Development of PI-ML Algorithm for Prediction of the Real-time Risk for Developing Pre-diabetes

NCT06195566 | Completed

• 1 other identifier: 101095672
• Study Type: observational
• Target: 77
• Locations: 1 country
• Sites: 1

Brief Summary

In this prospective, non-randomized, monocentric study, data will be collected from otherwise healthy individuals with overweight/obese grade I to increase data availability in the pre-diabetes field (impaired glucose intolerance), and to validate the outputs of an algorithm for the "physics-informed machine learning (PIML)" designed to estimate the real-time risk of prediabetes. Each participant will take part in the study for 4 months, including 3 onsite visits. During the screening visit, participants' eligibility will be determined by checking the inclusion and exclusion criteria after detailed information and obtaining informed consent by the investigator. Blood will be withdrawn for exclusion of existing prediabetes/diabetes at the fasted state. For women in reproductive age, a urinary pregnancy test will be performed. After getting the results of blood tests (glucose and HbA1c), participants will be asked to participate in study. On the visit 1, eligible participants will arrive at the study centre in a fasting state. Blood samples will be collected and participants will get vials and instructions for collection of stool and urine samples. Anthropometric data, lifestyle habit (cigarette, alcohol consumption) and family history will be collected. A 6-minute walking test to determine VO2 max will then be performed. Lap counts and time will be manually recorded using a sports watch. The Polar H10 heart rate monitor chest strap will be used to record heart rate (HR) throughout the test. To measure resting HR and heart rate recovery (HRR), participants will be asked to sit still for 5 minutes before the walking test and for 2 minutes after the test. Participants will receive a blinded Abbott Libre Pro glucose sensor, which they will wear for the next 14-days. Further, participants will be provided with a Fitbit Charge 5 health and fitness wristband. For validation purposes some part of study participants will be kindly asked to test newly develop wrist-worn device (EDIBit). With the help of 24-hour food recall, study subjects will be trained by medical staff on how to correctly enter their food intake in the Study app for completion of digital 3-day food diaries. They will be asked to fill in the diaries for 3 days after study visit1 and 3 days before study visit2. They will also receive a food frequency questionnaire during visit1. The second study visit will run nearly identical to study visit1 (except for food frequency questionnaire which will be omitted). During this visit, participants will receive information sheets on physical activity and dietary recommendations. The third and last visit will run nearly identically to the study visit2, except that no new glucose sensor will be inserted and also stool samples will not be collected.

Conditions

Prediabetic State; Body Weight; Overweight or Obesity; Life Style, Healthy

Keywords

overweight; obesity; prediabetic state; prediction; artificial intelligence

Outcome Measures

Primary Outcomes (1)

• Validation of the Mission T2D (MT2D) algorithm outputs, that predicts the real time risk for developing pre-diabetes.

  Data collections has three main purposes input data for the in-silico MT2D model (gender, weight, height, number of sessions of physical activity, duration of the bout of physical activity, intensity in terms of %VO2max, 3 meals per day (specified macronutrients). Validation of the MT2D outputs include inflammation markers, metabolic outcomes. The third data for training/validation of the physics-informed machine learning (PIML) algorithm: demographic data; health-related data; lifestyle data (e.g., food consumption data and physical activity data); continuous ingestion through wearable sensors (Continuous Glucose Monitoring (CGM and tracker of physical activity e.g., Fitbit Charge 5, EDIBit.)

  The study will run for 15 months. During this period, 75 individuals will be followed for 4 months, including screening visit and three onsite visits, if participants meet the predetermined inclusion criteria. Time frame between visits are 65 days (± 10

Eligibility Criteria

• Age: 18 Years - 65 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Study population will be selected mainly in primary care clinic - endocrinologists, general practitioners will be informed about the study. Informative materials about the study will be prepared, which will contain the contact information (e-mail, phone number) using which the potential participant will be able to apply for the study. In addition, it is possible to invite participants to the research using public media (TV, radio, internet), social networks and the homepage of the University of Latvia. Initially, potential participants will be informed about the purpose, the progress of the study by phone or e-mail. If potential individuals willing to participate, more detailed information and signing of informed consent forms will take place during the screening visit.

You may qualify if:

• Healthy adult volunteers (age ≥ 18 years old);
• Overweight (BMI 25 - 29.9 kg/m2) and obese grade I individuals (with BMI 30 - 34.9 kg/m2);
• Written consent of the participant after being informed;
• Ownership of a smartphone running Android or iOS.

You may not qualify if:

• Non-compliance;
• Ongoing treatment with immunosuppressive and/or anti-inflammatory medications (NSAIDs, glucocorticoids, chemotherapy, biologicals);
• Ongoing treatment with glucose lowering drugs, except if anti-diabetic medication has not been stopped - for metformin one month, for GLP-1 RA, tirzepatide - two months prior enrolment;
• Presence of autoimmune and/or inflammatory disease (autoimmune thyroid disease, psoriasis, inflammatory bowel disease);
• Skin conditions hindering application of continuous glucose monitoring systems;
• Diabetes or prediabetes as diagnosed by ADA/WHO criteria according to fasting glucose and/or HbA1c;
• High risk alcohol consumption - according to NIAAA - National Institute on Alcohol Abuse and Alcoholism (for men - more than 4 drinks on any day or more than 14 drinks per week; for women - more than 3 drinks on any day or more than 7 drinks per week);
• Factors otherwise limiting the participation in the study according to the judgement of the investigator;
• Pregnancy or intention to get pregnant during the study timeline.

Sponsors & Collaborators

• Jelizaveta Sokolovska: lead
• Spindox Labs: collaborator
• The National Research Council, Italy: collaborator
• The Institute of Electronics and Computer Sciences, Latvia: collaborator
• Euronet-Consulting: collaborator
• Scuola di Robotica: collaborator
• CheckHealth: collaborator
• The Italian Liver Foundation: collaborator
• Medical University of Graz: collaborator
• HK3 Lab S.R.L., Italy: collaborator

Study Sites (1)

University of Latvia, Faculty of Medicine

Riga, Latvia

Location

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Biospecimen

Retention: SAMPLES WITHOUT DNA

Serum, plasma and faecal samples will be stored at the temperature (-80°C) and access-controlled freezer for 10 years. Plasma and faecal samples will be shipped for further analysis to the project partner Italian Liver Foundation (FIF) in Basovizza, Trieste (Italy), but serum samples will be stored onsite at University of Latvia biorepository.

MeSH Terms

Conditions

Prediabetic State; Body Weight; Overweight; Obesity

Condition Hierarchy (Ancestors)

Diabetes Mellitus; Glucose Metabolism Disorders; Metabolic Diseases; Nutritional and Metabolic Diseases; Endocrine System Diseases; Signs and Symptoms; Pathological Conditions, Signs and Symptoms; Overnutrition; Nutrition Disorders

Study Officials

• Jelizaveta Sokolovska, Dr.med.

  University of Latvia, Faculty of Medicine

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR INVESTIGATOR
• PI Title: Leading researcher

Study Record Dates

• First Submitted: December 22, 2023
• First Posted: January 8, 2024
• Study Start: January 29, 2024
• Primary Completion: September 30, 2025
• Study Completion: September 30, 2025
• Last Updated: May 6, 2026

Record last verified: 2026-04

Data Sharing

• IPD Sharing: Will not share

Locations

LA (1)