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Cited by 127Health Promotion and Cardiovascular PreventionLipoproteins and Cardiovascular HealthCardiovascular Health and Risk Factors

The DOI matches its Crossref record; 37 of the 37 references it cites were found in a registry or an index.

A New Method for Chd Prediction and Prevention Based on Regional Risk Scores and Randomized Clinical Trials; PRECARD(R) and the Copenhagen Risk Score

Thomsen, T. F., Davidsen, M., Ibsen, H., Jorgensen, T., Jensen, G., Borch-Johnsen, K.·2001·European Journal of Cardiovascular Prevention & Rehabilitation
DOI 10.1177/174182670100800508
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Abstract

BACKGROUND: There is a considerable gap between the recommended prevention of coronary heart disease (CHD) in the guidelines from the European Society of Cardiology and the actually conducted clinical practice in preventive cardiology. A new method for implementing the recommended clinical practice in preventive cardiology is described. AIM: To develop a comprehensive and flexible health educational computer program (the PRECARD program) for individual coronary risk prediction and multifactorial prevention. MATERIAL AND METHODS: The PRECARD program contains a new coronary risk score (the Copenhagen Risk Score) for myocardial infarction and a model for calculating the effect of intervention. Two Danish population studies (n = 11,765) with 10 years of follow up were used to establish the risk score. The included risk factors were: age, sex, cholesterol (incl. HDL), systolic blood pressure, smoking, body mass index, diabetes, familial predisposition and previous heart disease. Nine randomized clinical trials were used to estimate the effect of intervention. RESULTS: The findings in the Copenhagen Risk Score and the estimated effect of intervention deducted from the clinical trials were comparable to other similar studies. The PRECARD program gives a graphical or numerical presentation of absolute coronary risk, the potential benefit of intervention, the relative impact of modifiable risk factors and numbers needed to treat. The program compiles individually tailored health messages in print for the patient. The program can easily be adjusted to different regional risk scores, other end-points and languages. CONCLUSION: The PRECARD program may promote the recommended clinical practice in preventive cardiology by serving as an integrated part of the lifestyle consultation.

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Crossref · 10.1177/174182670100800508

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Metadata

Authors
Thomsen, T. F., Davidsen, M., Ibsen, H., Jorgensen, T., Jensen, G., & Borch-Johnsen, K.
Affiliations
  • Glostrup Hospital (DK)
  • Bispebjerg Hospital (DK)
Corresponding author
Thomsen, T. F.
ORCID
Venue
European Journal of Cardiovascular Prevention & Rehabilitation
Publisher
Oxford University Press (OUP)
Published
2001-10-01
Volume
8
Issue
5
Pages
291-297
ISSN
  • 1741-8267 (ISSN-L)
  • 1741-8275
DOI
10.1177/174182670100800508
OpenAlex
W2110061973
Cited by
127
References
37
Citations by year
2025: 1 · 2024: 2 · 2023: 1 · 2022: 1 · 2021: 1 · 2018: 3 · 2017: 2 · 2016: 3 · 2015: 10 · 2014: 3 · 2013: 7 · 2012: 8
FWCI
9.64
Type
journal article
Language
en
Open access
closed
Locations
  • European Journal of Cardiovascular Prevention & Rehabilitation (publishedVersion)
  • PubMed (publishedVersion)
Funders
Hjerteforeningen
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, cardiovascular risk prediction, multifactorial prevention, myocardial infarction risk, intervention effect estimation, number needed to treat, modifiable risk factors, preventive cardiology
MeSH terms
Adult, Age Factors, Aged, Aged, 80 and over, Blood Pressure, Cholesterol, Coronary Disease, Denmark, Female, Follow-Up Studies, Humans, Lipoproteins, HDL, Male, Middle Aged, Myocardial Infarction, Predictive Value of Tests, Risk Factors, Software, Cohort Studies, Suburban Health

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