Using an AI-assisted tool to predict the behavior of children with type 1 diabetes for optimal use of sensor technology in Oman

Utilizing an AI-assisted tool to predict the behavior of children with type 1 diabetes for optimal use of sensor technology in Oman: a multi-phase translational research project Effectiveness of an AI-assisted assessment tool (the OMNIdiasense) to predict the behavior of adherence to CGMs use in children with T1DM in Oman: A pilot study

Status

Active, not recruiting

Phases

Unknown

Study type

Interventional

Source

ISRCTN

Registry ID

ISRCTN15827616

Enrollment

1500

Registered

2025-04-22

Start date

2025-12-01

Completion date

Unknown

Last updated

2026-07-13

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Improve the glycemic control and quality of life for children with type 1 diabetes Nutritional, Metabolic, Endocrine

Interventions

The phases/sub-studies associated with this project as background are: Sub-study 1: The characteristics of children with T1DM who received the CGMs in Oman (data from the Al Shifa system). All childr

Eligibility

Sex/Gender

All

Age

1 Years to 18 Years

Inclusion criteria

Inclusion criteria: All children with type 1 diabetes willing to participate

Exclusion criteria

Exclusion criteria: Refusal to participate

Design outcomes

Primary

Measure	Time frame
Effectiveness of the AI-assisted tool to predict the optimal use of CGMs in children with T1DM measured using 1. (OMNIdiasense) scores at baseline, 3, 6, and 12 months 2. Recordings from the CGMs at baseline, 3, 6, and 12 months 3. Motivational interviewing-guided behavior change consultations at baseline, 6 and 12 months	—

Secondary

Measure	Time frame
The following variables were assessed using data collected from a study questionnaire at baseline: 1. Demographic characteristics 2. Medical history of the disease 3. Family history of DM and type 4. History of co-morbidities The following variables were assessed using data collected from patient health information records at baseline, 6 and 12 months follow-up: 1. Drug/treatment history 2. Anthropometric measures: Weight, BMI 3. Blood pressure 4. Cholesterol testing, liver function tests (LFT), and renal function tests (RFT) 5. HbA1c	—

Measure

Time frame

The following variables were assessed using data collected from a study questionnaire at baseline: 1. Demographic characteristics 2. Medical history of the disease 3. Family history of DM and type 4. History of co-morbidities The following variables were assessed using data collected from patient health information records at baseline, 6 and 12 months follow-up: 1. Drug/treatment history 2. Anthropometric measures: Weight, BMI 3. Blood pressure 4. Cholesterol testing, liver function tests (LFT), and renal function tests (RFT) 5. HbA1c

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Countries

Oman

Contacts

Public ContactThamra Al Ghafri

t.alghafri@squ.edu.om+968-99376455

Outcome results

None listed

Source: ISRCTN (via WHO ICTRP) · Data processed: Jul 23, 2026