Digital Twin in Managing Hypertension Among People With Type 2 Diabetes: 1-Year Randomized Controlled Trial

Background: Digital twin (DT)-guided lifestyle changes induce type 2 diabetes (T2D) remission but effects on hypertension (HTN) in this population are unknown.

Objectives: 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.

Methods: 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.

Results: 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; P < 0.007) and diastolic blood pressure (-4.3 vs -2.2 mm Hg; P = 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%; P = 0.0009) and HTN remission (50% vs 0%; P < 0.0001) than SC subgroup. DT group had a higher rate of achieving normoalbuminuria (92.4% vs 83.1%; P = 0.018) at 1 year compared with SC group.

Conclusions: 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).