Top Things to Know: Novel Prediction Equations for Absolute Risk Assessment of Total CV Disease Incorporating Cardiovascular-Kidney-Metabolic Health

Published: November 10, 2023

  1. The American Heart Association (AHA) recently defined the construct of cardiovascular-kidney-metabolic (CKM) syndrome in response to the high prevalence of metabolic risk factors and kidney disease that disproportionately burden historically underserved populations.
  2. The recent availability of therapies that target key aspects of CKM syndrome and the need to more equitably estimate risk by incorporating social determinants of health (SDoH) in risk assessment, necessitated new risk prediction equations.
  3. This scientific statement summarizes the background, rationale, and clinical implications for newly developed sex-specific, race-free risk equations: American Heart Association Predicting Risk of CVD EVENTs (PREVENT [TM under review]).
  4. With changing prevalence of risk factors (e.g., tobacco use), secular trends in risk factor levels (e.g., declines in lipid levels in the past decade), changes in care patterns (e.g., more widespread use of a variety of anti-hypertensive therapies), the risk for incident ASCVD can be overestimated with the current Pooled Cohort Equations (PCEs).
  5. The authors reviewed the scientific evidence on risk assessment for incident CVD (and CVD subtypes), identified gaps in existing multivariable risk prediction equations, and subsequently developed a novel suite of risk prediction equations for incident CVD (and CVD subtypes).
  6. Using various data sources for model development, including electronic medical records, the equations were developed from >6 million US adults from various racial, ethnic, socioeconomic, and geographic backgrounds. Ensuring that the study populations used to derive the models match the ones in which they are intended for application (e.g., general population receiving clinical care) allowed for greater generalizability of CVD risk estimates.
  7. Current risk assessment with the Pooled Cohort does not predict heart failure risk, and only predict risk for individuals 40-79 years over a 10-year time horizon. The new equations predict someone’s likelihood of total CVD, including heart attack, stroke, and heart failure; enable risk estimates over a 10- and 30-year time period; and estimate CVD risk for adults starting at age 30.
  8. The PREVENT models newly integrate kidney function as a predictor in risk assessment for CVD and improve calibration of the models in high-risk individuals with chronic kidney disease. In addition, a suite of add-on models was developed that incorporate additional markers of kidney (UACR), metabolic (HbA1c), and social (SDI) risk, which highlight the opportunities to further personalize risk assessment and tailor risk-based recommendations for individual and combined preventive therapies.
  9. The statement reviewed the available evidence for additional cardiac biomarkers, such as high-sensitivity troponin and brain natriuretic peptide and deemed that the lack of routine clinical measurement precluded their inclusion in this iteration of risk prediction equations for the general primary prevention population. However, these biomarkers may be considered for sequential testing approaches to reclassify risk in selected patients (e.g., based on predicted risk, CKM stages).
  10. The statement details opportunities for future prevention guidelines to consider PREVENT risk estimates for absolute risk estimation and to inform risk-based prevention approaches for how clinicians should choose among various therapies. It also outlines areas for future research to assess the calibration of PREVENT among disaggregated racial and ethnic groups, to address current knowledge gaps in risk assessment and implementation, and to continue to consider novel predictors or additional outcomes in risk prediction.