Primary and subsequent coronary risk appraisal: New results from The Framingham Study

Abstract

These new models are useful tools for better understanding the relation between risk factors and the occurrences of CHD events in individuals who are free of cardiovascular disease as well as persons who have had a prior CHD event or stroke. With the development of these latter models, the importance of blood lipid levels, diabetes, and, in women, systolic blood pressure and cigarette smoking as independent predictors of risk is once again underscored.

Population Impact & Efficiency of Benefit‐Targeted Versus Risk‐Targeted Statin Prescribing for Primary Prevention of Cardiovascular Disease

“…ASCVD indicates atherosclerotic cardiovascular disease; CIs, confidence intervals; NNT 10 , number need to treat over 10 years to prevent 1 event.aCIs presented here are the 2.5th and 97.5th percentiles of the distribution of estimates derived from analyzing bootstrapped samples accounting for the complex National Health and Nutrition Examination Survey survey design and multiple imputation procedure.bWe do not present confidence intervals for maximum NNT 10 because this value is entirely dependent (defined by) a single outlier value in the data set and does not represent a statistical estimate.cAtherosclerotic cardiovascular disease (ASCVD) risk was estimated using the algorithm described in the 2013 American College of Cardiology/American Heart Association Guideline on the Assessment of Cardiovascular Risk2 for persons without pre‐existing cardiovascular disease, or an alternate Framingham‐based risk equation6, 7 with extrapolation to 10 years, for persons with and without pre‐existing cardiovascular disease, respectively.…”

“…Atherosclerotic cardiovascular disease (ASCVD) risk was estimated using the algorithm described in the 2013 American College of Cardiology/American Heart Association Guideline on the Assessment of Cardiovascular Risk2 for persons without pre‐existing cardiovascular disease, or an alternate Framingham‐based risk equation6, 7 with extrapolation to 10 years, for persons with and without pre‐existing cardiovascular disease, respectively.…”

“…For persons reporting pre‐existing cardiovascular disease (“Has a doctor or other health professional ever told you that you had” coronary heart disease, angina, heart attack, or stroke), we used a Framingham Heart Study–based calculator designed for calculation of 2‐year risk of recurrent coronary heart disease (myocardial infarction, coronary insufficiency, angina pectoris, and sudden and nonsudden coronary death; stroke is not included) 6, 7. We calculated 2‐year risk with current age and current risk factor levels and then recalculated risk every 2 years (assuming that age increases, but no other risk factors change) in order to extrapolate risk to 10 years, and then assumed that this estimate was comparable to the ASCVD risk calculator described above.…”

Estimating the Risk of Developing Glaucoma

“…The concept of risk factor became widespread in medicine ever since the landmark Framingham Heart Study first reported in the early 1960s that cigarette smoking, elevated blood cholesterol, and high blood pressure were predictors of the likelihood of dying from heart disease. Framingham investigators then started developing predictive models to evaluate the global risk of cardiovascular disease based on the summation of all major risk factors [1-3]. Risk assessment and prevention has contributed significantly to reduce mortality from cardiovascular disease and its successful implementation in this scenario has stimulated its application to several other areas.…”

Cost-effectiveness of switching to biphasic insulin aspart in poorly-controlled type 2 diabetes patients in China

“…The reliability of simulated outcomes has been tested, with results validated against those reported by clinical trials and epidemiological studies. 32 While the data used in the CORE Diabetes Model is derived primarily from landmark studies such as the UKPDS 21,33-38 and Framingham Heart Study, 39 conducted in largely white populations, China-specific risks of modelled events were incorporated in this analysis where data were available. Age-and sex-stratified mortality from nondiabetes-related causes (i.e.…”