The goal of this clinical trial is to evaluate the safety and efficacy of integrating predictive models into insulin therapy management via the user-centered glUCModel mobile app in People with Type 1 Diabetes Mellitus following Multiple Insulin Dosing therapy. Participants will be aged 18 to 65 years. The main questions it aims to answer are:
Does using the app improve glycaemic control, as measured by time in range? Does using the app reduce the number of episodes of hyperglycaemia and hypoglycaemia? Are the app's design and functionality adequate?
The study will comprise four phases:ses}):
* Screening phase: Informed consent, collection of sociodemographic and clinical data, and baseline Pittsburg, IFIS, and DTSQ questionnaires. * Run-in phase: 2 weeks of standard care with CGM. Data will be used to generate personalized predictive models in the intervention group. * Active treatment phase: Participants continue MDI therapy. The intervention group will additionally use the glUCModel mobile app. CGM data from the final 2 weeks will be analyzed. * Evaluation and analysis phase: Participants will complete the uMARS, Pittsburgh, and DTSQ questionnaires. Statistical analysis and correlations among outcomes will be processed.
HbA1c < 9%
Currently following an MDI Bolus-Basal therapy.
Wearing CGMs connected to a mobile phone.
Spanish language proficiency.
HbA1c < 9%.
Not wearing CGMs.
Non-Spanish language proficiency.
Less than one year since the time of diabetes diagnosis
Parallel
glUCModel app
Other interventionThe intervention consists on using glUCModel, an application designed to help people with diabetes. It features a suite of artificial intelligence tools and statistical techniques for capturing and managing key information that people with diabetes need to track, as well as for predicting glucose values to aid users in informed decision-making.
Time in Range (TIR)
Time in Range (TIR), defined as the percentage of time that interstitial glucose is between 70-180 mg/dL during the final 2 weeks of the intervention phase
Usability and adherence
Patient-reported outcomes on usability and adherence through uMARS. The usability of the app will be evaluated using the Spanish Version of the User Version of the Mobile Application Rating Scale (uMARS). This scale provides a comprehensive and objective measure of app usability and consists of 20 items. Each item is rated on a 5-point scale, ranging from 1 (inadequate) to 5 (excellent).
Frequency of Level 1 hypoglycemia
Frequency in minutes of Level 1 hypoglycemia (40 ≤ CGM glucose \< 55).
Frequency of Level 2 hypoglycemias
Frequency in minutes of Level 2 hypoglycemia (55 ≤ interstitial glucose ≤ 70)
Frequency of Level 1 hyperglycemias
Frequency in minutes of Level 1 hyperglycemia (180 ≤ CGM glucose ≤ 240).
Frequency of Level 2 hyperglycemias
Frequency in minutes of Level 2 hyperglycemia (241 ≤ interstitial glucose ≤ 400).
Sleep Quality before the intervention
We will evaluate Sleep Quality before and after the intervention. The Pittsburg Sleep Quality Index (PSQI) will be used. The Pittsburgh Sleep Quality Index (PSQI) is a self-rated questionnaire that assesses sleep quality and disturbances over a 1-month time interval. Nineteen individual items generate seven "component" scores: subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleeping medication, and daytime dysfunction. The sum of scores for these seven components yields one global score. The seven component scores are then summed to obtain a global PSQI score, which ranges from 0 to 21. Higher scores indicate poorer sleep quality, with a score greater than 5 suggesting significant sleep difficulties. https://www.sleep.pitt.edu/psqi
Sleep Quality after the intervention
We will evaluate Sleep Quality before and after the intervention. The Pittsburg Sleep Quality Index (PSQI) will be used. The Pittsburgh Sleep Quality Index (PSQI) is a self-rated questionnaire that assesses sleep quality and disturbances over a 1-month time interval. Nineteen individual items generate seven "component" scores: subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleeping medication, and daytime dysfunction. The sum of scores for these seven components yields one global score. The seven component scores are then summed to obtain a global PSQI score, which ranges from 0 to 21. Higher scores indicate poorer sleep quality, with a score greater than 5 suggesting significant sleep difficulties. https://www.sleep.pitt.edu/psqi
Click on the lead sponsor to view all of their trials.
Universidad Complutense de Madrid
Lead sponsor
Bioinspired Intelligence SL
Collaborator
Hospital de Toledo
Collaborator
