Heart Failure Risk Associated With Severity of Modifiable Heart Failure Risk Factors: The ARIC Study

Advancements in Incident Heart Failure Risk Prediction and Screening Tools

Heart failure (HF) is a major cause of mortality and morbidity in the United States that carries substantial healthcare costs. Multiple risk prediction models and strategies have been developed over the past 30 years with the aim of identifying those at high risk of developing HF and of implementing preventive therapies effectively. This review highlights recent developments in HF risk prediction tools including emerging risk factors, innovative risk prediction models, and novel screening strategies from artificial intelligence to biomarkers. These developments allow more accurate prediction, but their impact on clinical outcomes remains to be investigated. Implementation of these risk models in clinical practice is a considerable challenge, but HF risk prediction tools offer a promising opportunity to improve outcomes while maintaining value.

Cardiometabolic Co-morbidity Burden and Circulating Biomarkers in Patients With Chronic Coronary Disease in the ISCHEMIA Trials

Cardiometabolic co-morbidities, diabetes (DM), hypertension (HTN), and obesity contribute to cardiovascular disease. Circulating biomarkers facilitate prognostication for patients with cardiovascular disease. We explored the relation between cardiometabolic co-morbidity burden in patients with chronic coronary disease and biomarkers of myocardial stretch, injury, inflammation, and platelet activity. We analyzed participants from the International Study of Comparative Health Effectiveness with Medical and Invasive Approaches (ISCHEMIA) trials biorepository with plasma biomarkers (N-terminal probrain natriuretic peptide, high-sensitivity cardiac troponin T, high-sensitivity C-reactive protein, interleukin-6, soluble CD40 ligand, and growth differentiation factor-15) and clinical risk factors (hemoglobin A1c [HbA1c], systolic blood pressure [SBP], and body mass index [BMI]) at baseline. We defined cardiometabolic co-morbidities as DM, HTN, and obesity at baseline. Co-morbidity burden is characterized by the number and severity of co-morbidities. Controlled co-morbidities were defined as HbA1c <7% for those with DM, SBP <130 mm Hg for those with HTN, and BMI <30 kg/m2. Severely uncontrolled was defined as HbA1c ≥8%, SBP ≥160 mm Hg, and BMI ≥35 kg/m2. We performed linear regression analyses to examine the association between co-morbidity burden and log-transformed biomarker levels, adjusting for age, gender, estimated glomerular filtration rate controlled for hemodialysis, and left ventricular ejection fraction. A total of 752 participants (mean age 66 years, 19% women, 84% White) were included in this analysis. Self-reported Black race, current smokers, history of myocardial infarction, and heart failure had a greater cardiometabolic co-morbidity burden. The presence of ≥1 severely uncontrolled co-morbidity was associated with significantly higher baseline levels of high-sensitivity cardiac troponin T, high-sensitivity C-reactive protein, interleukin-6, and growth differentiation factor-15 than participants with no co-morbidities. In conclusion, increasing cardiometabolic co-morbidity burden in patients with chronic coronary disease is associated with higher levels of circulating biomarkers of myocardial injury and inflammation.

Development and Validation of the American Heart Association's PREVENT Equations

BACKGROUND

Multivariable equations are recommended by primary prevention guidelines to assess absolute risk of cardiovascular disease (CVD). However, current equations have several limitations. Therefore, we developed and validated the American Heart Association Predicting Risk of CVD EVENTs (PREVENT) equations among US adults 30 to 79 years of age without known CVD.

METHODS

The derivation sample included individual-level participant data from 25 data sets (N=3 281 919) between 1992 and 2017. The primary outcome was CVD (atherosclerotic CVD and heart failure). Predictors included traditional risk factors (smoking status, systolic blood pressure, cholesterol, antihypertensive or statin use, and diabetes) and estimated glomerular filtration rate. Models were sex-specific, race-free, developed on the age scale, and adjusted for competing risk of non-CVD death. Analyses were conducted in each data set and meta-analyzed. Discrimination was assessed using the Harrell C-statistic. Calibration was calculated as the slope of the observed versus predicted risk by decile. Additional equations to predict each CVD subtype (atherosclerotic CVD and heart failure) and include optional predictors (urine albumin-to-creatinine ratio and hemoglobin A1c), and social deprivation index were also developed. External validation was performed in 3 330 085 participants from 21 additional data sets.

RESULTS

Among 6 612 004 adults included, mean±SD age was 53±12 years, and 56% were women. Over a mean±SD follow-up of 4.8±3.1 years, there were 211 515 incident total CVD events. The median C-statistics in external validation for CVD were 0.794 (interquartile interval, 0.763-0.809) in female and 0.757 (0.727-0.778) in male participants. The calibration slopes were 1.03 (interquartile interval, 0.81-1.16) and 0.94 (0.81-1.13) among female and male participants, respectively. Similar estimates for discrimination and calibration were observed for atherosclerotic CVD- and heart failure-specific models. The improvement in discrimination was small but statistically significant when urine albumin-to-creatinine ratio, hemoglobin A1c, and social deprivation index were added together to the base model to total CVD (ΔC-statistic [interquartile interval] 0.004 [0.004-0.005] and 0.005 [0.004-0.007] among female and male participants, respectively). Calibration improved significantly when the urine albumin-to-creatinine ratio was added to the base model among those with marked albuminuria (>300 mg/g; 1.05 [0.84-1.20] versus 1.39 [1.14-1.65]; P=0.01).

CONCLUSIONS

PREVENT equations accurately and precisely predicted risk for incident CVD and CVD subtypes in a large, diverse, and contemporary sample of US adults by using routinely available clinical variables.

Men with erectile dysfunction (ED) should be screened for cardiovascular risk factors - Cost-benefit considerations in Swiss men

Background: Current evidence indicates that erectile dysfunction (ED) is an independent risk factor for future cardiovascular events. This study aimed to estimate the cost-effectiveness of screening and subsequent preventive treatment for cardiovascular risk factors among men newly diagnosed with ED from the Swiss healthcare system perspective. Methods: Based on known data on ED and cardiovascular disease (CVD) prevalence and incidence costs and effects of a screening intervention for cardiovascular risk including corresponding cardiovascular prevention in men with ED were calculated for the Swiss population over a period of 10 years. Results: Screening and cardiovascular prevention over a period of 10 years in Swiss men with ED of all seriousness degrees, moderate and severe ED only, or severe ED only can probably avoid 41,564, 35,627, or 21,206 acute CVD events, respectively. Number needed to screen (NNS) to prevent one acute CVD event is 30, 23, and 10, respectively. Costs for the screening intervention are expected to be covered at the seventh, the fifth, and the first year, respectively. Conclusion: Screening and intervention for cardiovascular risk factors in men suffering from ED is a cost-effective tool not only to strengthen prevention and early detection of cardiovascular diseases but also to avoid future cardiovascular events.

Preventing new-onset heart failure: Intervening at stage A

Heart failure (HF) prevention is an urgent public health need with national and global implications. Stage A HF patients do not show HF symptoms or structural heart disease but are at risk of HF development. There are no unique recommendations on detecting Stage A patients. Patients in Stage A are heterogeneous; many patients have different combinations of risk factors and, therefore, have markedly different absolute risks for HF. Comprehensive strategies to prevent HF at Stage A include intensive blood pressure lowering, adequate glycemic and lipid management, and heart-healthy behaviors (adopting Life's Essential 8). First and foremost, it is imperative to improve public awareness of HF risk factors and implement healthy lifestyle choices very early. In addition, recognize the HF risk-enhancing factors, which are nontraditional cardiovascular (CV) risk factors that identify individuals at high risk for HF (genetic susceptibility for HF, atrial fibrillation, chronic kidney disease, chronic liver disease, chronic inflammatory disease, sleep-disordered breathing, adverse pregnancy outcomes, radiation therapy, a history of cardiotoxic chemotherapy exposure, and COVID-19). Early use of biomarkers, imaging markers, and echocardiography (noninvasive measures of subclinical systolic and diastolic dysfunction) may enhance risk prediction among individuals without established CV disease and prevent chemotherapy-induced cardiomyopathy. Efforts are needed to address social determinants of HF risk for primordial HF prevention.Central illustrationPolicies developed by organizations such as the American Heart Association, American College of Cardiology, and the American Diabetes Association to reduce CV disease events must go beyond secondary prevention and encompass primordial and primary prevention.

Resolved Proteinuria May Attenuate the Risk of Heart Failure: A Nationwide Population-Based Cohort Study

Although proteinuria is a risk factor for heart failure (HF), proteinuria can be reversible or persistent. Our objective was to explore the link between changes in the proteinuria status and the risk of HF. We included participants from a Korean national health screening cohort who underwent health examinations in 2003-2004 and 2005-2006 and had no history of HF. Participants were categorized into four groups: proteinuria-free, proteinuria-resolved, proteinuria-developed, and proteinuria-persistent. The outcome of interest was the occurrence of HF. The study included 1,703,651 participants, among whom 17,543 (1.03%) were in the proteinuria-resolved group and 4585 (0.27%) were in the proteinuria-persistent group. After a median follow-up period of 14.04 years (interquartile range 14.19-15.07), HF occurred in 75,064 (4.41%) participants. A multivariable Cox proportional hazards regression analysis indicated that the proteinuria-persistent group had a higher risk of HF compared with the proteinuria-free group (hazard ratio (HR): 2.19, 95% confidence interval (CI): 2.03-2.36, p < 0.001). In a further pairwise comparison analysis, participants in the proteinuria-resolved group had a relatively low risk of HF compared with those in the proteinuria-persistent group (HR: 0.64, 95% CI: 0.58-0.70, p < 0.001). In conclusion, the risk of HF can change with alterations in the proteinuria status.

Cardiovascular-Kidney-Metabolic Health: A Presidential Advisory From the American Heart Association

Cardiovascular-kidney-metabolic health reflects the interplay among metabolic risk factors, chronic kidney disease, and the cardiovascular system and has profound impacts on morbidity and mortality. There are multisystem consequences of poor cardiovascular-kidney-metabolic health, with the most significant clinical impact being the high associated incidence of cardiovascular disease events and cardiovascular mortality. There is a high prevalence of poor cardiovascular-kidney-metabolic health in the population, with a disproportionate burden seen among those with adverse social determinants of health. However, there is also a growing number of therapeutic options that favorably affect metabolic risk factors, kidney function, or both that also have cardioprotective effects. To improve cardiovascular-kidney-metabolic health and related outcomes in the population, there is a critical need for (1) more clarity on the definition of cardiovascular-kidney-metabolic syndrome; (2) an approach to cardiovascular-kidney-metabolic staging that promotes prevention across the life course; (3) prediction algorithms that include the exposures and outcomes most relevant to cardiovascular-kidney-metabolic health; and (4) strategies for the prevention and management of cardiovascular disease in relation to cardiovascular-kidney-metabolic health that reflect harmonization across major subspecialty guidelines and emerging scientific evidence. It is also critical to incorporate considerations of social determinants of health into care models for cardiovascular-kidney-metabolic syndrome and to reduce care fragmentation by facilitating approaches for patient-centered interdisciplinary care. This presidential advisory provides guidance on the definition, staging, prediction paradigms, and holistic approaches to care for patients with cardiovascular-kidney-metabolic syndrome and details a multicomponent vision for effectively and equitably enhancing cardiovascular-kidney-metabolic health in the population.

The AHA/ACC/HFSA 2022 Heart Failure Guidelines: Changing the Focus to Heart Failure Prevention

The prevalence of heart failure (HF) in the United States (U.S.) is estimated at over 6 million adults, with the incidence continuing to increase. A large proportion of the U.S. population is also at risk of HF due to the high prevalence of established HF risk factors, such as hypertension, diabetes, and obesity. Many individuals have multiple risk factors, placing them at even higher risk. In addition, these risk factors disproportionately impact various racial and ethnic groups. Recognizing the rising health and economic burden of HF in the U.S., the 2022 American Heart Association / American College of Cardiology / Heart Failure Society of America (AHA/ACC/HFSA) Heart Failure Guideline placed a strong emphasis on prevention of HF. The purpose of this review is to highlight the role of both primary and secondary prevention in HF, as outlined by the recent guideline, and address the role of the preventive cardiology community in reducing the prevalence of HF in at-risk individuals.

The Prevalence and Risk Factors of Chronic Heart Failure in the Mongolian Population

BACKGROUND

The prevalence of heart failure in the Mongolian population is unknown. Thus, in this study, we aimed to define the prevalence of heart failure in the Mongolian population and to identify significant risk factors for heart failure among Mongolian adults.

METHODS

This population-based study included individuals 20 years and older from seven provinces as well as six districts of the capital city of Mongolia. The prevalence of heart failure was based on the European Society of Cardiology diagnostic criteria.

RESULTS

In total, 3480 participants were enrolled, of which 1345 (38.6%) participants were males, and the median age was 41.0 years (IQR 30-54 years). The overall prevalence of heart failure was 4.94%. Patients with heart failure had significantly higher body mass index, heart rate, oxygen saturation, respiratory rate, and systolic/diastolic blood pressure than patients without heart failure. In the logistic regression analysis, hypertension (OR 4.855, 95% CI 3.127-7.538), previous myocardial infarction (OR 5.117, 95% CI 3.040-9.350), and valvular heart disease (OR 3.872, 95% CI 2.112-7.099) were significantly correlated with heart failure.

CONCLUSIONS

This is the first report on the prevalence of heart failure in the Mongolian population. Among the cardiovascular diseases, hypertension, old myocardial infarction, and valvular heart disease were identified as the three foremost risk factors in the development of heart failure.