Actively Recruiting

Phase Not Applicable
Age: 6Years +
All Genders
NCT07150052

Efficacy and Safety of an Artificial Intelligence Tool for Carbohydrate Counting (Tiabete) in Children and Adults With Type 1 Diabetes Mellitus

Led by University of Sao Paulo · Updated on 2025-09-02

50

Participants Needed

1

Research Sites

82 weeks

Total Duration

On this page

AI-Summary

What this Trial Is About

IntroductionType 1 Diabetes Mellitus (T1DM) requires lifelong exogenous insulin therapy, along with self-management strategies, such as carbohydrate counting, to appropriately adjust insulin doses in response to meals. However, many patients face challenges in adhering consistently to carbohydrate counting, compromising glycemic control and increasing the risk of diabetes-related complications. Emerging technologies, such as artificial intelligence (AI), hold significant potential for optimizing disease management by enhancing the accuracy and efficiency of self-care practices. ObjectiveThe primary aim of this study is to evaluate the efficacy and safety of the AI-based tool Tia Bete, designed to assist patients with T1DM in carbohydrate counting and insulin dose adjustment. The tool provides real-time recommendations based on personalized insulin-to-carbohydrate ratios, insulin sensitivity factors, and individualized glycemic goals. MethodsThis is a prospective, longitudinal study involving 40 patients with T1DM, stratified into two cohorts: 20 children and adolescents (6-18 years) and 20 adults (\>18 years), recruited at the Hospital das Clínicas, University of São Paulo (HCFMUSP). Participants will be assessed before and after six months of using the Tia Bete tool. Glycemic control will be evaluated using parameters such as glycated hemoglobin (HbA1c), time in range, and the incidence of hypoglycemia and hyperglycemia. Quality of life and satisfaction with the tool will also be assessed. Overview of the AI Tool Launched in June 2024, Tia Bete is an AI-based digital solution designed to facilitate glycemic control and improve quality of life for patients with T1DM. By offering real-time assistance with carbohydrate counting and insulin dose recommendations, the tool aims to enhance patient autonomy while enabling flexible treatment adherence in collaboration with their multidisciplinary healthcare team. Results and ConclusionsPreliminary data indicate high engagement, with over 35,000 active users interacting with the platform at least four times per week. Initial findings suggest significant improvements in glycemic control, as well as increased confidence in carbohydrate counting and insulin dose adjustments. The dissemination of this project is crucial for advancing T1DM care, offering a scalable, accessible, and effective technological solution. Final results are expected by October 2025.

CONDITIONS

Official Title

Efficacy and Safety of an Artificial Intelligence Tool for Carbohydrate Counting (Tiabete) in Children and Adults With Type 1 Diabetes Mellitus

Who Can Participate

Age: 6Years +
All Genders

Eligibility Criteria

Eligible

You may qualify if you...

  • Diagnosis of type 1 diabetes mellitus
  • Children between 6 and 18 years old and their caregivers
  • Adults older than 18 years
  • Glycated hemoglobin (HbA1c) between 7.2% and 10.5% in the last 6 months
  • Currently using a basal-bolus insulin regimen
  • Able to participate in and understand the study guidelines for using the AI program
  • Agreeing to sign the free and informed consent form
  • Willing to perform regular monitoring at the diabetes outpatient clinic at HC-FMUSP
Not Eligible

You will not qualify if you...

  • Unable to understand the study instructions
  • Illiterate
  • Not attending the study visits as scheduled
  • Not using the AI tool via WhatsApp
  • Not providing consent to participate
  • Using the AI tool less than 3 days per week during the study period

AI-Screening

AI-Powered Screening

Complete this quick 3-step screening to check your eligibility

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Trial Site Locations

Total: 1 location

1

University of Sao Paulo

São Paulo, São Paulo, Brazil, 04026-001

Actively Recruiting

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Research Team

C

CAROLINE GB PASSONE, ENDOCRINOLOGIST

CONTACT

How is the study designed?

Study Type

INTERVENTIONAL

Masking

NONE

Allocation

NA

Model

SINGLE_GROUP

Primary Purpose

SUPPORTIVE_CARE

Number of Arms

1

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Efficacy and Safety of an Artificial Intelligence Tool for Carbohydrate Counting (Tiabete) in Children and Adults With Type 1 Diabetes Mellitus | DecenTrialz