title: [Practicality of cardiovascular risk functions].
abstract: Cardiovascular diseases prevention strategies require refinement because their incidence decreases very slowly. Risk functions were developed by including classical cardiovascular risk factors (age, sex, smoking, diabetes, blood pressure, and basic lipid profile) in cohorts followed more than 10 years. They are reasonably precise for population screening of, principally, coronary artery disease risk, required in all cardiovascular primary prevention clinical guidelines. Coronary artery disease risk functions classify patients in risk strata to concentrate the maximum therapeutic and life style effort in the highest risk groups, in which the number needed to treat and cost-effectiveness are optimal. By communicating the relative risk and vascular age to patients, increased motivation to comply with the proposed drug and life-style modifications can be achieved. Approximately 20% of the population 35 to 74 years old has an intermediate risk that requires reclassification into high or low risk because they concentrate 35% of population coronary artery disease events. Several biomarkers (biochemical, genetic or imaging) are being tested to improve coronary artery disease risk functions precision. Computerized systems of health facilities should incorporate, automated risk calculation in order to support the preventive task of health care providers.
authors.affiliation: Grupo de Epidemiología y Genética Cardiovascular, Instituto Hospital del Mar de Investigaciones Médicas, Barcelona, Cataluña, España. Address: Instituto Hospital del Mar de Investigaciones Médicas, Doctor Aiguader 88, Barcelona, Cataluña, España. Email: jmarrugat@regicor.cat.
authors.forename: Jaume
authors.initials: J
authors.lastname: Marrugat
authors.affiliation: Grupo de Epidemiología y Genética Cardiovascular, Instituto Hospital del Mar de Investigaciones Médicas, Barcelona, Cataluña, España.
authors.forename: Roberto
authors.initials: R
authors.lastname: Elosua
authors.affiliation: Instituto de Matemática y Física, Universidad de Talca, Talca, Chile.
authors.forename: Gloria
authors.initials: G
authors.lastname: Icaza
authors.affiliation: Cardiocentro Ernesto Che Guevara, Villa Clara, Cuba.
authors.forename: Alberto
authors.initials: A
authors.lastname: Morales-Salinas
authors.affiliation: Grupo de Epidemiología y Genética Cardiovascular, Instituto Hospital del Mar de Investigaciones Médicas, Barcelona, Cataluña, España.
authors.forename: Irene R
authors.initials: IR
authors.lastname: Dégano
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D015415:Biomarkers / Q000378:metabolism; D002318:Cardiovascular Diseases / Q000209:etiology / Q000503:physiopathology / Q000517:prevention & control*; D003324:Coronary Artery Disease / Q000209:etiology / Q000503:physiopathology / Q000517:prevention & control*; D006801:Humans; D008403:Mass Screening / Q000379:methods; D008875:Middle Aged; D012307:Risk Factors
chemical_list: D015415:Biomarkers
keywords:  cardiovascular disease;  risks factors; cardiovascular risk