AI-based analysis to find subgroups in adults with type 1 diabetes
Official title: Caracterización de Subgrupos de Personas Con Diabetes Tipo 1: análisis de características clínicas y glucométricas Utilizando Una aproximación de Inteligencia Artificial
Run by Fundació Institut de Recerca de l'Hospital de la Santa Creu i Sant Pau · NCT07461805 · Data updated 2026-11-12
This project will use artificial intelligence on medical records and continuous glucose monitor data to see if there are distinct subtypes among adults with type 1 diabetes.
Quick facts
| Study type | Observational |
|---|---|
| Ages | 18 Years and up |
| Sex | All |
| Enrollment | 800 (estimated) |
| Sponsor | Fundació Institut de Recerca de l'Hospital de la Santa Creu i Sant Pau Academic / other |
| Locations | 1 site (Barcelona, Barcelona) |
| Status | Recruiting |
| Started | November 4, 2025 |
| Main results expected | June 2028 |
| Study ends | December 2028 |
| Registry record updated | March 10, 2026 |
| Trial ID | NCT07461805 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Adults (18 years or older) with type 1 diabetes who have used continuous glucose monitoring for at least six months in 2024 and receive regular follow-up at the Hospital de la Santa Creu i Sant Pau are the intended participants.
✕Probably not a fit
Patients without CGM data, pediatric patients, or those not followed at the enrolling hospital are unlikely to benefit from or be eligible for this project.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This ambispective observational project will combine retrospective and prospective clinical data and continuous glucose monitoring (CGM) metrics from about 800 adults with type 1 diabetes followed at Hospital de la Santa Creu i Sant Pau. Artificial intelligence clustering methods will be applied to clinical and glucometric features to identify potential subgroups and characterize their profiles. Secondary analyses will examine cluster stability over 1–3 years, the variables driving cluster membership, and whether clusters predict diabetes-related complications. Participation requires only consent to access existing electronic medical records and CGM platform data, with no additional visits or tests.
Why it matters
Potential benefit: If successful, the results could enable more personalized care by identifying subgroups with different risks and treatment needs.
How similar studies have gone: Data-driven clustering approaches have shown promise in diabetes research, though applying AI to combined clinical and CGM data specifically in type 1 diabetes is relatively novel.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * Individuals with type 1 diabetes (T1D) aged 18 years or older. * T1D individuals expected to have regular follow-up at the Endocrinology and Nutrition Department of Hospital de la Santa Creu i Sant Pau. * Users of continuous glucose monitoring (CGM) systems for at least the last 6 months of 2024. * Willingness and ability to provide written informed consent to participate in the study (by the patient or his/her representative). Exclusion Criteria: * Presence of severe comorbidities or medical conditions that, in the investigator's judgment, could interfere with participation in the study or the interpretation of results. This circumstance is expected to be exceptional, as the study aims to be as inclusive as possible.
Where it's running
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Hospital de la Santa Creu i Sant Pau, Barcelona, Barcelona 08041
Barcelona, Barcelona, Spain Recruiting
Study contacts
- Principal investigator: Rosa M Corcoy — Fundació Institut de Recerca de l'Hospital de la Santa Creu i Sant Pau
- Study coordinator: Eva Safont, MD
- Email: esafont@santpau.cat
- Phone: +34686203964
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.