Cardiovascular disease risk profiles
KM Anderson, PM Odell, PWF Wilson, WB Kannel - American heart journal, 1991 - Elsevier
This article presents prediction equations for several cardiovascular disease endpoints,
which are based on measurements of several known risk factors. Subjects (n= 5573) were …
which are based on measurements of several known risk factors. Subjects (n= 5573) were …
How generalizable are coronary risk prediction models? Comparison of Framingham and two national cohorts
Background Previous models used to predict individual risk of death from coronary heart
disease (CHD) were developed from data of 3 decades ago from the Framingham Heart …
disease (CHD) were developed from data of 3 decades ago from the Framingham Heart …
Cardiovascular disease risk factors: epidemiology and risk assessment
B Dahlöf - The American journal of cardiology, 2010 - Elsevier
Current epidemiologic predictions show that the world is heading for a vascular tsunami of
pandemic proportions. The number of people at high risk from cardiovascular disease is …
pandemic proportions. The number of people at high risk from cardiovascular disease is …
Coronary risk prediction in adults (the Framingham Heart Study)
PWF Wilson, WP Castelli, WB Kannel - The American journal of cardiology, 1987 - Elsevier
Abstract The Framingham Heart Study, an ongoing prospective study of adult men and
women, has shown that certain risk factors can be used to predict the development of …
women, has shown that certain risk factors can be used to predict the development of …
Primary and subsequent coronary risk appraisal: new results from the Framingham study
RB D'Agostino, MW Russell, DM Huse, RC Ellison… - American heart …, 2000 - Elsevier
Background Coronary heart disease continues to be one of the most common chronic
illnesses in the United States and most of the developed world. Clinicians and health …
illnesses in the United States and most of the developed world. Clinicians and health …
[HTML][HTML] Prediction of mortality from coronary heart disease among diverse populations: is there a common predictive function?
DPC Group - Heart, 2002 - ncbi.nlm.nih.gov
Objectives: To examine the generalisability of multivariate risk functions from diverse
populations in three contexts: ordering risk, magnitude of relative risks, and estimation of …
populations in three contexts: ordering risk, magnitude of relative risks, and estimation of …
Concept and usefulness of cardiovascular risk profiles
WB Kannel, RB D'Agostino, L Sullivan… - American heart journal, 2004 - Elsevier
Despite major advances in the diagnosis and treatment of atherosclerotic cardiovascular
disease (CVD) in the past century, it remains a serious clinical and public health problem …
disease (CVD) in the past century, it remains a serious clinical and public health problem …
Long-term epidemiologic prediction of coronary disease: the Framingham experience
WB Kannel, M Larson - Cardiology, 1993 - karger.com
Atherosclerotic cardiovascular disease is a complex problem involving lipid deposition,
pressure, rheologic forces, carbohydrate tolerance and thrombogenesis. The major …
pressure, rheologic forces, carbohydrate tolerance and thrombogenesis. The major …
Representativeness of the Framingham risk model for coronary heart disease mortality: a comparison with a national cohort study
PE Leaverton, PD Sorlie, JC Kleinman… - Journal of chronic …, 1987 - Elsevier
Abstract The Framingham Heart Study has been the foundation upon which several national
policies regarding risk factors for coronary heart disease mortality are based. The NHANES I …
policies regarding risk factors for coronary heart disease mortality are based. The NHANES I …
Predicting the 30-year risk of cardiovascular disease: the framingham heart study
MJ Pencina, RB D'Agostino Sr, MG Larson… - Circulation, 2009 - Am Heart Assoc
Background—Present cardiovascular disease (CVD) risk prediction algorithms were
developed for a≤ 10-year follow up period. Clustering of risk factors at younger ages and …
developed for a≤ 10-year follow up period. Clustering of risk factors at younger ages and …