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Conference abstracts Conference abstracts
Jan 2024 | Poster presentation | By Dr. Manthan Mehta, Dr. Vineet Nair, Tirtha Pani, Dr Arbinder Kumar Singal

Predicting Glycemic Response to a Digital Lifestyle Intervention for Adults with Type 2 Diabetes using Artificial Intelligence based data modeling

A predictive model was developed to estimate HbA1c reduction after a 3-month digital lifestyle program for adults with type 2 diabetes in India. Analysis of data from 267 participants revealed significant associations between baseline HbA1c, body mass index, triglyceride-glucose (TyG) index , and younger age with HbA1c reductions. The final model demonstrated a reasonable predictive capability (R²=0.72), offering a formula to estimate HbA1c reduction based on baseline parameters. This model, leveraging readily available clinical variables, enables personalized targets and optimal intervention selection for diabetes management, potentially improving outcomes in T2D care.

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