How Can We Predict Cardiovascular Risk Before Disease Develops?

PREVENT combined established cardiovascular risk factors — including blood pressure, cholesterol, smoking, diabetes and treatment for hypertension or high cholesterol — with kidney function measured by estimated glomerular filtration rate (eGFR).

The models were sex-specific, did not use race as a predictor and accounted for the competing risk of death from causes other than cardiovascular disease. Additional equations incorporated urine albumin-to-creatinine ratio (UACR), HbA1c and social deprivation as optional predictors.

In external validation across more than 3.3 million adults, the equations showed good discrimination and calibration for total cardiovascular disease, with similar performance for ASCVD and heart failure.

Cardiovascular disease often develops over many years before symptoms or a clinical event occur. Estimating risk earlier can identify people who may benefit from greater attention to modifiable cardiovascular, metabolic and kidney risk factors.

For longevity medicine, this shifts the focus from responding to established disease toward identifying risk while there is still an opportunity for prevention.

A major strength of PREVENT is its integration of routinely available cardiovascular, metabolic and kidney health data within a single risk framework. This reflects the close interaction between these systems in the development of cardiovascular disease.

In clinical practice, calculated cardiovascular risk can support decisions about the intensity of preventive strategies and whether additional risk assessment may be appropriate. It should not, however, be interpreted as a diagnosis or as a prediction of exactly what will happen to an individual patient.