Characterization of Type 1 Diabetes Subgroup: An Artificial Intelligence Analysis of Clinical and Glucometric Features (T1DC)

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

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.

Study Overview

• Status: Recruiting
• Conditions: Type 1 Diabetes Mellitus

Detailed Description

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.

• Study Type: Observational
• Enrollment (Estimated): 800

Contacts and Locations

• Study Contact: Name: Eva Safont, MD; Phone Number: 5661 +34686203964; Email: esafont@santpau.cat
• Study Contact Backup: Name: Rosa M Corcoy, MD, PhD; Phone Number: 5661 +34686203964; Email: rcorcoy@santpau.cat

Study Locations

• Spain
  • Barcelona
    • Barcelona, Barcelona, Spain, 08025
      • Recruiting
      • Hospital de la Santa Creu i Sant Pau, Barcelona, Barcelona 08041
      • Contact: Rosa Corcoy, MD PhD; Phone Number: +34 935565661; Email: rcorcoy@santpau.cat
      • Contact: Eva Safont, MD; Phone Number: +34 935565661; Email: esafont@santpau.cat
      • Principal Investigator: Rosa Corcoy, MD PhD
      • Sub-Investigator: Eva Safont, MD
      • Sub-Investigator: Ana Chico, MD PhD
      • Sub-Investigator: Alex Mesa, MD PhD
      • Sub-Investigator: Helena Sardà, MD
      • Sub-Investigator: Lilian C Mendoza, MD PhD
      • Sub-Investigator: Natalia Mangas, RN
      • Sub-Investigator: Dídac Mauricio, MD PhD
      • Sub-Investigator: Santiago Martinez, MD
      • Sub-Investigator: Jose M Cubero, MD PhD
      • Sub-Investigator: Romina Miranda, PhD
      • Sub-Investigator: Bogdan Vlacho, PhD

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

• Sampling Method: Non-Probability Sample

Study Population

The study population consists of individuals with type 1 diabetes (T1D) cared for at the Endocrinology and Nutrition Department of Hospital de la Santa Creu i Sant Pau.

Description

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.

Study Plan

How is the study designed?

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort
People with type 1 diabetes mellitus; Individuals with type 1 diabetes mellitus (T1D) cared for at the Endocrinology and Nutrition Department of Hospital de la Santa Creu i Sant Pau.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Type 1 diabetes clusters	Differentiated groups of people with type 1 diabetes defined through the analysis of clinical, analytical, and glucometric variables.	Subgroups defined based on data from the year 2024.

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Cluster stability over time	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	2024 - 2027
Acute and chronic diabetes complications	Presence of acute complications (such as severe hypoglycemia) and chronic complications (such as retinopathy, nephropathy, and neuropathy) across the different clusters.	2024-2027
Glycemic control: mean glucose	Mean glucose reported in mg/dL	2024-2027
Glycemic control: GMI (glucose management indicator)	GMI (glucose management indicator) reported in percentage (%)	2024-2027
Glycemic control: CV (coefficient of variation)	CV (coefficient of variation) reported in percentage (%)	2024-2027
Glycemic control: time in range	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%	2024-2027
HbA1c	Lab or point-of-care HbA1c	2024-2027
Lipid profile	Laboratory mesured total cholesterol, triglycerids, LDL anb HDL	2024-2027
Creatinine	creatinine Laboratory measure. Units mg/dL	2024-2027
Estimated glomerular filtration rate	laboratory estimated glomerular filtration rate. Units mL/min/1.73 m2	2024-2027
Albuminuria	Albuminuria, laboratory measure. Units mg/g	2024-2027
Antihypertensive treatment	Use of Antihypertensive treatment and its relationship with the clusters.	2024-2027
Hypolipemiant treatment: use	Use of hypolipemiant medication (yes/no)	2024-2027
Hypolipemiant treatment amongst clusters	Association between use of hypolipemiant treatment and the clusters.	2024-2027
Insulin treatment: type	Type of insulin therapy: multiple daily injections, continuous subcutaneous insulin infusion systems, hybrid closed-loop systems	2024-2027
Insulin treatment: association with the clusters	Association with the type of insulin therapy and the clusters	2024-2027
Anthropometric variables: weight	Weight in kilograms and its relationship with the clusters. Weight and height will be combined to report BMI in kg/m^2.	2024-2027
Anthropometric variables: height	Height in centimeters and its relationship with the clusters. Weight and height will be combined to report BMI in kg/m^2.	2024-2027
Anthropometric variables: waist circumference	Waist circumference in centimeters and its relationship with the clusters.	2024-2027
Substance use: tobacco	Tobacco consumption and its relationship with the clusters. Tobacco use will be reported: active tobacco use, past tobacco use, never smoker, unknown.	2024-2027
Substance use: alcohol	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.	2024-2027
Age at diagnosis	Patient age at diabetes diagnosis and its relationship with the clusters.	2024-2027
Disease duration	Diabetes duration and its relationship with the clusters.	2024-2027
Pregnancy	Active pregnancy and its relationship with the clusters.	2024-2027
Parity status in women	Parity status in women and its relationship with the clusters.	2024-2027
Menstrual cycle phase	Menstrual cycle phase and its relationship with the clusters.	2024-2027
Reproductive stage in women	Reproductive stage in women and its relationship with the clusters. Reproductive stage will be reported as: Reproductive, Perimenopausal, Postmenopausal, Unknown	2024-2027
Patient-reported variables	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.	2024-2027
Patient-reported variables and its association with the clusters	Correlation between patient reported health-related quality of life and the association with the clusters.	2024-2027
Sociodemographic variables	Date of birth	2024-2027
Sociodemographic variables	Sex assigned at birth	2024-2027
Sociodemographic variables	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	2024-2027

Collaborators and Investigators

• Sponsor: Fundació Institut de Recerca de l'Hospital de la Santa Creu i Sant Pau
• Collaborators: Sociedad Española de Diabetes; Associació Catalana de Diabetis
• Investigators: Principal Investigator: Rosa M Corcoy, Fundació Institut de Recerca de l'Hospital de la Santa Creu i Sant Pau

Publications and helpful links

General Publications

• Diabetes Control and Complications Trial Research Group; Nathan DM, Genuth S, Lachin J, Cleary P, Crofford O, Davis M, Rand L, Siebert C. The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus. N Engl J Med. 1993 Sep 30;329(14):977-86. doi: 10.1056/NEJM199309303291401.
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• Goldstein A, Shahar Y, Weisman Raymond M, Peleg H, Ben-Chetrit E, Ben-Yehuda A, Shalom E, Goldstein C, Shiloh SS, Almoznino G. Multi-Dimensional Validation of the Integration of Syntactic and Semantic Distance Measures for Clustering Fibromyalgia Patients in the Rheumatic Monitor Big Data Study. Bioengineering (Basel). 2024 Jan 19;11(1):97. doi: 10.3390/bioengineering11010097.
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• Sammouda R, El-Zaart A. An Optimized Approach for Prostate Image Segmentation Using K-Means Clustering Algorithm with Elbow Method. Comput Intell Neurosci. 2021 Nov 15;2021:4553832. doi: 10.1155/2021/4553832. eCollection 2021.
• Vigers T, Chan CL, Snell-Bergeon J, Bjornstad P, Zeitler PS, Forlenza G, Pyle L. cgmanalysis: An R package for descriptive analysis of continuous glucose monitor data. PLoS One. 2019 Oct 11;14(10):e0216851. doi: 10.1371/journal.pone.0216851. eCollection 2019.
• Kovatchev B, Lobo B. Clinically Similar Clusters of Daily Continuous Glucose Monitoring Profiles: Tracking the Progression of Glycemic Control Over Time. Diabetes Technol Ther. 2023 Aug;25(8):519-528. doi: 10.1089/dia.2023.0117.
• Tobias DK, Merino J, Ahmad A, Aiken C, Benham JL, Bodhini D, Clark AL, Colclough K, Corcoy R, Cromer SJ, Duan D, Felton JL, Francis EC, Gillard P, Gingras V, Gaillard R, Haider E, Hughes A, Ikle JM, Jacobsen LM, Kahkoska AR, Kettunen JLT, Kreienkamp RJ, Lim LL, Mannisto JME, Massey R, Mclennan NM, Miller RG, Morieri ML, Most J, Naylor RN, Ozkan B, Patel KA, Pilla SJ, Prystupa K, Raghavan S, Rooney MR, Schon M, Semnani-Azad Z, Sevilla-Gonzalez M, Svalastoga P, Takele WW, Tam CH, Thuesen ACB, Tosur M, Wallace AS, Wang CC, Wong JJ, Yamamoto JM, Young K, Amouyal C, Andersen MK, Bonham MP, Chen M, Cheng F, Chikowore T, Chivers SC, Clemmensen C, Dabelea D, Dawed AY, Deutsch AJ, Dickens LT, DiMeglio LA, Dudenhoffer-Pfeifer M, Evans-Molina C, Fernandez-Balsells MM, Fitipaldi H, Fitzpatrick SL, Gitelman SE, Goodarzi MO, Grieger JA, Guasch-Ferre M, Habibi N, Hansen T, Huang C, Harris-Kawano A, Ismail HM, Hoag B, Johnson RK, Jones AG, Koivula RW, Leong A, Leung GKW, Libman IM, Liu K, Long SA, Lowe WL Jr, Morton RW, Motala AA, Onengut-Gumuscu S, Pankow JS, Pathirana M, Pazmino S, Perez D, Petrie JR, Powe CE, Quinteros A, Jain R, Ray D, Ried-Larsen M, Saeed Z, Santhakumar V, Kanbour S, Sarkar S, Monaco GSF, Scholtens DM, Selvin E, Sheu WH, Speake C, Stanislawski MA, Steenackers N, Steck AK, Stefan N, Stoy J, Taylor R, Tye SC, Ukke GG, Urazbayeva M, Van der Schueren B, Vatier C, Wentworth JM, Hannah W, White SL, Yu G, Zhang Y, Zhou SJ, Beltrand J, Polak M, Aukrust I, de Franco E, Flanagan SE, Maloney KA, McGovern A, Molnes J, Nakabuye M, Njolstad PR, Pomares-Millan H, Provenzano M, Saint-Martin C, Zhang C, Zhu Y, Auh S, de Souza R, Fawcett AJ, Gruber C, Mekonnen EG, Mixter E, Sherifali D, Eckel RH, Nolan JJ, Philipson LH, Brown RJ, Billings LK, Boyle K, Costacou T, Dennis JM, Florez JC, Gloyn AL, Gomez MF, Gottlieb PA, Greeley SAW, Griffin K, Hattersley AT, Hirsch IB, Hivert MF, Hood KK, Josefson JL, Kwak SH, Laffel LM, Lim SS, Loos RJF, Ma RCW, Mathieu C, Mathioudakis N, Meigs JB, Misra S, Mohan V, Murphy R, Oram R, Owen KR, Ozanne SE, Pearson ER, Perng W, Pollin TI, Pop-Busui R, Pratley RE, Redman LM, Redondo MJ, Reynolds RM, Semple RK, Sherr JL, Sims EK, Sweeting A, Tuomi T, Udler MS, Vesco KK, Vilsboll T, Wagner R, Rich SS, Franks PW. Second international consensus report on gaps and opportunities for the clinical translation of precision diabetes medicine. Nat Med. 2023 Oct;29(10):2438-2457. doi: 10.1038/s41591-023-02502-5. Epub 2023 Oct 5.
• Somolinos-Simon FJ, Garcia-Saez G, Tapia-Galisteo J, Corcoy R, Elena Hernando M. Cluster analysis of adult individuals with type 1 diabetes: Treatment pathways and complications over a five-year follow-up period. Diabetes Res Clin Pract. 2024 Sep;215:111803. doi: 10.1016/j.diabres.2024.111803. Epub 2024 Jul 30.
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Study record dates

Study Major Dates

• Study Start (Actual): November 4, 2025
• Primary Completion (Estimated): June 1, 2028
• Study Completion (Estimated): December 1, 2028

Study Registration Dates

• First Submitted: November 14, 2025
• First Submitted That Met QC Criteria: March 6, 2026
• First Posted (Actual): March 10, 2026

Study Record Updates

• Last Update Posted (Actual): March 10, 2026
• Last Update Submitted That Met QC Criteria: March 6, 2026
• Last Verified: November 1, 2025

More Information

Terms related to this study

• Keywords: Artificial intelligence; Type 1 diabetes mellitus; Clusters; glucometry
• Additional Relevant MeSH Terms: Endocrine System Diseases; Metabolic Diseases; Autoimmune Diseases; Immune System Diseases; Glucose Metabolism Disorders; Diabetes Mellitus; Nutritional and Metabolic Diseases; Diabetes Mellitus, Type 1
• Other Study ID Numbers: IIBSP-GIA-2024-115

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: UNDECIDED
• IPD Plan Description: We may publish anonymized patient data on the Universitat Autònoma de Barcelona website, ensuring that no information allowing re-identification is included, such as name, ID number, telephone number, postal or email address, social security number, exact date of birth, exact place of birth, or occupation.

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No