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 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
800
Hospital de la Santa Creu i Sant Pau, Barcelona, Barcelona 08041
Barcelona, Barcelona, Spain
RECRUITINGType 1 diabetes clusters
Differentiated groups of people with type 1 diabetes defined through the analysis of clinical, analytical, and glucometric variables.
Time frame: Subgroups defined based on data from the year 2024.
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
Time frame: 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.
Time frame: 2024-2027
Glycemic control: mean glucose
Mean glucose reported in mg/dL
Time frame: 2024-2027
Glycemic control: GMI (glucose management indicator)
GMI (glucose management indicator) reported in percentage (%)
Time frame: 2024-2027
Glycemic control: CV (coefficient of variation)
CV (coefficient of variation) reported in percentage (%)
Time frame: 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%
Time frame: 2024-2027
HbA1c
Lab or point-of-care HbA1c
Time frame: 2024-2027
Lipid profile
Laboratory mesured total cholesterol, triglycerids, LDL anb HDL
Time frame: 2024-2027
Creatinine
creatinine Laboratory measure. Units mg/dL
Time frame: 2024-2027
Estimated glomerular filtration rate
laboratory estimated glomerular filtration rate. Units mL/min/1.73 m2
Time frame: 2024-2027
Albuminuria
Albuminuria, laboratory measure. Units mg/g
Time frame: 2024-2027
Antihypertensive treatment
Use of Antihypertensive treatment and its relationship with the clusters.
Time frame: 2024-2027
Hypolipemiant treatment: use
Use of hypolipemiant medication (yes/no)
Time frame: 2024-2027
Hypolipemiant treatment amongst clusters
Association between use of hypolipemiant treatment and the clusters.
Time frame: 2024-2027
Insulin treatment: type
Type of insulin therapy: multiple daily injections, continuous subcutaneous insulin infusion systems, hybrid closed-loop systems
Time frame: 2024-2027
Insulin treatment: association with the clusters
Association with the type of insulin therapy and the clusters
Time frame: 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.
Time frame: 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.
Time frame: 2024-2027
Anthropometric variables: waist circumference
Waist circumference in centimeters and its relationship with the clusters.
Time frame: 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.
Time frame: 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.
Time frame: 2024-2027
Age at diagnosis
Patient age at diabetes diagnosis and its relationship with the clusters.
Time frame: 2024-2027
Disease duration
Diabetes duration and its relationship with the clusters.
Time frame: 2024-2027
Pregnancy
Active pregnancy and its relationship with the clusters.
Time frame: 2024-2027
Parity status in women
Parity status in women and its relationship with the clusters.
Time frame: 2024-2027
Menstrual cycle phase
Menstrual cycle phase and its relationship with the clusters.
Time frame: 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
Time frame: 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.
Time frame: 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.
Time frame: 2024-2027
Sociodemographic variables
Date of birth
Time frame: 2024-2027
Sociodemographic variables
Sex assigned at birth
Time frame: 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
Time frame: 2024-2027
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