Shamanna Paramesh, Joshi Shashank, Dharmalingam Mala, Vadavi Arun, Keshavamurthy Ashok, Shah Lisa, Samajdar Shambo Samrat, Mechanick Jeffrey I
Department of Diabetes, Bangalore Diabetes Centre, Bangalore, Karnataka, India.
Department of Diabetology and Endocrinology, Lilavati Hospital and Research Center, Mumbai, India.
JACC Adv. 2024 Aug 14;3(9):101172. doi: 10.1016/j.jacadv.2024.101172. eCollection 2024 Sep.
Digital twin (DT)-guided lifestyle changes induce type 2 diabetes (T2D) remission but effects on hypertension (HTN) in this population are unknown.
The purpose of this study was to assess effects of DT vs standard of care (SC) on blood pressure (BP), anti-HTN medication, HTN remission, and microalbuminuria in participants with T2D.
This is a secondary analysis of a randomized controlled trial in India of 319 participants with T2D. Participants were randomized to DT group (N = 233), which used artificial intelligence-enabled DT technology, or SC group (N = 86). A Home Blood Pressure Monitoring system guided anti-HTN medication adjustments. BP, anti-HTN medications, HTN remission rates, and microalbuminuria were compared between groups.
Among the 319 participants, 44 in DT and 15 in SC group were on anti-HTN medications, totaling 59 (18.4%) participants. DT group achieved significant reductions in systolic blood pressure (-7.6 vs -3.2 mm Hg; < 0.007) and diastolic blood pressure (-4.3 vs -2.2 mm Hg; = 0.046) after 1 year compared with SC group. 68.2% of DT group remained off anti-HTN medications compared to none in SC group. Among participants with HTN, DT subgroup achieved higher rates of normotension (40.9% vs 6.7%; = 0.0009) and HTN remission (50% vs 0%; < 0.0001) than SC subgroup. DT group had a higher rate of achieving normoalbuminuria (92.4% vs 83.1%; = 0.018) at 1 year compared with SC group.
Artificial intelligence -enabled DT technology is more effective than SC in reducing BP and anti-HTN medications and inducing HTN remission and normoalbuminuria in participants with HTN and T2D. (A Novel WholeBody Digital Twin Enabled Precision Treatment for Reversing Diabetes; CTRI/2020/08/027072).
数字孪生（DT）引导的生活方式改变可促使2型糖尿病（T2D）缓解，但该人群中对高血压（HTN）的影响尚不清楚。
本研究旨在评估DT与标准治疗（SC）对T2D参与者的血压（BP）、抗高血压药物、HTN缓解及微量白蛋白尿的影响。
这是一项对印度319名T2D参与者进行的随机对照试验的二次分析。参与者被随机分为DT组（N = 233），使用人工智能驱动的DT技术，或SC组（N = 86）。家庭血压监测系统指导抗高血压药物调整。比较两组之间的BP、抗高血压药物、HTN缓解率和微量白蛋白尿。
在319名参与者中，DT组44人、SC组15人服用抗高血压药物，共59人（18.4%）。与SC组相比，DT组在1年后收缩压（-7.6 vs -3.2 mmHg；P < 0.007）和舒张压（-4.3 vs -2.2 mmHg；P = 0.046）显著降低。DT组68.2%的人停用了抗高血压药物，而SC组无人停用。在患有HTN的参与者中，DT亚组的血压正常率（40.9% vs 6.7%；P = 0.0009）和HTN缓解率（50% vs 0%；P < 0.0001）高于SC亚组。与SC组相比，DT组在1年时实现正常白蛋白尿的比例更高（92.4% vs 83.1%；P = 0.018）。
在降低患有HTN和T2D参与者的BP和抗高血压药物使用、诱导HTN缓解及正常白蛋白尿方面，人工智能驱动的DT技术比SC更有效。（一种新型的全身数字孪生实现逆转糖尿病的精准治疗；CTRI/2020/08/027072）
