Artificial Intelligence in Cardiovascular Disease Prevention: Is it Ready for Prime Time?

PURPOSE OF REVIEW: This review evaluates how Artificial Intelligence (AI) enhances atherosclerotic cardiovascular disease (ASCVD) risk assessment, allows for opportunistic screening, and improves adherence to guidelines through the analysis of unstructured clinical data and patient-generated data. Additionally, it discusses strategies for integrating AI into clinical practice in preventive cardiology. RECENT FINDINGS: AI models have shown superior performance in personalized ASCVD risk evaluations compared to traditional risk scores. These models now support automated detection of ASCVD risk markers, including coronary artery calcium (CAC), across various imaging modalities such as dedicated ECG-gated CT scans, chest X-rays, mammograms, coronary angiography, and non-gated chest CT scans. Moreover, large language model (LLM) pipelines are effective in identifying and addressing gaps and disparities in ASCVD preventive care, and can also enhance patient education. AI applications are proving invaluable in preventing and managing ASCVD and are primed for clinical use, provided they are implemented within well-regulated, iterative clinical pathways.

Inequities in atherosclerotic cardiovascular disease prevention.

Atherosclerotic cardiovascular (CV) disease (ASCVD) prevention encompasses interventions across the lifecourse: from primordial to primary and secondary prevention. Primordial prevention begins in childhood and involves the promotion of ideal CV health (CVH) via optimizing physical activity, body mass index, blood glucose levels, total cholesterol levels, blood pressure, and sleep while minimizing tobacco use. Primary and secondary prevention of ASCVD thereafter centers around mitigating ASCVD risk factors via medical therapy and lifestyle interventions. Disparities in optimal preventive efforts exist among historically marginalized groups in each of these three prongs of ASCVD prevention. Children and adults with a high burden of social determinants of health also face inequity in preventive measures. Inadequate screening, risk factor management and prescription of preventive therapeutics permeate the care of certain groups, especially women, Black, and Hispanic individuals in the United States. Beyond this, individuals belonging to historically marginalized groups also are much more likely to experience other ASCVD risk-enhancing factors, placing them at higher risk for ASCVD over their lifetime. These disparities translate to worse outcomes, with higher rates of ASCVD and CV mortality among these groups. Possible solutions to promoting equity involve community-based youth lifestyle interventions, improved risk-factor screening, and increasing accessibility to healthcare resources and novel preventive diagnostics and therapeutics.

Association of Coronary Artery Calcium Detected by Routine Ungated CT Imaging With Cardiovascular Outcomes.

BACKGROUND: Coronary artery calcium (CAC) is a strong predictor of cardiovascular events across all racial and ethnic groups. CAC can be quantified on nonelectrocardiography (ECG)-gated computed tomography (CT) performed for other reasons, allowing for opportunistic screening for subclinical atherosclerosis. OBJECTIVES: The authors investigated whether incidental CAC quantified on routine non-ECG-gated CTs using a deep-learning (DL) algorithm provided cardiovascular risk stratification beyond traditional risk prediction methods. METHODS: Incidental CAC was quantified using a DL algorithm (DL-CAC) on non-ECG-gated chest CTs performed for routine care in all settings at a large academic medical center from 2014 to 2019. We measured the association between DL-CAC (0, 1-99, or ≥100) with all-cause death (primary outcome), and the secondary composite outcomes of death/myocardial infarction (MI)/stroke and death/MI/stroke/revascularization using Cox regression. We adjusted for age, sex, race, ethnicity, comorbidities, systolic blood pressure, lipid levels, smoking status, and antihypertensive use. Ten-year atherosclerotic cardiovascular disease risk was calculated using the pooled cohort equations. RESULTS: Of 5,678 adults without ASCVD (51% women, 18% Asian, 13% Hispanic/Latinx), 52% had DL-CAC >0. Those with DL-CAC ≥100 had an average 10-year ASCVD risk of 24%; yet, only 26% were on statins. After adjustment, patients with DL-CAC ≥100 had increased risk of death (HR: 1.51; 95% CI: 1.28-1.79), death/MI/stroke (HR: 1.57; 95% CI: 1.33-1.84), and death/MI/stroke/revascularization (HR: 1.69; 95% CI: 1.45-1.98) compared with DL-CAC = 0. CONCLUSIONS: Incidental CAC ≥100 was associated with an increased risk of all-cause death and adverse cardiovascular outcomes, beyond traditional risk factors. DL-CAC from routine non-ECG-gated CTs identifies patients at increased cardiovascular risk and holds promise as a tool for opportunistic screening to facilitate earlier intervention.

Coronary Artery Calcium Score to Refine the Use of PCSK9i in Asymptomatic Individuals: A Multicohort Study.

Background The value of coronary artery calcium (CAC) in the allocation of PCSK9i (proprotein convertase subtilisin/kexin type 9 inhibitors) among individuals without clinically evident atherosclerotic cardiovascular disease (ASCVD) is unknown for indications that do not require confirmed familial hypercholesterolemia. We aimed to assess the ability of CAC to stratify ASCVD risk under 3 non-familial hypercholesterolemia PCSK9i allocation paradigms. Methods and Results We included participants without clinically evident ASCVD from MESA (Multi-Ethnic Study of Atherosclerosis), CARDIA (Coronary Artery Risk Development in Young Adults) study, DHS (Dallas Heart Study), and HNR (Heinz Nixdorf Recall) study. Three PCSK9i eligibility scenarios were defined: a broad scenario informed only by high low-density lipoprotein cholesterol levels (N=567), a restrictive one combining higher low-density lipoprotein cholesterol levels and presence of ≥2 additional risk factors (N=127), and a high-risk scenario where individuals with subclinical organ damage or high estimated risk would be treated to achieve low-density lipoprotein cholesterol <55 mg/dL (N=471). The high-risk scenario had the highest ASCVD event rates (27.8% at 10 years). CAC=0 was observed in 35% participants in the broad scenario, 25% in the restrictive scenario, and 16% in the high-risk scenario. In all, CAC=0 was associated with the lowest incident ASCVD rates at 5 and 10 years, and CAC burden was independently associated with ASCVD events adjusting for traditional risk factors. Conclusions CAC may be used to refine the allocation of PCSK9i, potentially leading to a more conservative use if CAC=0. The value of CAC testing is greater in scenarios that use low-density lipoprotein cholesterol levels and/or traditional risk factors to define PCSK9i eligibility (CAC=0 present in 1 of 3-4 patients), whereas its prevalence is lower when allocation is informed by presence of noncoronary subclinical organ damage.

Ten things to know about ten cardiovascular disease risk factors - 2022.

The American Society for Preventive Cardiology (ASPC) "Ten things to know about ten cardiovascular disease risk factors - 2022" is a summary document regarding cardiovascular disease (CVD) risk factors. This 2022 update provides summary tables of ten things to know about 10 CVD risk factors and builds upon the foundation of prior annual versions of "Ten things to know about ten cardiovascular disease risk factors" published since 2020. This 2022 version provides the perspective of ASPC members and includes updated sentinel references (i.e., applicable guidelines and select reviews) for each CVD risk factor section. The ten CVD risk factors include unhealthful dietary intake, physical inactivity, dyslipidemia, pre-diabetes/diabetes, high blood pressure, obesity, considerations of select populations (older age, race/ethnicity, and sex differences), thrombosis (with smoking as a potential contributor to thrombosis), kidney dysfunction and genetics/familial hypercholesterolemia. Other CVD risk factors may be relevant, beyond the CVD risk factors discussed here. However, it is the intent of the ASPC "Ten things to know about ten cardiovascular disease risk factors - 2022" to provide a tabular overview of things to know about ten of the most common CVD risk factors applicable to preventive cardiology and provide ready access to applicable guidelines and sentinel reviews.