title: Risk scores for prediction of coronary heart disease: an update.
abstract: Risk scores for the prediction of coronary heart disease (CHD) have greatly improved in the past 30 years. While standardized baseline measurements and modern technology aid in the development of increasingly accurate CHD risk algorithms, recent reports have shown that simple prediction tools using a basic set of variables, including age, systolic blood pressure, smoking, hypertension, exercise, body mass index, diabetes, and family history are predictive of CHD risk and can potentially be self-administered.
authors.affiliation: Division of Cardiology, Emory University School of Medicine, EPICORE, Suite 1 North, 1256 Briarcliff Road, Atlanta, GA 30306, USA. peter.wf.wilson@emory.edu
authors.forename: Peter W F
authors.initials: PW
authors.lastname: Wilson
mesh_terms: D000465:Algorithms; D003327:Coronary Disease / Q000175:diagnosis / Q000453:epidemiology*; D006801:Humans; D011237:Predictive Value of Tests; D012016:Reference Values; D018570:Risk Assessment; D016896:Treatment Outcome