Prediction of metabolic subphenotypes of type 2 diabetes via continuous glucose monitoring ...
This study, part of the Precision Diets for Diabetes Prevention trial, recruited 36 participants aged 30-70 with BMI 23-40 kg/m². 32 completed metabolic tests, forming the main cohort. An independent validation cohort of 24 and a combined CGM cohort of 29 were also used. Metabolic tests included OGTT, at-home OGTT with CGM, IIGI, insulin suppression test, and plasma glucose measurement. Calculations assessed muscle insulin resistance, β-cell function, incretin effect, and hepatic insulin resistance. A machine-learning framework identified metabolic subphenotypes from OGTT glucose time series, validated on an independent cohort.
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This study, part of the Precision Diets for Diabetes Prevention trial, recruited 36 participants aged 30-70 with BMI 23-40 kg/m². 32 completed metabolic tests, forming the main cohort. An independent validation cohort of 24 and a combined CGM cohort of 29 were also used. Metabolic tests included OGTT, at-home OGTT with CGM, IIGI, insulin suppression test, and plasma glucose measurement. Calculations assessed muscle insulin resistance, β-cell function, incretin effect, and hepatic insulin resistance. A machine-learning framework identified metabolic subphenotypes from OGTT glucose time series, validated on an independent cohort.