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Updated: Sep 12, 2025
07:51
Hydra, a Computer-Based Platform for Aiding Clinicians in Cardiovascular Analysis and Diagnosis
Published on: September 26, 2018
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Optimizing Cardiovascular Risk Management in Primary Care Using a Personalized eCoach Solution Enhanced by an
Rutger van Mierlo1,2,3, Bart Scheenstra4, Joost Verbeek5
1Department of Cardiology, Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, The Netherlands.
JMIR Research Protocols
|August 8, 2025
Summary
This study introduces a cardiovascular risk management (CVRM) eCoach to help healthy individuals prevent atherosclerotic cardiovascular disease. The eCoach uses AI to predict risk and guide lifestyle changes, aiming for a moderate risk reduction.
Area of Science:
- Cardiovascular Health
- Preventive Medicine
- Digital Health Interventions
Background:
- Atherosclerotic cardiovascular disease (ASCVD) presents a significant public health challenge.
- Clinical prediction models can identify at-risk individuals for targeted prevention.
- The CARRIER project developed a personalized cardiovascular risk management (CVRM) eCoach to prevent ASCVD.
Purpose of the Study:
- To evaluate the effectiveness of the CVRM eCoach approach.
- To assess the 10-year risk calculation for ASCVD and contributing factors.
- To understand how the eCoach supports informed decision-making and behavior change.
Main Methods:
- A pretest-posttest interventional study involving 100 apparently healthy individuals.
- A 6-month intervention using the multicomponent eHealth CVRM eCoach.
- The eCoach calculates 10-year ASCVD risk, including hypothetical intervention impacts, and features goal setting, decision support, and remote monitoring.
- Data analyzed using paired-sample analyses.
Main Results:
- Participant recruitment is ongoing, aiming for 100 individuals by 2025.
- Data collection and analysis are in progress.
Conclusions:
- The CVRM eCoach is anticipated to be valuable for primary ASCVD prevention.
- Education, regular monitoring, and clear risk communication are expected to support sustained behavior change.
- A slight to moderate reduction in 10-year ASCVD risk is hypothesized, leading to long-term health improvements.
Keywords:
AI-drivenartificial intelligenceatherosclerosisatherosclerotic cardiovascular diseasecardiovascularcardiovascular diseasecardiovascular risk managementclinical prediction modelcostsdigital healthdisease managementeCoacheffectivenessmedical informaticsprediction modelprimary carerisk management
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