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Validation of a population coronary disease predictive system

The CASSANDRA model

Bibliographic Data

ID11180489
AuthorsCindy A Kermott (0000-0003-1925-6949, Mayo Clinic, corresponding author), Kent R Bailey (0000-0001-8968-643X, Mayo Clinic), Josephine E Olson (0000-0003-4944-7789, Mayo Clinic), Janet E Olson (Mayo Clinic)
Year2014
Volume68
Issue11
Pages1009-1009
Publication date2014-11-01
Open AccessNo
TypeARTICLE
VenueJournal of Epidemiology and Community Health (JOURNAL)
Journal identifiersISSN: 0143-005X • E-ISSN: 1470-2738
PublisherBMJ (PUBLISHER • GB)
DOI10.1136/jech-2014-204165
PMID24817707
OpenAlexW2119996129
LanguageEN

Accurate prediction allows us to plan. This prediction capability has been made possible through the understanding of epidemiological principles of causation, while relying on statistical tools, or models, using an unbiased sample from a representative population in order to make an accurate claim. In the research work of Grau et al , an attempt had been undertaken to validate a prediction tool to estimate the disease burden, or risk, of coronary heart disease (CHD) should certain and known modifiable risk factors be altered given a public health initiative aimed at disease reduction. The risk factors identified include those that are non-modifiable (age, gender) and those that may be modified (smoking, hypertension, diabetes, blood pressure). These had been originally defined in the Framingham Heart Study with 10-year risk of CHD contingent on the role of each of these factors. Risk of disease had been determined

Coronary disease · Coronary heart disease · Environmental health · Population · Blood Pressure and Hypertension Studies · Cardiac Health and Mental Health · Health and Lifestyle Studies · Internal Medicine · Medicine

Highly citedNo

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