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

Launched by JELIZAVETA SOKOLOVSKA · Jan 5, 2024

Keywords

ClinConnect Summary

This clinical trial is studying a new method called the "PI-ML Algorithm" to help predict the risk of developing prediabetes in individuals who are overweight or mildly obese. Prediabetes is a condition where blood sugar levels are higher than normal but not high enough to be diagnosed as diabetes. The trial aims to collect information from healthy adults aged 18 and older, specifically those with a body mass index (BMI) between 25 and 34.9. Participants will need to have a smartphone and will undergo a series of tests and health assessments over a four-month period, including three visits to the study center.

During the trial, participants will provide blood, urine, and stool samples, wear a glucose monitoring device for two weeks, and use a fitness tracker to monitor their activity. They will also receive guidance on healthy eating and exercise. To join the study, individuals should not be taking certain medications or have conditions like diabetes, autoimmune diseases, or significant alcohol consumption. This study is a great opportunity for those looking to contribute to health research and learn more about their own risk for prediabetes.

Gender

ALL

Eligibility criteria

• Inclusion Criteria:
• • 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.
• Exclusion Criteria:
• • 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.