Type 1 DiabetesTiabeteNCT07150052
Efficacy and Safety of an Artificial Intelligence Tool for Carbohydrate Counting (Tiabete) in Children and Adults With Type 1 Diabetes Mellitus
A study testing Artifical intelligence in whatsapp in people with Type 1 Diabetes, run by University of Sao Paulo at 1 site in Brazil.
Trial summary
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. Read more about this study
- Who is it for?
- Ages 6 years and older
- Conditions the study is for
- Type 1 Diabetes
- What is being tested?
- Artifical intelligence in whatsapp
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 50 participants
- Where
- 1 siteBrazil
- Study dates
- 1 May 2025to Dec 2026
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 6 years and older
- All sexes
- No healthy volunteers
- Child, Adult, Older adult
Who may be able to join
- Diagnosis of type 1 diabetes mellitus
- children between 6 and 18 years old and their caregivers; and adults > 18 years old.
- Glycated Hb between 7.2-10.5% in the last 6 months. Being on a basal-bolus regimen Participating in and understanding the guidelines on how to use the program to be tested in this study Agreeing to the free and informed consent form. Performing periodic monitoring at the DM outpatient clinic at HC-FMUSP
Who cannot join
- Not understanding the instructions.
- Being illiterate
- Not attending the visits proposed by the study
- Not using the tool via WhatsApp.
- Not accepting consent.
- Interacting with the tool less than 3 days a week during the study period.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Brazil1 site, 1 recruiting
- Recruiting
University of Sao Paulo
São Paulo, São Paulo, 04026-001
CAROLINE PASSONE, +5511981467909, carol.passone@gmail.com
carol.passone@gmail.com
About this study
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
- Type 1 Diabetes
- Being tested
- Artifical intelligence in whatsapp
- Keywords
- type 1 diabetes, technology, artificial intelligence, carb counting
- Medical subject headings
- Diabetes Mellitus, Type 1
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Artifical intelligence in whatsappOther
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.
| Study group | Role | What they receive |
|---|---|---|
| Use of Tiabete - AI tool | Experimental | Patients will use the AI tool and we will compare before and after the intervention Receives: Other: Artifical intelligence in whatsapp |
What is being measured
The primary outcome is the main question the study is designed to answer.
Glycated hemoglobin (HbA1c)
Participants will be assessed before and after six months of using the Tia Bete tool. Glycemic control will be evaluated using :
- Hb1 Ac ( as a percentage of total hemoglobin- real value)
Measured: 6 months
- time in range ( percentage) - hypoglycemia (mean daily percentage of hypo- glycemia less than 70 mg/dl) - hyperglycemia(mean daily percentage of hyper- glycemia above than 180mg/dl)
Participants will be assessed before and after six months of using the Tia Bete tool. Glycemic control will be evaluated using :
- time in range ( percentage)
- hypoglycemia (mean daily percentage of hypo- glycemia less than 70 mg/dl)
- hyperglycemia(mean daily percentage of hyper- glycemia above than 180mg/dl)
Measured: 6 months
Secondary outcomes (2)
Quality of life
Diabetes-specific health-related quality of life will be assessed with validated, age-appropriate instruments: the Pediatric Quality of Life Inventory (PedsQL) 3.0 Diabetes Module for children/adolescents (<18 years) and the Brazilian abridged version of the Diabetes Quality of Life Measure (DQOL-Brazil-8) for adults (≥18 years). Scores for both instruments range from 0 (lowest possible quality of life) to 100 (highest); higher scores indicate better quality of life.
Measured: 6 months
Satisfaction with the tool
Participant satisfaction with the intervention will be assessed using the Satisfaction Form with the Tia Bete Tool. The instrument yields a total score from 4 (minimum possible satisfaction) to 30 (maximum possible satisfaction); higher scores indicate greater satisfaction with the tool.
Measured: 6 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted2 Sep 2025
- Study start1 May 2025
- Primary completionOct 2025 (estimated)
- Study completionDec 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (2)Papers the sponsor has linked to this study.
- Other trials for Type 1 DiabetesStudies of the same condition, open and under way.
- More trials run by University of Sao PauloThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Supportive care
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Enrolment
- 50 participants (estimated)
Sponsor and investigators
- Lead sponsor
- University of Sao Paulo
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Caroline de Gouveia Buff Passone, University of Sao Paulo
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07150052
- Sponsor's protocol ID
- USaoPauloTiabete
- Acronym
- Tiabete
- Status last verified
- Jun 2025
- First submitted
- 28 Jun 2025
- Last updated
- 2 Sep 2025
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Cengiz E, Danne T, Ahmad T, Ayyavoo A, Beran D, Ehtisham S, Fairchild J, Jarosz-Chobot P, Ng SM, Paterson M, Codner E. ISPAD Clinical Practice Consensus Guidelines 2022: Insulin treatment in children and adolescents with diabetes. Pediatr Diabetes. 2022 Dec;23(8):1277-1296. doi: 10.1111/pedi.13442. No abstract available.
PubMed 36537533Annan SF, Higgins LA, Jelleryd E, Hannon T, Rose S, Salis S, Baptista J, Chinchilla P, Marcovecchio ML. ISPAD Clinical Practice Consensus Guidelines 2022: Nutritional management in children and adolescents with diabetes. Pediatr Diabetes. 2022 Dec;23(8):1297-1321. doi: 10.1111/pedi.13429. Epub 2022 Dec 5. No abstract available.
PubMed 36468223
Study at a glance
From the registry record, last updated by the sponsor on 2 Sep 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Efficacy and Safety of an Artificial Intelligence Tool for Carbohydrate Counting (Tiabete) in Children and Adults With Type 1 Diabetes Mellitus
- ClinicalTrials.gov ID
- NCT07150052
- Acronym / sponsor ID
- Tiabete / USaoPauloTiabete
- Conditions
- Type 1 Diabetes
- Keywords
- type 1 diabetes, technology, artificial intelligence, carb counting
- Study type
- Interventional
- Recruitment status
- Recruiting
- Enrolment
- 50 participants (estimated)
- Lead sponsor
- University of Sao PauloUniversity, hospital or other
- Study start
- 1 May 2025 (actual)
- Primary completion
- Oct 2025 (estimated)
- Study completion
- Dec 2026 (estimated)
- First posted
- 2 Sep 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Study design
- Primary purpose
- Supportive care
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Use of Tiabete - AI tool | Experimental | Other: Artifical intelligence in whatsappPatients will use the AI tool and we will compare before and after the intervention |
Who may qualify
- Ages
- 6 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult, Older adult
Key inclusion criteria (3 listed)
- Diagnosis of type 1 diabetes mellitus
- children between 6 and 18 years old and their caregivers; and adults > 18 years old.
- Glycated Hb between 7.2-10.5% in the last 6 months. Being on a basal-bolus regimen Participating in and understanding the guidelines on how to use the program to be tested in this study Agreeing to the free and informed consent form. Performing periodic monitoring at the DM outpatient clinic at HC-FMUSP
Key exclusion criteria (6 listed)
- Not understanding the instructions.
- Being illiterate
- Not attending the visits proposed by the study
- Not using the tool via WhatsApp.
- Not accepting consent.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Artifical intelligence in whatsappAI-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. | Other | Use of Tiabete - AI tool |
Primary outcome
Glycated hemoglobin (HbA1c)
Time frame: 6 months
Participants will be assessed before and after six months of using the Tia Bete tool. Glycemic control will be evaluated using : - Hb1 Ac ( as a percentage of total hemoglobin- real value)
- time in range ( percentage) - hypoglycemia (mean daily percentage of hypo- glycemia less than 70 mg/dl) - hyperglycemia(mean daily percentage of hyper- glycemia above than 180mg/dl)
Time frame: 6 months
Participants will be assessed before and after six months of using the Tia Bete tool. Glycemic control will be evaluated using : * time in range ( percentage) * hypoglycemia (mean daily percentage of hypo- glycemia less than 70 mg/dl) * hyperglycemia(mean daily percentage of hyper- glycemia above than 180mg/dl)
2 secondary outcomes
Quality of life
Time frame: 6 months
Satisfaction with the tool
Time frame: 6 months
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 2 Sep 2025.
- Background: PubMed 36537533Cengiz E, Danne T, Ahmad T, Ayyavoo A, Beran D, Ehtisham S, Fairchild J, Jarosz-Chobot P, Ng SM, Paterson M, Codner E. ISPAD Clinical Practice Consensus Guidelines 2022: Insulin treatment in children and adolescents with diabetes. Pediatr Diabetes. 2022 Dec;23(8):1277-1296. doi: 10.1111/pedi.13442. No abstract available.
- Background: PubMed 36468223Annan SF, Higgins LA, Jelleryd E, Hannon T, Rose S, Salis S, Baptista J, Chinchilla P, Marcovecchio ML. ISPAD Clinical Practice Consensus Guidelines 2022: Nutritional management in children and adolescents with diabetes. Pediatr Diabetes. 2022 Dec;23(8):1297-1321. doi: 10.1111/pedi.13429. Epub 2022 Dec 5. No abstract available.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Artifical intelligence in whatsapp in people with Type 1 Diabetes, run by University of Sao Paulo at 1 site in Brazil.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 6 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 2 Sep 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Brazil. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact CAROLINE GB PASSONE, ENDOCRINOLOGIST (+5511981467909, carol.passone@gmail.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Glycated hemoglobin (HbA1c) (time frame: 6 months). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT07150052, which also lists 2 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 2 Sep 2025; AzTrials last refreshed its copy on 7 Nov 2026.