PREVENT ASCVD Risk Calculator
PREVENT (2023) 10-year risk for a first atherosclerotic cardiovascular disease (ASCVD) event or heart failure
RESULTS
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ASCVD Risk Evaluation (PREVENT 2023)
10-year risk of atherosclerotic cardiovascular disease:
6.8%
Borderline Risk
(5% to < 7.5%)
Intermediate Risk
(≥ 7.5% to < 20%)
Contribution of Each Risk Factor
Each factor affecting 10-year ASCVD risk can be measured on its own, whether it is protective (reducing risk) or harmful (increasing risk):
ASCVD Risk with Optimal Risk Factors
10-year ASCVD risk in a similar patient with optimal risk factors
:
1.8%
Coronary Heart Disease and Stroke Risk
ASCVD is a composite of coronary heart disease (myocardial infarction) and stroke (ischemic or hemorrhagic). The 10-year risk of each of these outcomes individually are:
10-year risk of coronary heart disease (CHD)
4.5%
10-year risk of stroke
2.6%
ASCVD Risk with PCE 2013 Equations
PREVENT has replaced the Pooled Cohort Equations (PCE) from 2013. The following ASCVD risk is calculated using the 2013 PCE equations:
10-year ASCVD risk from PCE 2013 equations
19.3%
Heart Failure (HF) Risk Evaluation
PREVENT also estimates the 10-year risk of a first heart failure hospitalization among patients without any history of ASCVD or heart failure:
10-year risk of heart failure hospitalization:
4.8%
10-year risk in a similar patient with optimal risk factors :
1.2%
Total Cardiovascular Disease (CVD) Risk Evaluation
Total CVD is a composite risk of a first ASCVD event or heart failure hospitalization.
10-year risk of total CVD (ASCVD or HF):
10.5%
10-year risk in a similar patient with optimal risk factors :
2.6%
About This Calculator
This validated calculator uses the PREVENT 2023 equations to estimate a patient's 10-year risk of a first ASCVD (atherosclerotic cardiovascular disease) event or heart failure hospitalization in adults aged 30 to 79 years without pre-existing cardiovascular disease.1 Most guidelines consider patients to be at an "elevated" ASCVD risk if the ASCVD risk estimate is ≥ 7.5%.
The PREVENT 2023 equations were designed to replace the 2013 Pooled Cohort Equations (PCE).2 This calculator has been validated to ensure identical risk estimates to the ACC/AHA Excel and website implementations of the PREVENT and PCE equations.
Definitions of ASCVD and Other Events
The PREVENT 2023 equations estimate the risk of a first cardiovascular event in the next 10 years based on patient-specific risk factors among patients who have never had one of these events in the past. These events include:
- ASCVD (atherosclerotic cardiovascular disease): myocardial infarction (heart attack), fatal coronary heart disease, or stroke (ischemic or hemorrhagic)
- CHD (coronary heart disease): myocardial infarction (heart attack)
- Stroke: an ischemic or hemorrhagic stroke
- HF (heart failure): hospitalization for heart failure
- Total CVD (cardiovascular disease): composite of any ASCVD event (CHD or stroke) and HF event
Because a patient can develop more than one cardiovascular event over 10 years (e.g., both HF hospitalization and myocardial infarction), the composite outcomes of total CVD and ASCVD may be less than the sum of their individual components.
Comparison of PREVENT 2023 vs. PCE 2013
Compared with PCE, PREVENT incorporates additional risk factors (eGFR, BMI, statin use) and optional predictors (urine albumin-creatinine ratio, hemoglobin A1C, and social deprivation index). Race was removed as a predictor, reflecting the consensus that it is a social construct and should not be used in risk estimation.
PREVENT has a slight improvement in predictive ability compared to PCE. Based on the published ΔC-statistic differences, PREVENT correctly discriminates between event and non-event patients about 6 more times per 1,000 comparisons.
On average, PCE estimates are inflated compared to PREVENT estimates. As an example, an ASCVD risk of 7.5% with PCE equates to a PREVENT ASCVD risk of 4.9% (men) and 3.7% (women). For comparison purposes, this calculator includes the ASCVD estimate in conjunction with the PREVENT risk estimate.
Risk Factors Incorporated in PREVENT 2023
PREVENT was developed using risk factors that are widely available in large cohort studies and in routine clinical practice. Other risk factors or biomarkers (e.g., high-sensitivity C-reactive protein, Lp(a), coronary artery calcium, family history of early heart disease, physical activity, dietary patterns, etc.) may inform risk assessment but are not part of the PREVENT model.
Each risk factor has a range of valid values. Values outside of these ranges will be changed to the nearest valid value by the calculator; however, the risk estimate will be less accurate. These risk factors include:
- Age (between 30 and 79 years old)
- Gender (male/female)
- Total cholesterol (between 130 and 320 mg/dL)
- HDL cholesterol (between 20 and 100 mg/dL)
- Systolic blood pressure (between 90 and 200 mmHg)
- Estimated glomerular filtration rate (eGFR) (between 15 and 150 mL/min/1.73 m2) as measured by CKD-EPI 2021 3
- Body mass index (BMI) (between 18.5 and 39.9 kg/m2)
- History of diabetes (yes/no)
- Current smoking status (yes/no)
- Taking an antihypertensive medication (yes/no)
- Taking a statin medication (yes/no)
PREVENT also includes three risk factors that are optional. Inclusion of these optional factors improves risk prediction but may not be readily available in all patients:
- Urine albumin-creatinine ratio (between 0.1 and 25,000 mg/g)
- Hemoglobin A1C (between 3% and 15%)
- Social deprivation index (between 1 and 10)
Social Deprivation Index (SDI)
Epidemiologic data have demonstrated the association of socioeconomic status and the risk of cardiovascular disease. To measure socioeconomic status, PREVENT uses the social deprivation index based on ZIP code.4 The following factors are incorporated into the SDI score:
- Percent of population below federal poverty level
- Percent of population older than 25 years with less than 12 years of education
- Percent of population 16-64 years old who are not employed
- Percent of households in renter-occupied housing units
- Percent of households in crowded housing units
- Percent single parent families with dependents less than 18 years old
- Percent of households with no vehicle
These seven factors are combined to create a single SDI score (1-10), indicating a percentile of a ZIP code versus all other ZIP codes in the survey data. An SDI score of 1 indicates affluent or well-resourced communities, whereas a score of 10 indicates underserved or high deprivation communities. The PREVENT score incorporates the SDI score based on a value of a low SDI (1-3), moderate SDI (4-6), or high SDI (7-10).
References and Additional Reading
- Khan SS, Matsushita K, Sang Y, et al. Development and Validation of the American Heart Association's PREVENT Equations. Circulation. 2024;149(6):430-449. doi:10.1161/CIRCULATIONAHA.123.067626
- Khan SS, Coresh J, Pencina MJ, et al. Novel Prediction Equations for Absolute Risk Assessment of Total Cardiovascular Disease Incorporating Cardiovascular-Kidney-Metabolic Health: A Scientific Statement From the American Heart Association. Circulation. 2023;148(24):1982-2004. doi:10.1161/CIR.0000000000001191
- Inker LA, Eneanya ND, Coresh J, et al. New Creatinine- and Cystatin C-Based Equations to Estimate GFR without Race. N Engl J Med. 2021;385(19):1737-1749. doi:10.1056/NEJMoa2102953
- Robert Graham Center. Social Deprivation Index (SDI), The 2019 SDI at the ZCTA level (derived from the 2015-2019 ACS 5-Year Summary Files). https://www.graham-center.org/maps-data-tools/social-deprivation-index.html.