Abstract
The American Heart Association (AHA) recently introduced a new acronym, CKM (cardiovascularkidney-metabolic) syndrome, to highlight the significant overlap between cardiovascular, renal, and metabolic diseases. 1 Metabolic diseases, including obesity, type 2 diabetes, and chronic kidney disease (CKD), can damage nearly every organ system, including the heart. Individually, each of these conditions is associated with substantial morbidity and mortality. Furthermore, the conditions frequently coexist, multiplying the odds of developing cardiovascular diseases (CVDs), including heart failure (HF), atrial fibrillation, coronary artery disease, stroke, and peripheral artery disease.
Cardiovascular Risk Assessment
Cardiovascular risk calculators play a pivotal role in clinical practice by providing a systematic and evidence-based method for assessing an individual’s risk of developing heart disease. These tools enable health care professionals to make informed decisions about preventive strategies, personalized treatment plans, and lifestyle interventions. By translating complex clinical and social data into a tangible risk estimate, risk calculators empower individuals to actively participate in their health care and make informed choices regarding lifestyle modifications, medication use, and overall cardiovascular health management.
The integration of risk calculators into routine clinical practice helps bridge the gap between evidence-based guidelines and individualized patient care, fostering a more personalized and proactive approach to CVD prevention. This aligns with the broader shift toward precision medicine, where health care interventions are tailored to an individual’s unique risk profile, ultimately leading to more effective and targeted preventive measures.
As the landscape of cardiovascular risk assessment continues to evolve with advancements in technology and research, these calculators remain indispensable in the broader context of preventive medicine, emphasizing the importance of early identification and management of cardiovascular risk factors in improving overall public health.
Pooled Cohort Equations
The inception of the pooled cohort equations (PCEs) for atherosclerotic CVD risk involved a rigorous and evidence-based process led by the AHA and the American College of Cardiology (ACC). Introduced in 2013, the PCEs were created to provide a more contemporary and personalized approach to estimating an individual’s 10-year risk of atherosclerotic CVD (ASCVD) for individuals ages 40 to 79.
The equations were derived from data obtained from several major cohort studies, including the Framingham Heart Study, Atherosclerosis Risk in Communities Study, Cardiovascular Health Study, and Coronary Artery Risk Development in Young Adults Study. 2 The development process involved statistical modeling and analysis to identify key risk factors contributing to ASCVD. The final equations incorporated factors such as age, sex, race, total cholesterol, high-density lipoprotein cholesterol, systolic blood pressure, diabetes status, and smoking history. By leveraging data from these large cohorts, the PCEs sought to enhance the accuracy and relevance of cardiovascular risk assessment. 2
Improving the PCE Model
The PCEs have proven to be a tremendous asset in patient care, as evidenced by their widespread integration into clinical practice guidelines, yet the landscape of cardiometabolic care has changed substantially over the past decade. Tobacco use continues to decline, use of antihypertensive agents is more widespread, and lipid goals recommended by the guidelines have become increasingly more aggressive. 3 The changing prevalence of these cardiovascular risk factors in today’s population suggests that the cohort that the PCEs were studied in may no longer be representative of today’s patient, resulting in an overestimation of ASCVD risk. An additional limitation of the PCEs is the inclusion of only White and Black races.
Today, there is a desire for new risk markers of CVD to be incorporated into a risk assessment tool to further enhance its accuracy. Epidemiological evidence substantiates strong connections between CKM risk markers, such as CKD and diabetes, and the occurrence of total CVD and specific subtypes, including ASCVD and HF. 4
The PREVENT Calculator
Given the rising prevalence of poor CKM health among US citizens, the incorporation of metabolic and CKD markers into a new risk assessment tool, PREVENT, plays a role in optimizing its accuracy and relevance to today’s population. The base model of the PREVENT tool includes estimated glomerular filtration rate, and optional add-ons to the model include urine albumin-creatinine ratio (UACR), A1C, and social risk.
Features of the PREVENT Risk Calculator include the following.
CKM Health Markers
A number of epidemiologic studies have elucidated the relationship between CKD and CVD. Alarmingly, the association is so strong that individuals with CKD are more likely to face mortality from a cardiovascular event than from worsening kidney function. 5 Estimated glomerular filtration rate (eGFR) is a parameter that is widely available in clinical settings and has been newly included as a predictor in the base model of the PREVENT risk assessment. Inclusion of eGFR aligns with the holistic approach to CKM health as a broader framework for prevention given novel therapies that simultaneously target cardiovascular and kidney outcomes.
In an effort to capture the additional CVD risk posed by dysglycemia, A1C can be used as an input into the model. Because A1C is not routinely assessed for those without diabetes, the PREVENT tool was developed with this feature as an optional input to be used for those with and without diabetes when these data are available. Additionally, a robust association between elevated UACR and CVD led to the inclusion of UACR as a novel predictor. However, a similar rationale was applied to UACR as A1C in that it is considered an optional parameter because UACR screening rates are low despite recommendation by the American Diabetes Association and Kidney Disease Improving Global Outcomes for annual albuminuria screening in those with diabetes or CKD. 2 In the AHA’s statistical analysis of PREVENT, these add-on CKM features improved calibration among individuals with CKD to a statistically significant degree. 2 A1C and UACR should be included in the risk calculation when the data are clinically indicated and available because their utility may enhance the tool’s discrimination of CVD risk.
HF
The rise in mortality rates among CVD subtypes has been notably more pronounced for HF compared to heart disease of atherosclerotic origin. HF stands as the predominant cause of hospitalization among individuals older than 65, and its prevalence is steadily increasing across all age groups. 6 The concerning trends in mortality, hospitalizations, prevalence, and incidence of HF underscore the imperative to prioritize primary prevention efforts. Expanding the PREVENT risk assessment tool to include HF is particularly beneficial specifically in populations with poor CKM health, among whom risk for HF is relatively greater than risk for ASCVD. 5
Race-Free Equations
In developing the PREVENT models, the AHA removed race as an input to the calculator. This decision aligns with the growing consensus in medicine to eliminate the use of race from clinical algorithms, acknowledging that racism, rather than race itself, shapes societal and individual experiences, correlates with adverse social determinants of health (SDOH), and significantly contributes to unfavorable CVD outcomes.
To capture the influence of SDOH on cardiovascular outcomes, the PREVENT calculator includes a social deprivation index (SDI) as an add-on input. The SDI provides a zip-code-specific surrogate measure of SDOH and considers a variety of characteristics, including percentage living in poverty, percentage with <12 years of formal education, percentage of single-parent households, percentage living in rental properties, percentage of households without a car, and percentage of unemployed adults <65 years old. 2 Although this is a crucial first step in the effort to represent the impact of SDOH, it is important to recognize that these place-based measures do not necessarily encapsulate an individual’s experiences with key social drivers.
Early Intervention and Lifetime Risk Assessment
The PREVENT equations allow for accurate and precise estimations of both short-term and long-term CVD risk among adults ages 30 to 79. Whereas the PCEs are rated for 10-year risk assessment, PREVENT offers both 10-year and 30-year assessments. 2 This approach broadens the scope of prevention efforts, facilitating interventions across a wider age range and enabling earlier interventions in younger adults.
Despite the generally low absolute 10-year or short-term risk in young adults, even in the presence of moderately elevated risk factor levels or established CVD risk factors, such as hypertension and diabetes, there is a substantial risk over the long term. Relying solely on shortterm risk assessments may falsely reassure individuals with low short-term risk who actually have a high lifetime risk. 3 Consequently, incorporating lifetime risk considerations can guide more intensive modification of risk factors at an earlier stage in life, potentially maximizing the efficacy of preventive strategies.
Conclusion
The AHA’s PCEs and the newly emerged PREVENT Risk Calculator represent 2 approaches to cardiovascular risk assessment, each with slightly different considerations. The AHA’s PCEs have been widely integrated into clinical practice, providing a straightforward and well-established tool for estimating 10-year cardiovascular risk. However, its reliance on historical data and limited inclusion of additional risk factors may hinder its ability to adapt to evolving health landscapes.
In contrast, the PREVENT Risk Calculator brings a contemporary perspective to cardiovascular risk that is not only more equitable but also incorporates a more extensive set of risk factors. In particular, the inclusion of parameters that reflect CKM health offers a more comprehensive risk assessment given the complex interplay of obesity, diabetes, CKD, and cardiovascular health.
Although refinement of quantitative cardiovascular risk assessment will continue to be an evolving process, PREVENT provides an important follow-up to the PCEs that acknowledges the importance of CVD prevention across the spectrum of CKM. The base model calculator can be accessed on the AHA website at https://professional.heart.org/en/guidelines-andstatements/prevent-calculator. Add-on models incorporating A1C, UACR, and social risk are currently under development. ■
Footnotes
Acknowledgements
The author would like to acknowledge the valuable contributions of Haley Frey, PharmD, for drafting the article.
Declaration of Conflicting Interests
The authors declare having no professional or financial association or interest in an entity, product, or service related to the content or development of this article.
Funding
The authors declare having received no specific grant from a funding agency in the public, commercial, or not-for-profit sectors related to the content or development of this article.
Debra J. Reid, PharmD, BCACP, BC-ADM, CDCES, FADCES, is with Northeastern University in Boston, MA.