Key points are not available for this paper at this time.
Utilizing the Digital Twin (DT) technology, which integrates Artificial Intelligence (AI) and the Internet of Things (IoT), this study aimed to improve extra glycemic parameters in patients with Type 2 Diabetes (T2D). The DT platform processed multidimensional data to provide individualized nutrition and health recommendations via a mobile application. Analysis was conducted on data from 218 of the 233 participants who completed a 18 months intervention with DT, showing marked improvements. The mean age and duration of diabetes were 44 years (±8.6) and 3.7 years (±2.7), respectively. Significant changes (p0.0001) were observed from baseline to 18 months in key non-glycemic parameters: Systolic BP (from 127.4 mmHg ± 11.5 to 121 mmHg ± 12.8), Diastolic BP (from 84.7 ± 7.2 to 81.6 ± 10), hs-CRP (from 2.9 mg/dl ± 4.5 to 2.2 mg/dl ± 3.1), TG/HDL ratio (from 7.9 ± 16.8 to 4.6 ± 3.6), NAFLD Fibrosis Score (from -2.3 ± 1.1 to -2.9 ± 1), and NAFLD Liver Fat Score (from 1.2 ± 2 to -0.6 ± 1.7). The integration of AI and IoT in the DT platform significantly enhanced extra glycemic parameters in T2D patients over eighteen months, indicating its transformative potential beyond traditional glycemic management. Disclosure S. Joshi: None. M. Dharmalingam: None. A. Vadavi: None. A. Keshavamurthy: None. S. Bhonsley: None. M. Thajudeen: None. A. Sha: None. P. Shamanna: None.
Joshi et al. (Fri,) studied this question.