| CVD Risk Guideline
2. Use calculator to assess CVD risk
Identify people at clinically determined high risk
Assess CVD risk as high for people with moderate-to-severe chronic kidney disease meeting any of these criteria:
|Assess CVD risk as high for people with a confirmed diagnosis of familial hypercholesterolaemia.
Moderate-to-severe chronic kidney disease
Chronic kidney disease (CKD) is an independent risk factor for CVD.
Estimated glomerular filtration rate (eGFR) is inversely correlated with CVD risk at a population level; as eGFR decreases, starting from <75mL/min/1.73m2, the risk of CVD-related mortality increases, up to an approximate three-fold risk in people with eGFR of 15mL/min/1.73m2.19
The increase in risk is even greater for young adults, in whom CVD-related mortality may increase to an approximate ten-fold risk in those with eGFR 15mL/min/1.73m2.20
Increased albumin excretion is also associated with CVD mortality risk, independent of eGFR.19
People with moderate-to-severe CKD (sustained eGFR <45mL/min/1.73m2 and/or persistent uACR >25mg/mmol [men] or uACR >35mg/mmol [women]) are at clinically determined high risk and should be automatically managed as high CVD risk.
Familial hypercholesterolaemia (FH) is the most common inherited cause of premature CHD, with a prevalence of 1 in 250.21
People with diagnosed FH are at clinically determined high risk and should be automatically managed as high CVD risk.
Individuals with FH should be treated according to Australian guidelines for managing FH.22 FH-specific calculators may be useful.23,24
Using the Australian cardiovascular disease risk calculator
The Australian cardiovascular disease risk calculator (Aus CVD Risk Calculator) is validated for use in people without known
CVD aged 30 to 79 years who do not already meet high risk
criteria. The accuracy of risk estimates in people aged 80 and
over is uncertain and the Aus CVD Risk Calculator is likely
to underestimate risk in these people.
The Aus CVD Risk Calculator produces estimated 5-year CVD risk scores, expressed as a percentage representing the person’s probability of dying or being hospitalised due to myocardial infarction, angina, other coronary heart disease, stroke, transient ischaemic attack, peripheral vascular disease, congestive heart failure or other ischaemic CVD-related conditions within the next 5 years.
Variables and instructions are shown in Table 4.
Table 4: Aus CVD Risk Calculator variables and instructions for use
Enter age in years
The Aus CVD Risk Calculator is validated for adults aged 30 to 79 years.
Enter sex at birth
(there is currently insufficient data to stratify risk for people who are intersex or non-binary sex)
Choose from three categories:
|Blood pressure (BP)
Enter systolic blood pressure (SBP) in mmHg.
Use the average of the last two seated, in-clinic BP measurements.
Convert home and ambulatory BP readings to in-clinic equivalents before entering into the calculator.
Enter ratio of total cholesterol (TC) to high-density lipoprotein cholesterol (HDL-C).
Use most recent measurements (fasting or non-fasting).
|Enter diabetes status: YES or NO
CVD medicines used during the 6 months prior to risk assessment (lipid-modifying, BP-lowering, and/or antithrombotic medicines)
Note: Relationship between risk and CVD medicines is associative, not causative.
Lipid-modifying medicines – atorvastatin, fluvastatin, pravastatin, simvastatin, acipimox, bezafibrate, cholestyramine, clofibrate, colestipol, ezetimibe, ezetimibe with simvastatin, gemfibrozil and nicotinic acid.
BP-lowering medicines – angiotensin converting enzyme inhibitors, betablockers, thiazide, angiotensin II receptor blockers and calcium channel blockers.
Antithrombotic medicines – aspirin, clopidogrel, dipyridamole, prasugrel, ticagrelor, ticlopidine, warfarin, dabigatran, phenindione and rivaroxaban.
|Enter postcode. Postcode is used to calculate Socio-Economic Indexes for Areas (SEIFA) quintile, and under the discretion of the clinician, may be manually adjusted to better reflect the socioeconomic status of individual patients.
|Medical history of atrial fibrillation
Known history of electrocardiogram (ECG) confirmed atrial fibrillation: YES or NO.
Both paroxysmal and persistent AF are included in the definition of AF.
|Additional diabetes-specific variables for people with diabetesa for a more accurateassessment of risk if selected.
|Time since diagnosis of diabetes
|Enter time in years.
|Glycated haemoglobin (HbA1c)
|Enter HbA1c in mmol/mol or % (single non-fasting).
|Enter urine albumin-creatinine ratio (uACR)
(measured in mg/mmol).
Enter eGFR in mL/min/1.73m2.
If needed, eGFR should be calculated based on the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation.
Serum creatinine used in the calculation should be based on the most recent result.
|Body mass index(BMI)
|Measure weight in kilograms and height in metres.
Calculate BMI: kg/m2.
|Record use of insulin in the 6 months before risk assessment.
- The equation on which the Aus CVD Risk Calculator is based has not been validated for people with type 1 diabetes.
- Whilst uACR and eGFR have been shown to independently improve prediction of cardiovascular events, they are only included as variables in the diabetes-specific equation due to lack of availability of data in the general population PREDICT cohort. Instead, they have been incorporated into the overall risk calculation as a reclassification factor. In future, when data is available from the PREDICT population, these measures may be incorporated directly into the risk equation.
Like most other CVD risk equations, the Aus CVD Risk Calculator includes traditional variables such as age, sex, smoking status, diabetes, BP and lipids.
It also includes other relatively easily measured variables that improve the performance of the equation in predicting CVD risk, above and beyond these variables. This helps avoid risk that might otherwise be underestimated or overestimated.
Type 2 diabetes is independently associated with a two-fold increased risk of developing CVD.25 Risk is also higher in people with longstanding diabetes, microvascular complications and suboptimal glycaemic control.26,27 However, due to significant heterogeneity in risk among people living with diabetes, it is important to stratify risk further within this cohort.28
A type 2 diabetes-specific CVD risk prediction equation was developed and validated using a contemporary New Zealand diabetes population.29 This equation has been incorporated into the new Aus CVD Risk Calculator to provide a more accurate CVD risk estimate for people with type 2 diabetes.
Time since diagnosis of diabetes, HbA1c, eGFR, uACR, BMI and insulin use are included in the new Aus CVD Risk Calculator. Newer classes of glucose-lowering medicines, including SGLT2 inhibitors, GLP-1 receptor agonists and DPP4-inhibitors, have not been included in the risk calculator because data were not available.
Type 1 diabetes
Although the same main risk factors (including diabetes duration, presence of kidney disease, glycaemic control) influence CVD risk as for type 2 diabetes, the Aus CVD Risk Calculator is not validated for type 1 diabetes. Using the Aus CVD Risk Calculator in people with type 1 diabetes may give an inaccurate risk estimate.
In addition to physiological and lifestyle factors, socioeconomic status is also associated with increased CVD risk. In the Australian population, CVD risk varies according to socioeconomic status, with greater disadvantage associated with higher incidences of primary and secondary cardiovascular events.30
Including socioeconomic status in risk prediction improves accuracy, compared with using risk factors alone.1
The Aus CVD Risk Calculator uses Socio-Economic Indexes for Areas (SEIFA)31 quintiles obtained from residential postcodes. SEIFA is a population-level summary measure that reflects determinants such as education, housing, employment and income.
SEIFA quintiles based on postcode31 provide the most readily accessible means of incorporating socioeconomic status into CVD risk assessment in Australia at this time.
Since SEIFA is an average based on postcode, it may not accurately reflect the socioeconomic status of all individuals within that postcode. If the person has a level of disadvantage that differs markedly from that of the average for their postcode, their socioeconomic quintile can be manually adjusted up or down in the risk calculator.
First Nations people
The determinants included in SEIFA may not fully capture the environmental, social, political and economic determinants of CVD and health inequality experienced by First Nations people.
In particular, SEIFA indices will not fully reflect the broad impacts of discrimination and disadvantage that are widely understood to be key drivers of health disparities between First Nations communities and non-Indigenous Australians.32
Socioeconomic status may also influence the risk of CVD differentially across First Nations communities.
When considering reclassifying risk for First Nations people (see Recommendation on ethnicity), it may be appropriate to consider a broader range of socioeconomic determinants than those incorporated into the SEIFA measure used in the Aus CVD Risk Calculator.
- Management of type 2 diabetes: A handbook for general practice - RACGP and Diabetes Australia
- Living Evidence Guidelines in Diabetes - The Living Evidence for Diabetes Consortium
- Type 2 diabetes treatment: A new blood glucose management algorithm for type 2 diabetes - Australian Diabetes Society
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1. Identify people for CVD risk assessment
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3. Identify CVD risk category