PREVENT 2023 10-year CVD Risk (race-free)

PREVENT 2023 10-year CVD Risk (race-free) - a deterministic tool in Sophie Well's Clinical Scoring & Risk group.

Open the PREVENT 2023 10-year CVD Risk (race-free) → Runs in your browser. No signup, no tracking.

What this is

Calculate the 10-year total cardiovascular-disease risk using the American Heart Association PREVENT equations (2023) - the race-free successor to the Pooled Cohort Equations. PREVENT takes age, sex, total cholesterol, HDL, systolic blood pressure, BMI, and eGFR and returns the 10-year probability of a first hard cardiovascular event combining MI, stroke, and heart-failure outcomes. Sophie Well runs the base total-CVD equation only and does not include the optional UACR, HbA1c, or social-deprivation extensions. Source: Khan SS et al. Circulation 2024;149:430-449.

When to use it

Use this in primary care for an adult age 30-79 without known atherosclerotic cardiovascular disease to anchor a shared decision about statin therapy, antihypertensive intensification, and lifestyle intervention. PREVENT is calibrated for a contemporary US population and replaces race as an input - the variable that drove much of the equity criticism of the older PCE - while adding heart-failure outcomes to the composite. It is not a treatment threshold; the 2024 ACC/AHA primary-prevention guidance pairs PREVENT output with risk-enhancing factors, coronary artery calcium scoring, and patient preference before prescribing.

References

Khan SS, et al. Development and Validation of the AHA PREVENT Equations. Circulation. 2024;149(6):430-449. PREVENT is race-FREE; differs from PCE on this point. Base 10-yr total CVD equation only (no statin / antihypertensive use, UACR, HbA1c, or SDI terms).

Worked example: PREVENT 10-year total CVD risk lands in the borderline / low band for a healthy 55-year-old.

Sophie Well is a reference and educational tool. Not medical, legal, or financial advice. Does not replace clinician judgment, professional billing review, or legal counsel.

Built by Clay Good. Source on GitHub.