers
No
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
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Feasibility of AI for retinopathy screening | 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
| Measure | Time frame | Description |
|---|---|---|
| Examination satisfaction | 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. |
| Prevalence of diabetic retinopathy | Through study completion, on average 6 months. | Prevalence of diabetic retinopathy among CwD in a single center with favorable glucose control |
| Prevalence of diabetic neuropathy | 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 |
Countries
Czechia
Contacts
CONTACTVit Neuman, MD, PhD
Outcome results
None listed