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NCT Number: NCT07461805

Characterization of Type 1 Diabetes Subgroup: An Artificial Intelligence Analysis of Clinical and Glucometric Features

The goal of this observational study is to characterize different subgroups among patients with type 1 diabetes. The main research question is:

Are there distinct subtypes among people with type 1 diabetes?

Participants will be invited to take part in the study by allowing access to their health data. They will not be required to undergo any additional examinations, tests, visits, or interventions.

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Key information

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

Hospital de la Santa Creu i Sant Pau, Barcelona, Barcelona 08041

Barcelona, 08025, Spain

Location status: Recruiting

Location contact

Alex Mesa, MD PhD

SUB_INVESTIGATOR

Ana Chico, MD PhD

SUB_INVESTIGATOR

Bogdan Vlacho, PhD

SUB_INVESTIGATOR

Dídac Mauricio, MD PhD

SUB_INVESTIGATOR

Eva Safont, MD

CONTACT

[email protected]

+34 935565661

Eva Safont, MD

SUB_INVESTIGATOR

Helena Sardà, MD

SUB_INVESTIGATOR

Jose M Cubero, MD PhD

SUB_INVESTIGATOR

Lilian C Mendoza, MD PhD

SUB_INVESTIGATOR

Natalia Mangas, RN

SUB_INVESTIGATOR

Romina Miranda, PhD

SUB_INVESTIGATOR

Rosa Corcoy, MD PhD

CONTACT

[email protected]

+34 935565661

Rosa Corcoy, MD PhD

PRINCIPAL_INVESTIGATOR

Santiago Martinez, MD

SUB_INVESTIGATOR

About this study

Study Description

Main Objective The primary objective of this study is to characterize subgroups of individuals with type 1 diabetes (T1D) based on clinical and glucometric features using an artificial intelligence (AI) approach.

Secondary objectives Evaluate cluster stability over time (1, 2, and 3 years); assess cluster utility for predicting complications; analyze the contribution of different clinical variables to cluster characterization and its evolution over time; and model endpoints such as diabetes-related complications.

Study Design This is an ambispective observational study.

Disease Under Study Type 1 Diabetes Mellitus.

Methodology This ambispective observational study will use information extracted from participants' electronic medical records and glucometric data obtained from the corresponding monitoring platforms. The data will be analyzed using artificial intelligence techniques to identify patterns and potential subgroups within the type 1 diabetes population.

Study Population and Sample Size The study population includes individuals with type 1 diabetes (T1D) who are being followed at the Endocrinology and Nutrition Department of Hospital de la Santa Creu i Sant Pau. As this is an exploratory study, no formal sample size calculation is required. Approximately 800 patients are expected to be included.

Who can participate

Healthy volunteers accepted: No

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

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.

Treatment and study plan

Primary outcomes

  1. Type 1 diabetes clusters

    Time frame: Subgroups defined based on data from the year 2024.

    Differentiated groups of people with type 1 diabetes defined through the analysis of clinical, analytical, and glucometric variables.

Secondary outcomes

  1. Cluster stability over time

    Time frame: 2024 - 2027

    Cluster stability over time determined using the Jaccard index as a reliability criterion: persistence of clusters over 1, 2, and 3 years. The Jaccard index (JI) measures the degree of similarity between two sets, regardless of the type of elements. It takes values between 0 and 1, with the latter corresponding to complete equality between both sets

  2. Acute and chronic diabetes complications

    Time frame: 2024-2027

    Presence of acute complications (such as severe hypoglycemia) and chronic complications (such as retinopathy, nephropathy, and neuropathy) across the different clusters.

  3. Glycemic control: mean glucose

    Time frame: 2024-2027

    Mean glucose reported in mg/dL

  4. Glycemic control: GMI (glucose management indicator)

    Time frame: 2024-2027

    GMI (glucose management indicator) reported in percentage (%)

  5. Glycemic control: CV (coefficient of variation)

    Time frame: 2024-2027

    CV (coefficient of variation) reported in percentage (%)

  6. Glycemic control: time in range

    Time frame: 2024-2027

    Time in range expressed as percentage:

    • % of time in glucose range 70-180 mg/dl (TIR) >70%
    • % of time in glucose range 70-140 mg/dl (TTIR) >70%
    • % of time <70 mg/dl (TBR1) <4%
    • % of time <54 mg/dl (TBR2) <1%
    • % of time >180 mg/dl (TAR1) <25%
    • % of time >250 mg/dl (TAR2) <5%
  7. HbA1c

    Time frame: 2024-2027

    Lab or point-of-care HbA1c

  8. Lipid profile

    Time frame: 2024-2027

    Laboratory mesured total cholesterol, triglycerids, LDL anb HDL

  9. Creatinine

    Time frame: 2024-2027

    creatinine Laboratory measure. Units mg/dL

  10. Estimated glomerular filtration rate

    Time frame: 2024-2027

    laboratory estimated glomerular filtration rate. Units mL/min/1.73 m2

  11. Albuminuria

    Time frame: 2024-2027

    Albuminuria, laboratory measure. Units mg/g

  12. Antihypertensive treatment

    Time frame: 2024-2027

    Use of Antihypertensive treatment and its relationship with the clusters.

  13. Hypolipemiant treatment: use

    Time frame: 2024-2027

    Use of hypolipemiant medication (yes/no)

  14. Hypolipemiant treatment amongst clusters

    Time frame: 2024-2027

    Association between use of hypolipemiant treatment and the clusters.

  15. Insulin treatment: type

    Time frame: 2024-2027

    Type of insulin therapy: multiple daily injections, continuous subcutaneous insulin infusion systems, hybrid closed-loop systems

  16. Insulin treatment: association with the clusters

    Time frame: 2024-2027

    Association with the type of insulin therapy and the clusters

  17. Anthropometric variables: weight

    Time frame: 2024-2027

    Weight in kilograms and its relationship with the clusters. Weight and height will be combined to report BMI in kg/m^2.

  18. Anthropometric variables: height

    Time frame: 2024-2027

    Height in centimeters and its relationship with the clusters. Weight and height will be combined to report BMI in kg/m^2.

  19. Anthropometric variables: waist circumference

    Time frame: 2024-2027

    Waist circumference in centimeters and its relationship with the clusters.

  20. Substance use: tobacco

    Time frame: 2024-2027

    Tobacco consumption and its relationship with the clusters. Tobacco use will be reported: active tobacco use, past tobacco use, never smoker, unknown.

  21. Substance use: alcohol

    Time frame: 2024-2027

    Acohol consumption and its relationship with the clusters. Alcohol consumption will be reported as: Low risk consumption, Risk consumption (>10 grams of alcohol in women, >20g of alcohol in men), known active alcohol disorder, Passed alcohol disorder, Unknown.

  22. Age at diagnosis

    Time frame: 2024-2027

    Patient age at diabetes diagnosis and its relationship with the clusters.

  23. Disease duration

    Time frame: 2024-2027

    Diabetes duration and its relationship with the clusters.

  24. Pregnancy

    Time frame: 2024-2027

    Active pregnancy and its relationship with the clusters.

  25. Parity status in women

    Time frame: 2024-2027

    Parity status in women and its relationship with the clusters.

  26. Menstrual cycle phase

    Time frame: 2024-2027

    Menstrual cycle phase and its relationship with the clusters.

  27. Reproductive stage in women

    Time frame: 2024-2027

    Reproductive stage in women and its relationship with the clusters. Reproductive stage will be reported as: Reproductive, Perimenopausal, Postmenopausal, Unknown

  28. Patient-reported variables

    Time frame: 2024-2027

    Patient-reported health-related quality of life will be assessed using a validated questionnaire for patients with type 1 diabetes. The Spanish version of the Diabetes Quality of Life questionnaire (EsDQOL) will be used. The score obtained from the questionnaire ranges from 0 to 100, where 0 represents the lowest possible quality of life and 100 the highest possible.

  29. Patient-reported variables and its association with the clusters

    Time frame: 2024-2027

    Correlation between patient reported health-related quality of life and the association with the clusters.

  30. Sociodemographic variables

    Time frame: 2024-2027

    Date of birth

  31. Sociodemographic variables

    Time frame: 2024-2027

    Sex assigned at birth

  32. Sociodemographic variables

    Time frame: 2024-2027

    Race/ethnic background reported as: White, Mediterranean or Hispanic, African or Caribbean, South Asian (Indian, Pakistani, Bangladeshi, or other Asian), East or Southeast Asian (Chinese, Japanese, or Southeast Asian), Arab or North African (including Egyptian), Unknown

Study contacts

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

Eva Safont, MD

CONTACT

[email protected]

+34686203964 ext. 5661

Rosa M Corcoy, MD, PhD

CONTACT

[email protected]

+34686203964 ext. 5661

Sponsors and collaborators

Lead sponsor

Fundació Institut de Recerca de l'Hospital de la Santa Creu i Sant Pau

Other

Collaborators

  • Associació Catalana de Diabetis
  • Sociedad Española de Diabetes

Registry information

Official study title

Caracterización de Subgrupos de Personas Con Diabetes Tipo 1: análisis de características clínicas y glucométricas Utilizando Una aproximación de Inteligencia Artificial

Acronym: T1DC

Important dates

Study start
2025
Primary completion
2028
Study completion
2028
First posted
Mar 10, 2026
Registry last updated
Mar 10, 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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