Abstract P468: Correlation Among A1c Improvement, Weight Reduction, and Decreased ASCVD Risk in Participants Enrolled for Type 2 Diabetes Remission: Outcomes at 1 Year From an RCCT Using Whole-Body Digital Twin Technology

Abstract

Background and Aims: The effects of digital twin (DT) technology for remission of T2D on cardiovascular risk reduction is unknown. We evaluated the effectiveness of the DT to improve A1c and body weight and ASCVD risk, in patients enrolled to achieve remission of T2DM. DT platform uses AI and Internet of Things, to integrate multi-dimensional data to give precision nutrition and health recommendations via the mobile app and by coaches. Materials and Methods: Data from 208 participants who had been on DT for 1 year were analyzed. Remission was defined as A1C levels less than 6.5% without medication for over 3 months. Outcomes included the change in HbA1c, body weight and change in ASCVD risk scores. The DT uses a machine learning algorithm to integrate clinical and sensor data to predict personal glucose response. Patients were connected to continuous glucose monitoring (CGM) throughout the study and self-recorded dietary intake using the mobile app. Results: The study participants had a mean diabetes duration of 3.7±2.7 years and a mean age of 44±8.5 years. Based on the ADA criteria, at 1 year, 72.6% (n=151/208) continued to be under remission. The mean 10-year ASCVD risk (%) at baseline was 7.9 (±7.8, 95% CI 6.8 to 8.9) which reduced to 3.6 (±4, 95% CI 3.1 to 4.2) at 360 days, p<0.0001. A1c (%) at baseline was 8.9 (±1.8, 95% CI 8.7 to 9.2, minimum 5.5, maximum 16.2) which reduced to 6 (±0.6, 95% CI 5.9 to 6.1, minimum 4.7, maximum 9.2), p<0.0001. Body weight (kg) at baseline was 78 (±14.3, 95% CI 76.1 to 79.9) which reduced to 70.4 (±12.9, 95% CI 68.7 to 72.1), p<0.0001. There was a significant correlation between the reduction in A1c and ASCVD (Pearson r 0.41, 95% CI 0.31 to 0.5, p<0.0001). Similarly, there was a significant correlation between the reduction in body weight and ASCVD (Pearson r 0.25, 95% CI 0.12 to 0.3, <0.0001). At baseline, there were 49% of participants who had low risk score (<5%), 16% as borderline risk (5-7.5%), 27% as intermediate risk (7.5-19.9), 8% as high risk (>20%) that at 1 year shifted to 77% as low risk, 11% as borderline, 11% as intermediate risk and 1% as high-risk scores. Conclusion: The implementation of digital twin (DT) technology, utilizing AI and Internet of Things, demonstrated significant potential in T2DM management in participants enrolled to achieve remission. In our study with 208 participants, DT effectively reduced A1c levels, body weight, and ASCVD risk scores over 360 days. The correlations between reductions in A1c, body weight, and ASCVD underscore the potential of DT as a transformative tool in diabetes and cardiovascular risk management.