Cited by 178Health Promotion and Cardiovascular PreventionLipoproteins and Cardiovascular HealthCardiovascular Health and Risk Factors

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Framingham-based tools to calculate the global risk of coronary heart disease: A systematic review of tools for clinicians

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Sheridan, Stacey, Pignone, Michael, Mulrow, Cynthia·2003·Journal of General Internal Medicine

DOI 10.1111/j.1525-1497.2003.30107.xPMC PMC1494957

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Abstract

Purpose To examine the features of available Framingham-based risk calculation tools and review their accuracy and feasibility in clinical practice.Data sources medline, 1966-April 2003, and the google search engine on the Internet. TOOL AND STUDY SELECTION: We included risk calculation tools that used the Framingham risk equations to generate a global coronary heart disease (CHD) risk. To determine tool accuracy, we reviewed all articles that compared the performance of various Framingham-based risk tools to that of the continuous Framingham risk equations. To determine the feasibility of tool use in clinical practice, we reviewed articles on the availability of the risk factor information required for risk calculation, subjective preference for 1 risk calculator over another, or subjective ease of use.Data extraction Two reviewers independently reviewed the results of the literature search, all websites, and abstracted all articles for relevant information.Data synthesis Multiple CHD risk calculation tools are available, including risk charts and computerized calculators for personal digital assistants, personal computers, and web-based use. Most are easy to use and available without cost. They require information on age, smoking status, blood pressure, total and HDL cholesterol, and the presence or absence of diabetes. Compared to the full Framingham equations, accuracy for identifying patients at increased risk was generally quite high. Data on the feasibility of tool use was limited.Conclusions Several easy-to-use tools are available for estimating patients' CHD risk. Use of such tools could facilitate better decision making about interventions for primary prevention of CHD, but further research about their actual effect on clinical practice and patient outcomes is required.

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Additional file 2 of Risk factors for ANA positivity in healthy persons
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Additional file 4 of Risk factors for ANA positivity in healthy persons
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Additional file 6 of Risk factors for ANA positivity in healthy persons
Li, Q., Karp, D. R., Quan, J., Branch, V. K., Zhou, J., Lian, Y., Chong, B. F., Wakeland, E. K., & Olsen, N. J. (2020) · Figshare · doi:10.6084/m9.figshare.12877066
Additional file 3 of Risk factors for ANA positivity in healthy persons
Li, Q., Karp, D. R., Quan, J., Branch, V. K., Zhou, J., Lian, Y., Chong, B. F., Wakeland, E. K., & Olsen, N. J. (2020) · Figshare · doi:10.6084/m9.figshare.12877057
Additional file of Risk factors for ANA positivity in healthy persons
Li, Q., Karp, D. R., Quan, J., Branch, V. K., Zhou, J., Lian, Y., Chong, B. F., Wakeland, E. K., & Olsen, N. J. (2020) · Figshare · doi:10.6084/m9.figshare.12877048
Additional file 7 of Risk factors for ANA positivity in healthy persons
Li, Q., Karp, D. R., Quan, J., Branch, V. K., Zhou, J., Lian, Y., Chong, B. F., Wakeland, E. K., & Olsen, N. J. (2020) · Figshare · doi:10.6084/m9.figshare.12877069
Additional file 5 of Risk factors for ANA positivity in healthy persons
Li, Q., Karp, D. R., Quan, J., Branch, V. K., Zhou, J., Lian, Y., Chong, B. F., Wakeland, E. K., & Olsen, N. J. (2020) · Figshare · doi:10.6084/m9.figshare.12877063
Additional file 8 of Risk factors for ANA positivity in healthy persons
Li, Q., Karp, D. R., Quan, J., Branch, V. K., Zhou, J., Lian, Y., Chong, B. F., Wakeland, E. K., & Olsen, N. J. (2020) · Figshare · doi:10.6084/m9.figshare.12877072
Additional file 1 of Risk factors for ANA positivity in healthy persons
Li, Q., Karp, D. R., Quan, J., Branch, V. K., Zhou, J., Lian, Y., Chong, B. F., Wakeland, E. K., & Olsen, N. J. (2020) · Figshare · doi:10.6084/m9.figshare.12877051
A diagnosis tool for early detection and classification of heart disease in individuals using transformer mechanisms
Arif, S., Son, S. H., Kim, H. Y., Kim, S. C., & Lee, J. Y. (2026) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2026.109248 · Cited by 2

Authors: Sheridan, S., Pignone, M., & Mulrow, C.
Affiliations: University of North Carolina at Chapel Hill (US)
The University of Texas at San Antonio Health Science Center (US)
Corresponding author: Sheridan, Stacey
ORCID: Sheridan, Stacey
Pignone, Michael
Mulrow, Cynthia
Venue: Journal of General Internal Medicine
Publisher: Springer Science and Business Media LLC
Published: 2003-12
Volume: 18
Issue: 12
Pages: 1039-1052
ISSN: 0884-8734 (ISSN-L)
1525-1497
DOI: 10.1111/j.1525-1497.2003.30107.x
PMC: PMC1494957
OpenAlex: W2000702318
Cited by: 178
References: 65
Citations by year: 2026: 1 · 2025: 4 · 2024: 3 · 2023: 3 · 2022: 3 · 2021: 5 · 2020: 14 · 2019: 6 · 2018: 3 · 2017: 6 · 2016: 8 · 2015: 10 · 2014: 10 · 2013: 13 · 2012: 15
FWCI: 1.51
Type: journal article
Language: en
Open access: green
europepmc.org
Locations: Journal of General Internal Medicine (publishedVersion)
Europe PMC (PubMed Central) (publishedVersion)
PubMed Central (publishedVersion)
PubMed (publishedVersion)
Topics: Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Health Promotion and Cardiovascular Prevention
Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Lipoproteins and Cardiovascular Health
Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiovascular Health and Risk Factors
Keywords: coronary artery disease, Framingham risk equation, cardiovascular risk prediction, risk calculator, risk charts, primary prevention, clinical feasibility, personal digital assistants, risk factor assessment
MeSH terms: Coronary Disease, Humans, Predictive Value of Tests, Risk Factors, MEDLINE, Risk Assessment, Internet

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Framingham-based tools to calculate the global risk of coronary heart disease: A systematic review of tools for clinicians

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