Simple A Computer Program for Guiding Management of Cardiovascular Risk Factors and Prescribing
Aroon D. Higorani, Patrick Vallance, British Medical Journal, Vol. 318, Issue 7176, p.101-105
By Praphasri Pitakstham July 1, 1999
July 12, 1999
Objective
! To describe and test against trail data by using a simple and flexible computer program as an aid to manage risk factor and prescribe drugs to lower cholesterol concentration and blood pressure. ! To help physicians implement guidelines on the use of statins or antihypertensives by identifying individuals most likely to benefit. ! To enable patients to make informed decisions about which interventions they would wish to pursue.
Risk of Cardiovascular Disease (CVD)
! Age ! Sex ! Smoking status ! Blood pressure ! Serum concentrations
Total cholesterol High Density Lipoprotien Cholesterol (HDL)
Reducing Serum Cholesterol Concentration
Reduces the incidence of coronary heart disease events
! In patients with a history of angina or myocardial infarction (MI) ! In middle aged men with a high cholesterol concentration but without symptomatic coronary artery disease.
July 12, 1999
Current System
! Calculate levels of risk and possible benefits of intervention ! Develop risk charts or tables
Weakness of the Current System
! Broad estimates of risk based on clusters of risk factors ! Calculations of levels of risk and possible benefits of intervention in any individual are not straightforward and rarely undertaken ! Difficult to quantify precisely the predicted risk and consequences of therapeutic intervention
Needs Analysis
! Cardiovascular disease is a major cause of mortality and
mobility in Britain
! The interaction between risk factors is not additive but
synergistic
! The absolute risk of CHD in any individual is
determined by a complex interplay of several risk factors
! High cost of statins (a choice for secondary prevention)
recommended by the Standing Medical Advisory Committee
July 12, 1999
Computer Program
Developed at the Vascular Risk Clinic, the University College Hospital, England
! Use a Microsoft Excel version 5.0 workbook available on a single floppy disk ! Run on a personal computer ! Provide a graphical and numerical display of the risk of cardiovascular outcomes for any given combination of clinical variables (See Figure 1.)
Boundaries
! Logistic regression equations derived from the Framingham populations ! Patient profile--age, total cholesterol level, HDL level, systolic blood pressure, smoking status, blood sugar level, previous diagnoses (Diabetes, Aterial Fibrilation, ECG-LVH, history of CVD, hypertensive treatment) ! Published data from large intervention studies used to form the basis of current recommendations on treatment policies WOSCOPS (West of Scotland Coronary Prevention Study, a primary prevention trial) 4S (The Scandinavian Simvastatin Survival Study) CARE (The Cholesterol and Recurrent Events Trial, a secondary prevention trial)
Evaluate Method
! Patients information are entered into a simple
screen
! Risks are calculated with logistic regression
equations derived from the Framingham populations
! Framingham populations
- A large cohort in the United States studied prospectively over many years - Observing the cumulative number of events use of heart coronary disease and cardiovascular disease among the original Framingham cohort and the subjects of the Framingham offspring study - Designed for use in the setting of primary prevention and forms the basis of some commonly used guidelines and risk tables such as the Sheffield and New Zealand tables.
July 12, 1999
Evaluate Method (Cont)
! Predict risks by using the mean patient data from each trial--WOSCOPS, 4S, CARE ! Treated the mean patient data as a hypothetical individual to generate a predicted outcome using definitions of end points that were similar to those of the trials, but not always identical with them
Evaluate Method(Cont)
! Display an individual's risks Risk of coronary heart disease, myocardial infarction, and stroke Comparison between smokers and non-smokers with age adjusted population mean levels of Total cholesterol High density lipoprotein cholesterol Systolic blood pressure ! Print out of data and predicted outcomes
Evaluate Method (Cont)
! Stored in a database ! Interrogated in order to provide
Information on changes in risk factors over time Success in risk reduction Prescribing policy against risk scores The overall burden of cardiovascular disease in a practice population.
July 12, 1999
Input
! Patient information
Total cholesterol HDL
Age Cholesterol concentration Systolic blood pressure Smoking status Blood sugar Pervious diagnoses
Diabetes AF ECG-LVH History of CVD Hypertensive treatment
Activities
! Estimate risk ! Analyze how the risk estimate generated by the program differed from the risk estimate provided by
The Sheffield tables Framingham data WOSCOPS 4S CARE.
Output
! Predict risk (comparing between smokers and non-smokers)
CHD MI Death from CHD Stoke
! Predict reduction in relative risk ! Predict effects of intervention ! Simply guide on treatment according to best available evidence
July 12, 1999
Advantages
! Use the full Framingham risk score rather than an
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