Online calculator for estimating 10-year cardiovascular risk
Keywords:
Cardiometabolic Risk Factors, Internet Access, Dashboard Systems, Automation, User-Centered DesignAbstract
Introduction: Cardiovascular diseases represent a serious public health problem, and digital tools offer an opportunity to calculate cardiovascular risk (CVR) in adults. Objective: To describe the design, workflow, and age-specific analysis of a web-based CVR calculator hosted on a server to provide an online service, which includes an administration module. Methodology: A functional architecture is proposed, including user and administrator interaction paths. Within this framework, a set of synthetic test records (n=100) is analyzed to validate the consistency between clinical variables and the CVR output. Results: The system includes a form where age is selected by age ranges, along with sex, BMI, systolic blood pressure, smoking status, cholesterol, and diabetes; at the end, it generates a CVR percentage illustrated with five colors, each representing a category. Access to the monitoring area requires authentication, which allows users to view a table of records and graphs by age group. Conclusion: The tool enables monitoring of the user’s risk and aggregate tracking by age.
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Alegría Ezquerra, E., Alegría Barrero, A., & Alegría Barrero, E. (2012). Estratificación del riesgo cardiovascular: Importancia y aplicaciones. Cardiocore, 47(2), 8–11. https://doi.org/10.1016/S1131-3587(12)70039-0
American Heart Association. (2024). Heart disease and stroke statistics—2024 update: A report from the American Heart Association. Circulation, 149(8), e347–e913. https://doi.org/10.1161/CIR.0000000000001209
Arnett, D. K., Blumenthal, R. S., Albert, M. A., Buroker, A. B., Goldberger, Z. D., Hahn, E. J., … Ziaeian, B. (2019). 2019 ACC/AHA guideline on the primary prevention of cardiovascular disease. Journal of the American College of Cardiology, 74(10), e177–e232. https://doi.org/10.1016/j.jacc.2019.03.010
European Society of Cardiology. (2021). ESC Guidelines on cardiovascular disease prevention in clinical practice. European Heart Journal, 42(34), 3227–3337. https://doi.org/10.1093/eurheartj/ehab484
Kaptoge, S., Pennells, L., De Bacquer, D., Cooney, M. T., Kavousi, M., Stevens, G., … Di Angelantonio, E. (2019). World Health Organization cardiovascular disease risk charts: Revised models to estimate risk in 21 global regions. The Lancet Global Health, 7(10), e1332–e1345. https://doi.org/10.1016/S2214-109X(19)30318-3
Organización Mundial de la Salud. (2023). Enfermedades cardiovasculares (ECV): Datos y cifras. https://www.who.int/es/news-room/fact-sheets/detail/cardiovascular-diseases-(cvds)
Organización Panamericana de la Salud. (2023). Enfermedades cardiovasculares en las Américas. https://www.paho.org/es/temas/enfermedades-cardiovasculares
Quesada, J. A., López-Pineda, A., Gil-Guillén, V. F., et al. (2019). Machine learning to predict cardiovascular risk. International Journal of Clinical Practice, 73, e13389. https://doi.org/10.1111/ijcp.13389
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