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CardiologyASCVD

AHA PREVENT-ASCVD Risk Calculator

Estimate 10-year and age-eligible 30-year risk of a first ASCVD event with the corrected AHA PREVENT base equations.

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QuickMedCalc is developed and maintained by an independent developer. Medical content is not independently reviewed by a physician.

Formula and medical content are based on the references listed on this page. See sources, About, and Sources and Review Process.

For a clinician-reviewed primary-prevention discussion

ASCVD means atherosclerotic cardiovascular disease: disease caused by plaque in arteries that can lead to myocardial infarction or stroke. Enter current measurements and explicitly complete every selector. The result estimates risk in a population model; it does not inspect arteries, diagnose disease, or tell an individual which test or treatment to use.

Model population and measurements

PREVENT is a primary-prevention model for adults without established cardiovascular disease or heart failure.

Select the published female or male coefficient set; PREVENT does not use race.

years

Whole completed years, 30–79. The 30-year equation is available only through age 59.

mg/dL

Current total cholesterol, 130–320 mg/dL, from a clinician-reviewed lipid panel.

mg/dL

Current HDL cholesterol, 20–100 mg/dL, from the same assessment period.

mmHg

Current systolic blood pressure, 90–200 mmHg. Use a representative clinical measurement.

mL/min/1.73 m²

Current estimated glomerular filtration rate, 15–140 mL/min/1.73 m².

Current clinical factors

Use actual, up-to-date clinical information from the current assessment. Changing blood pressure, cholesterol, treatment, statin, smoking, or other inputs to create a hypothetical before-and-after result does not estimate the causal benefit of treatment or the expected change in risk.

Select Yes when antihypertensive treatment is currently used.

Select Yes when statin therapy is currently used; this is a model predictor, not a recommendation.

Use the documented current diabetes status from the clinical assessment.

PREVENT defines current smoking as cigarette use within the past 30 days.

About

The corrected AHA PREVENT-ASCVD base equations estimate the probability of a first atherosclerotic cardiovascular disease event—fatal or nonfatal myocardial infarction or stroke—over 10 years and, when age-eligible, 30 years. They are sex-specific, race-free population models developed from contemporary U.S. cohorts, not a diagnosis or a certainty for one person. [1, 2]

This page implements only the corrected ASCVD base equations for adults ages 30–79 without established cardiovascular disease or heart failure. It does not calculate PREVENT-CVD, PREVENT-HF, optional UACR, HbA1c, or social-deprivation models, PREVENT-Age, a 30-year PREVENT-CVD percentile, or treatment effect. [3, 4, 5]

The 10-year model is available from ages 30–79; the 30-year model is limited to ages 30–59. A percentage describes outcomes observed in people with similar modeled characteristics. It cannot inspect arteries, detect subclinical plaque or a prior silent event, or determine an individual future. [1, 5]

Formula

Risk (%) = 100 × logistic(sex- and time-horizon-specific linear predictor). The page uses the formally corrected coefficient tables. [1, 2]
Base predictors are age, non-HDL cholesterol, HDL cholesterol, systolic blood pressure, diabetes, current cigarette smoking, eGFR, current blood-pressure treatment, current statin use, and the published interaction and spline terms. [1]
non-HDL-C = total cholesterol − HDL cholesterol. Cholesterol values entered in mg/dL are converted internally with 1 mg/dL = 0.02586 mmol/L before the published equation terms are evaluated. [1, 5]
Systolic blood pressure uses a spline at 110 mmHg; eGFR uses a spline at 60 mL/min/1.73 m². Internal arithmetic remains unrounded and final percentages are displayed to one decimal place. [1, 2]
BMI is not a predictor in the published ASCVD-specific base equations. It appears in other PREVENT outcome models and in the full AHA tool context, but it does not enter this page’s calculation. [1, 3]

Interpretation

What the percentage represents

The result estimates how often a first ASCVD event occurred over the stated time horizon among people with similar modeled characteristics. A 3.6% estimate is not a predetermined 3.6% fate for one person. Both underestimation and overestimation are possible, and the model cannot diagnose myocardial infarction, stroke, coronary disease, plaque, or heart failure. Use current, clinician-verified values from the same assessment period. [1, 3]

Published worked example

In the original PREVENT report, a 50-year-old woman with total cholesterol 240 mg/dL, HDL-C 55 mg/dL, treated systolic blood pressure 160 mmHg, no statin use, no diabetes, no current smoking, and eGFR 90 mL/min/1.73 m² had an ASCVD base estimate of about 3.6% at 10 years and 20% at 30 years. This page reproduces 3.6% and 19.9% before the paper’s whole-number rounding. It is an equation check, not a normal reference patient. [1, 2]

2026 dyslipidemia categories are conditional context

Static 2026 PREVENT-ASCVD risk-category context
10-year PREVENT-ASCVD estimateStatic guideline term
<3%Low
3% to <5%Borderline
5% to <10%Intermediate
≥10%High

The 2026 U.S. dyslipidemia guideline applies these terms in a specific lipid-management context: adults without known ASCVD or subclinical atherosclerosis and with LDL-C 70–189 mg/dL. This page does not collect LDL-C or establish whether subclinical atherosclerosis is absent, so it does not dynamically label a submitted result or turn the percentage into a medication, nonstatin therapy, or coronary calcium recommendation. The static context can support clinician–patient shared decision-making only after the applicable pathway is established. [7, 8, 9]

Base ASCVD versus other cardiovascular tools

PREVENT-ASCVD predicts a first ASCVD event. The full AHA PREVENT tool can also calculate total CVD and heart-failure outcomes and can use optional UACR, HbA1c, or social-deprivation inputs. The historical Framingham General CVD calculator uses different predictors, endpoints, populations, and calibration. Its percentage is not interchangeable with this result. The full AHA tool also provides PREVENT-Age and a 30-year PREVENT-CVD percentile; neither can be derived from this page’s ASCVD percentage. [4, 5]

Limits and appropriate use

PREVENT was developed from U.S. data. A 2026 multinational validation included 6,422,714 people across 44 observational cohorts and 18 randomized trials and found generally useful performance, but calibration varied by region. ASCVD evidence from Asia and other underrepresented regions was more limited, so the study does not prove identical accuracy in every country, health system, population, or person. This page cannot perform local recalibration. [10]

Inputs used by this ASCVD base model

InputMeaning on this pageTechnical range or state
Sex coefficientThe published female or male coefficient set; it does not infer gender identity, chromosomes, hormone status, or another coefficient.Female or male set
AgeCompleted years at the current assessment.30–79 years
Total cholesterol and HDL-CCurrent reliable values from the same assessment period; non-HDL-C is calculated as total cholesterol minus HDL-C.TC 130–320; HDL-C 20–100 mg/dL
Systolic blood pressureA representative current systolic measurement.90–200 mmHg
eGFRA current clinically reported estimate; this page does not calculate eGFR from creatinine.15–140 mL/min/1.73 m²
Current BP treatmentWhether antihypertensive medicine is currently used.Yes or No
Current statin useWhether a statin is currently used; this is not a treatment recommendation.Yes or No
DiabetesThe documented diabetes-history input used by the model.Yes or No
Current smokingCigarette use within the previous 30 days; it does not quantify pack-years or all nicotine exposure.Yes or No

These limits are the implemented model’s technical input ranges, not healthy ranges, treatment targets, diagnoses, or a reason to substitute the nearest boundary. This calculator rejects an out-of-range value instead of silently capping it. [5, 6]

Model identity, correction, and reproducibility

The original methods report describes the endpoint, cohorts, predictors, splines, interactions, and sex-specific logistic models. A separate formal correction supplies corrected equation material; this implementation identifies that corrected model explicitly and retains full precision until display. The two publications are listed separately so the correction is not hidden inside the original citation. [1, 2]

What the complete AHA tool does that this page does not

The AHA PREVENT family has separate outcome equations for total cardiovascular disease, ASCVD, and heart failure, plus optional predictors in expanded models. The current official tool can also present PREVENT-Age and a 30-year PREVENT-CVD percentile. Those outputs require their own definitions and models. This page does not treat missing UACR, HbA1c, or ZIP-code/SDI data as zero and does not derive any of those outputs from the ASCVD base percentage. [3, 4, 5]

Different guidelines use different PREVENT outcomes

The 2026 U.S. dyslipidemia pathway uses PREVENT-ASCVD in its defined primary-prevention context. By contrast, the 2025 U.S. blood-pressure guideline’s 7.5% decision threshold refers to 10-year total CVD from PREVENT-CVD, not this page’s ASCVD-specific output. The two endpoints are not interchangeable, and this page does not apply that 7.5% threshold. [6, 7, 8]

Why the selectors are not a treatment simulator

Blood-pressure treatment, statin use, smoking, diabetes, and measurements must describe the actual current assessment. Changing a selector to create a hypothetical second result does not estimate the causal effect of starting or stopping therapy, stopping smoking, or changing a laboratory value. The difference between two runs is not treatment benefit and cannot select a medicine, dose, coronary calcium scan, or care plan. [3, 9]

Calibration and individual limitations

Even a well-performing population model can overestimate or underestimate absolute risk for a particular person or setting. The multinational validation supports transportability across many cohorts while also documenting regional variation and thinner evidence in some regions. Interpretation still depends on local calibration, current measurements, known or subclinical disease, LDL-C and other risk enhancers, competing illness, and patient preferences. [9, 10]

References

  1. 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. PMID 37947085. PMCID PMC10910659. DOI 10.1161/CIRCULATIONAHA.123.067626.
  2. Correction to: Development and Validation of the American Heart Association’s PREVENT Equations. Circulation. 2024;149(11):e956. PMID 38466792. DOI 10.1161/CIR.0000000000001230.
  3. 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. PMID 37947094. DOI 10.1161/CIR.0000000000001191.
  4. American Heart Association. Predicting Risk of cardiovascular disease EVENTs (PREVENT) Calculator. Official model and implementation information.
  5. American Heart Association. PREVENT Equations Quickstart Guide. 2026.
  6. American Heart Association. PREVENT Equations Frequently Asked Questions. Current guideline-use FAQ.
  7. Blumenthal RS, Morris PB, Gaudino M, et al. 2026 ACC/AHA/AACVPR/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA Guideline on the Management of Dyslipidemia. Circulation. 2026;153:e1154–e1276. DOI 10.1161/CIR.0000000000001423.
  8. Correction to: 2026 ACC/AHA/AACVPR/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA Guideline on the Management of Dyslipidemia. Circulation. 2026. PMID 42330109. DOI 10.1161/CIR.0000000000001457.
  9. American Heart Association. Top Take-Home Messages for Clinicians: Using PREVENT-ASCVD Equations for Risk-Based Lipid Management. 2026.
  10. Neuen BL, Major RW, Grams ME, et al. Multinational validation of the PREVENT and SCORE2 cardiovascular risk equations across 6.4 million individuals. Nature Medicine. 2026. PMID 42086979. DOI 10.1038/s41591-026-04437-z.

FAQ

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Disclaimer

Educational and informational reference only. Not intended to replace professional medical advice, diagnosis, treatment, or independent verification.