Optimizing cardiovascular risk management in primary care with a personalized eCoach solution enriched by an AI-driven clinical prediction model: a study protocol of the CARRIER consortium (Preprint)
Authors: van Mierlo Rutger F R , Scheenstra Bart , Verbeek Joost G E , Bruninx Anke , Kalendralis Petros , Bermejo Inigo , Dekker Andre , van 't Hof Arnoud W J , Spreeuwenberg Marieke M D , Hochstenbach Laura M J 
Published: September 2024

BACKGROUND

Atherosclerotic cardiovascular disease poses a heavy burden on the population’s health and healthcare costs. Identifying apparently healthy individuals at-risk of developing cardiovascular diseases using clinical prediction models raises awareness, facilitates shared decision-making, and supports tailored management of disease prevention. In the CARRIER project, a personalized cardiovascular risk management (CVRM) eCoach approach is co-created, in which identified individuals receive education, guidance, and monitoring to prevent atherosclerotic cardiovascular disease through existing interventions. In this approach, an AI-driven clinical prediction model calculates the 10-year risk for atherosclerotic cardiovascular disease, which supports informed decision making.

OBJECTIVE

Our primary aim is to assess the effectiveness of our CVRM eCoach approach through a 10-year risk calculation of atherosclerotic cardiovascular disease, including risk factors contributing to this risk.

METHODS

This pretest-posttest interventional study provides the CVRM eCoach approach for six months to 100 apparently healthy individuals visiting their General Practitioner for primary CVRM. The CVRM eCoach approach is a multicomponent eHealth solution, including a clinical prediction under intervention model that not only calculates the 10-year risk of cardiovascular disease through conventional risk factors (smoking, blood pressure, lipid profile), and individual characteristics (age, gender, socioeconomic status, physical activity and diet), but also calculates how the risk changes after hypothetical lifestyle or medical interventions. The CVRM eCoach approach include features that encourage behavioral change. Most of these features include goal setting, decision cards to help decide on an intervention, intervention monitoring, remote communication, education, all accessible from one dashboard. A practice nurse consults the individuals after risk calculation with the clinical prediction model, and uses behavioral change features, such as the decision cards to support shared decision-making. Data are primarily collected via the eCoach, after which the 10-year risk for atherosclerotic cardiovascular disease and its components are analyzed using paired sample analyses.

RESULTS

Recruitment began in March 2024 and will continue until 100 participants have been recruited, which is expected in 2025.

CONCLUSIONS

We anticipate that our CVRM eCoach approach will be valuable in the primary prevention setting. During the crucial initial first months of habit formation, factors like education, regular check-ups via the eCoach, and clear risk communication could support individuals in sustaining their medical or lifestyle interventions. We hypothesize that there will be a slight to moderate reduction in the 10-year risk of atherosclerotic cardiovascular disease, which over time will lead to significant health improvements on a larger scale.

CLINICALTRIAL

https://onderzoekmetmensen.nl/nl/trial/56578; NL84584.096.23