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

Area of Science:

• Biomedical Engineering
• Artificial Intelligence in Healthcare
• Metabolic Diseases

Background:

• Digital twin (DT)-guided lifestyle interventions have shown promise in achieving type 2 diabetes (T2D) remission.
• The impact of DT technology on hypertension (HTN) in T2D patients remains largely uninvestigated.

Purpose of the Study:

• To evaluate the efficacy of DT-guided interventions versus standard of care (SC) in managing blood pressure (BP).
• To assess the effects on anti-hypertensive medication use, HTN remission rates, and microalbuminuria in individuals with T2D.

Main Methods:

• A secondary analysis was conducted on a randomized controlled trial involving 319 participants with T2D in India.
• Participants were randomized to either an artificial intelligence-enabled DT group (N=233) or an SC group (N=86).
• Home Blood Pressure Monitoring guided anti-hypertensive medication adjustments, with subsequent comparisons of BP, medication use, HTN remission, and microalbuminuria.

Main Results:

• The DT group demonstrated significant reductions in both systolic (-7.6 vs -3.2 mm Hg) and diastolic (-4.3 vs -2.2 mm Hg) blood pressure compared to the SC group after one year.
• A higher proportion of the DT group (68.2%) remained off anti-hypertensive medications compared to the SC group (0%).
• The DT subgroup achieved significantly higher rates of normotension (40.9% vs 6.7%) and hypertension remission (50% vs 0%), along with improved normoalbuminuria rates (92.4% vs 83.1%) compared to the SC subgroup.

Conclusions:

• Artificial intelligence-enabled DT technology proves more effective than standard care for reducing BP and anti-hypertensive medication requirements in T2D patients.
• DT interventions significantly improve hypertension remission rates and normoalbuminuria in individuals with co-existing HTN and T2D.
• The findings support the use of AI-powered DTs as a precision treatment strategy for reversing diabetes and managing associated comorbidities.