Cited by 7,491Health Promotion and Cardiovascular PreventionCardiovascular Health and Risk FactorsLipoproteins and Cardiovascular Health

The DOI matches its Crossref record; 52 of the 52 references it cites were found in a registry or an index.

General Cardiovascular Risk Profile for Use in Primary Care: The Framingham Heart Study

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Abstract

Background— Separate multivariable risk algorithms are commonly used to assess risk of specific atherosclerotic cardiovascular disease (CVD) events, ie, coronary heart disease, cerebrovascular disease, peripheral vascular disease, and heart failure. The present report presents a single multivariable risk function that predicts risk of developing all CVD and of its constituents. Methods and Results— We used Cox proportional-hazards regression to evaluate the risk of developing a first CVD event in 8491 Framingham study participants (mean age, 49 years; 4522 women) who attended a routine examination between 30 and 74 years of age and were free of CVD. Sex-specific multivariable risk functions (“general CVD” algorithms) were derived that incorporated age, total and high-density lipoprotein cholesterol, systolic blood pressure, treatment for hypertension, smoking, and diabetes status. We assessed the performance of the general CVD algorithms for predicting individual CVD events (coronary heart disease, stroke, peripheral artery disease, or heart failure). Over 12 years of follow-up, 1174 participants (456 women) developed a first CVD event. All traditional risk factors evaluated predicted CVD risk (multivariable-adjusted P <0.0001). The general CVD algorithm demonstrated good discrimination (C statistic, 0.763 [men] and 0.793 [women]) and calibration. Simple adjustments to the general CVD risk algorithms allowed estimation of the risks of each CVD component. Two simple risk scores are presented, 1 based on all traditional risk factors and the other based on non–laboratory-based predictors. Conclusions— A sex-specific multivariable risk factor algorithm can be conveniently used to assess general CVD risk and risk of individual CVD events (coronary, cerebrovascular, and peripheral arterial disease and heart failure). The estimated absolute CVD event rates can be used to quantify risk and to guide preventive care.

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Crossref · 10.1161/circulationaha.107.699579

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  1. 10.1016/S0140-6736(05)70240-3 · DOI
  2. 10.1161/circ.83.1.1984895 · DOI
  3. 10.1161/circ.105.3.310 · DOI
  4. 10.1161/circ.97.18.1837 · DOI
  5. 10.1161/str.22.3.2003301 · DOI
  6. 10.1161/circ.96.1.44 · DOI
  7. 10.1161/circ.100.9.988 · DOI

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Metadata

Authors
D’Agostino, R. B., Vasan, R. S., Pencina, M. J., Wolf, P. A., Cobain, M., Massaro, J. M., & Kannel, W. B.
Affiliations
Boston University (US)
Venue
Circulation
Published
2008-02-12
Volume
117
Issue
6
Pages
743-753
ISSN
  • 0009-7322 (ISSN-L)
  • 1524-4539
OpenAlex
W2148092884
Cited by
7,491
References
52
Citations by year
2026: 491 · 2025: 567 · 2024: 552 · 2023: 511 · 2022: 529 · 2021: 592 · 2020: 562 · 2019: 454 · 2018: 475 · 2017: 452 · 2016: 385 · 2015: 389 · 2014: 391 · 2013: 323 · 2012: 294
FWCI
169.19
Type
journal article
Language
en
Open access
Locations
  • Circulation (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • National Institutes of Health (n01hc25195-41-0-1)
  • National Heart, Lung, and Blood Institute (2K24 HL 04334, N01‐HC25195, K24HL004334)
Topics
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Health Promotion and Cardiovascular Prevention
  • Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiovascular Health and Risk Factors
  • Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Lipoproteins and Cardiovascular Health
Keywords
cardiovascular risk prediction, atherosclerotic cardiovascular disease, Framingham risk score, coronary artery disease, stroke, peripheral arterial disease, heart failure, traditional risk factors, cholesterol, blood pressure, smoking, diabetes mellitus, primary care
MeSH terms
Adult, Aged, Algorithms, Cardiovascular Diseases, Female, Humans, Longitudinal Studies, Male, Middle Aged, Primary Health Care, Risk Factors, Sex Factors, Multivariate Analysis, Proportional Hazards Models, Risk Assessment

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