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Implementation of Machine Learning and Hemodynamic Profiles Based Clinical Decision Support Systems for Personalized Guideline Accordant Antihypertensive Regimens in Primary Care: a Pragmatic Cluster Randomized Controlled Trial
Sponsor: China National Center for Cardiovascular Diseases
Summary
This trial is a prospective, multicenter, single-blind, three-arm parallel-group, cluster randomized controlled trial assessing the effectiveness and safety of two types of CDSS in primary care settings in China. Primary care sites are randomized to one of the intervention arms or the control arm (1:1:1 ratio) using computer-generated random numbers stratified by region and administrative categories of the primary healthcare institutions (including community health centers, community health stations, and township health centers). A total of 51 primary care sites are randomized to three groups, with 17 sites assigned to group A (use a CDSS based on clinical guidelines and machine learning), 17 sites to group B (use a CDSS based on guidelines, hemodynamic parameters and ML), and the remaining 17 sites to the control group.
Key Details
Gender
All
Age Range
35 Years - 79 Years
Study Type
INTERVENTIONAL
Enrollment
2160
Start Date
2025-05-26
Completion Date
2026-05-31
Last Updated
2026-02-12
Healthy Volunteers
No
Conditions
Interventions
Group A (clinical guideline+machine learning)
Group A (CG+ML): A Clinical Decision Support System (CDSS) with the algorithm that incorporates clinical guideline (CG) and machine learning (ML) approach.
Group B (clinical guideline+impedance cardiograph+machine learning)
Group B (CG+ICG+ML): A Clinical Decision Support System (CDSS) with the algorithm that incorporates clinical guideline (CG), hemodynamic parameters measured by impedance cardiograph (ICG), and machine learning (ML) approach.
Group C (usual care)
Control group, the physicians manage the hypertensive patients according to their knowledge and experiences.
Locations (1)
Fuwai Shenzhen Hospital, Chinese Academy of Medical Sciences
Shenzhen, Shenzhen, China