Risk-Based Approach for the Prediction and Prevention of Heart Failure

Metabolomic Association and Risk Prediction With Heart Failure in Older Adults

BACKGROUND

Older adults have markedly increased risks of heart failure (HF), specifically HF with preserved ejection fraction (HFpEF). Identifying novel biomarkers can help in understanding HF pathogenesis and improve at-risk population identification. This study aimed to identify metabolites associated with incident HF, HFpEF, and HF with reduced ejection fraction and examine risk prediction in older adults.

METHODS

Untargeted metabolomic profiling was performed in Black and White adults from the ARIC study (Atherosclerosis Risk in Communities) visit 5 (n=3719; mean age, 75 years). We applied Cox regressions to identify metabolites associated with incident HF and its subtypes. The metabolite risk score (MRS) was constructed and examined for associations with HF, echocardiographic measures, and HF risk prediction. Independent samples from visit 3 (n=1929; mean age, 58 years) were used for replication.

RESULTS

Sixty metabolites (hazard ratios range, 0.79-1.49; false discovery rate, <0.05) were associated with incident HF after adjusting for clinical risk factors, eGFR, and NT-proBNP (N-terminal pro-B-type natriuretic peptide). Mannonate, a hydroxy acid, was replicated (hazard ratio, 1.36 [95% CI, 1.19-1.56]) with full adjustments. MRS was associated with an 80% increased risk of HF per SD increment, and the highest MRS quartile had 8.7× the risk of developing HFpEF than the lowest quartile. High MRS was also associated with unfavorable values of cardiac structure and function. Adding MRS over clinical risk factors and NT-proBNP improved 5-year HF risk prediction C statistics from 0.817 to 0.850 (∆C, 0.033 [95% CI, 0.017-0.047]). The association between MRS and incident HF was replicated after accounting for clinical risk factors (P<0.05).

CONCLUSIONS

Novel metabolites associated with HF risk were identified, elucidating disease pathways, specifically HFpEF. An MRS was associated with HF risk and improved 5-year risk prediction in older adults, which may assist at at-risk population identification.

Proteomic prediction of incident heart failure and its main subtypes

AIM

To examine the ability of serum proteins in predicting future heart failure (HF) events, including HF with reduced or preserved ejection fraction (HFrEF or HFpEF), in relation to event time, and with or without considering established HF-associated clinical variables.

METHODS AND RESULTS

In the prospective population-based Age, Gene/Environment Susceptibility Reykjavik Study (AGES-RS), 440 individuals developed HF after their first visit with a median follow-up of 5.45 years. Among them, 167 were diagnosed with HFrEF and 188 with HFpEF. A least absolute shrinkage and selection operator regression model with non-parametric bootstrap were used to select predictors from an analysis of 4782 serum proteins, and several pre-established clinical parameters linked to HF. A subset of 8-10 distinct or overlapping serum proteins predicted different future HF outcomes, and C-statistics were used to assess discrimination, revealing proteins combined with a C-index of 0.80 for all incident HF, 0.78 and 0.80 for incident HFpEF or HFrEF, respectively. In the AGES-RS, protein panels alone encompassed the risk contained in the clinical information and improved the performance characteristics of prediction models based on N-terminal pro-B-type natriuretic peptide and clinical risk factors. Finally, the protein predictors performed particularly well close to the time of an HF event, an outcome that was replicated in the Cardiovascular Health Study.

CONCLUSION

A small number of circulating proteins accurately predicted future HF in the AGES-RS cohort of older adults, and they alone encompass the risk information found in a collection of clinical data. Incident HF events were predicted up to 8 years, with predictor performance significantly improving for events occurring less than 1 year ahead, a finding replicated in an external cohort study.

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.

Prediction models for heart failure in the community: A systematic review and meta-analysis

AIMS

Multivariable prediction models can be used to estimate risk of incident heart failure (HF) in the general population. A systematic review and meta-analysis was performed to determine the performance of models.

METHODS AND RESULTS

From inception to 3 November 2022 MEDLINE and EMBASE databases were searched for studies of multivariable models derived, validated and/or augmented for HF prediction in community-based cohorts. Discrimination measures for models with c-statistic data from ≥3 cohorts were pooled by Bayesian meta-analysis, with heterogeneity assessed through a 95% prediction interval (PI). Risk of bias was assessed using PROBAST. We included 36 studies with 59 prediction models. In meta-analysis, the Atherosclerosis Risk in Communities (ARIC) risk score (summary c-statistic 0.802, 95% confidence interval [CI] 0.707-0.883), GRaph-based Attention Model (GRAM; 0.791, 95% CI 0.677-0.885), Pooled Cohort equations to Prevent Heart Failure (PCP-HF) white men model (0.820, 95% CI 0.792-0.843), PCP-HF white women model (0.852, 95% CI 0.804-0.895), and REverse Time AttentIoN model (RETAIN; 0.839, 95% CI 0.748-0.916) had a statistically significant 95% PI and excellent discrimination performance. The ARIC risk score and PCP-HF models had significant summary discrimination among cohorts with a uniform prediction window. 77% of model results were at high risk of bias, certainty of evidence was low, and no model had a clinical impact study.

CONCLUSIONS

Prediction models for estimating risk of incident HF in the community demonstrate excellent discrimination performance. Their usefulness remains uncertain due to high risk of bias, low certainty of evidence, and absence of clinical effectiveness research.

Prognostic models for heart failure in patients with type 2 diabetes: a systematic review and meta-analysis

OBJECTIVE

To provide a systematic review, critical appraisal, assessment of performance and generalisability of all the reported prognostic models for heart failure (HF) in patients with type 2 diabetes (T2D).

METHODS

We performed a literature search in Medline, Embase, Central Register of Controlled Trials, Cochrane Database of Systematic Reviews and Scopus (from inception to July 2022) and grey literature to identify any study developing and/or validating models predicting HF applicable to patients with T2D. We extracted data on study characteristics, modelling methods and measures of performance, and we performed a random-effects meta-analysis to pool discrimination in models with multiple validation studies. We also performed a descriptive synthesis of calibration and we assessed the risk of bias and certainty of evidence (high, moderate, low).

RESULTS

Fifty-five studies reporting on 58 models were identified: (1) models developed in patients with T2D for HF prediction (n=43), (2) models predicting HF developed in non-diabetic cohorts and externally validated in patients with T2D (n=3), and (3) models originally predicting a different outcome and externally validated for HF (n=12). RECODe (C-statistic=0.75 95% CI (0.72, 0.78), 95% prediction interval (PI) (0.68, 0.81); high certainty), TRS-HFDM (C-statistic=0.75 95% CI (0.69, 0.81), 95% PI (0.58, 0.87); low certainty) and WATCH-DM (C-statistic=0.70 95% CI (0.67, 0.73), 95% PI (0.63, 0.76); moderate certainty) showed the best performance. QDiabetes-HF demonstrated also good discrimination but was externally validated only once and not meta-analysed.

CONCLUSIONS

Among the prognostic models identified, four models showed promising performance and, thus, could be implemented in current clinical practice.

Pregnancy-Induced Hypertensive Disorder and Risks of Future Ischemic and Nonischemic Heart Failure

BACKGROUND

Although adverse pregnancy outcomes are associated with an increased risk of cardiovascular disease, studies on timing and subtypes of heart failure after a hypertensive pregnancy are lacking.

OBJECTIVES

The goal of this study was to assess the association between pregnancy-induced hypertensive disorder and risk of heart failure, according to ischemic and nonischemic subtypes, and the impact of disease characteristics and the timing of heart failure risks.

METHODS

This was a population-based matched cohort study, comprising all primiparous women without a history of cardiovascular disease included in the Swedish Medical Birth Register between 1988 and 2019. Women with pregnancy-induced hypertensive disorder were matched with women with normotensive pregnancies. Through linkage with health care registers, all women were followed up for incident heart failure, classified as ischemic or nonischemic.

RESULTS

In total, 79,334 women with pregnancy-induced hypertensive disorder were matched with 396,531 women with normotensive pregnancies. During a median follow-up of 13 years, rates of all heart failure subtypes were more common among women with pregnancy-induced hypertensive disorder. Compared with women with normotensive pregnancies, adjusted HRs (aHRs) with 95% CIs were as follows: heart failure overall, aHR: 1.70 (95% CI: 1.51-1.91); ischemic heart failure, aHR: 2.28 (95% CI: 1.74-2.98); and nonischemic heart failure, aHR: 1.60 (95% CI: 1.40-1.83). Disease characteristics indicating severe hypertensive disorder were associated with higher heart failure rates, and rates were highest within the first years after the hypertensive pregnancy but remained significantly increased thereafter.

CONCLUSIONS

Pregnancy-induced hypertensive disorder is associated with an increased short-term and long-term risk of incident ischemic and nonischemic heart failure. Disease characteristics indicating more severe forms of pregnancy-induced hypertensive disorder amplify the heart failure risks.

Association Between Electrocardiographic Age and Cardiovascular Events in Community Settings: The Framingham Heart Study

BACKGROUND

Deep neural networks have been used to estimate age from ECGs, the electrocardiographic age (ECG-age), which predicts adverse outcomes. However, this prediction ability has been restricted to clinical settings or relatively short periods. We hypothesized that ECG-age is associated with death and cardiovascular outcomes in the long-standing community-based FHS (Framingham Heart Study).

METHODS

We tested the association of ECG-age with chronological age in the FHS cohorts in ECGs from 1986 to 2021. We calculated the gap between chronological and ECG-age (Δage) and classified individuals as having normal, accelerated, or decelerated aging, if Δage was within, higher, or lower than the mean absolute error of the model, respectively. We assessed the associations of Δage, accelerated and decelerated aging with death or cardiovascular outcomes (atrial fibrillation, myocardial infarction, and heart failure) using Cox proportional hazards models adjusted for age, sex, and clinical factors.

RESULTS

The study population included 9877 FHS participants (mean age, 55±13 years; 54.9% women) with 34 948 ECGs. ECG-age was correlated to chronological age (r=0.81; mean absolute error, 9±7 years). After 17±8 years of follow-up, every 10-year increase of Δage was associated with 18% increase in all-cause mortality (hazard ratio [HR], 1.18 [95% CI, 1.12-1.23]), 23% increase in atrial fibrillation risk (HR, 1.23 [95% CI, 1.17-1.29]), 14% increase in myocardial infarction risk (HR, 1.14 [95% CI, 1.05-1.23]), and 40% increase in heart failure risk (HR, 1.40 [95% CI, 1.30-1.52]), in multivariable models. In addition, accelerated aging was associated with a 28% increase in all-cause mortality (HR, 1.28 [95% CI, 1.14-1.45]), whereas decelerated aging was associated with a 16% decrease (HR, 0.84 [95% CI, 0.74-0.95]).

CONCLUSIONS

ECG-age was highly correlated with chronological age in FHS. The difference between ECG-age and chronological age was associated with death, myocardial infarction, atrial fibrillation, and heart failure. Given the wide availability and low cost of ECG, ECG-age could be a scalable biomarker of cardiovascular risk.

Blood pressure per the 2017 ACC/AHA and 2018 ESC/ESH guidelines and heart failure risk: the Suita Study

Hypertension is a significant risk factor for heart failure (HF). Since hypertension definition varies across guidelines, identifying blood pressure (BP) categories that should be targeted to prevent HF is required. We, therefore, investigated the association between hypertension per the 2017 American College of Cardiology/American Heart Association (ACC/AHA) and 2018 European Society of Cardiology/European Society of Hypertension (ESC/ESH) guidelines and HF risk. This prospective cohort study included randomly selected 2809 urban Japanese people from the Suita Study. Cox regression was used to assess HF risk, in the form of hazard ratios (HRs) and 95% confidence intervals (95% CIs), for different BP categories in both guidelines, compared to a reference category defined as systolic BP (SBP) <120 mmHg and diastolic BP (DBP) <80 mmHg. Within 8 years of median follow-up, 339 HF cases were detected. Per the 2017 ACC/AHA guidelines, hypertension I and II and isolated systolic hypertension were associated with increased HF risk: HRs (95% CIs) = 1.81 (1.33-2.47), 1.68 (1.24-2.27), and 1.64 (1.13-2.39), respectively. Per the 2018 ESC/ESH guidelines, high-normal BP, hypertension I, II, and III, and isolated systolic hypertension were associated with increased HF risk: HRs (95% CIs) = 1.88 (1.35-2.62), 1.57 (1.13-2.16), 2.10 (1.34-3.29), 2.57 (1.15-5.77), and 1.51 (1.04-2.19), respectively. In conclusion, hypertension and isolated systolic hypertension per the 2017 ACC/AHA and 2018 ESC/ESH guidelines and high-normal BP per the 2018 ESC/ESH guidelines are risk factors for HF.

RhoA rescues cardiac senescence by regulating Parkin-mediated mitophagy

Heart failure is one of the leading causes of death worldwide. RhoA, a small GTPase, governs actin dynamics in various tissue and cell types, including cardiomyocytes; however, its involvement in cardiac function has not been fully elucidated. Here, we generated cardiomyocyte-specific RhoA conditional knockout (cKO) mice, which demonstrated a significantly shorter lifespan with left ventricular dilation and severely impaired ejection fraction. We found that the cardiac tissues of the cKO mice exhibited structural disorganization with fibrosis and also exhibited enhanced senescence compared with control mice. In addition, we show that cardiomyocyte mitochondria were structurally abnormal in the aged cKO hearts. Clearance of damaged mitochondria by mitophagy was remarkably inhibited in both cKO cardiomyocytes and RhoA-knockdown HL-1 cultured cardiomyocytes. In RhoA-depleted cardiomyocytes, we reveal that the expression of Parkin, an E3 ubiquitin ligase that plays a crucial role in mitophagy, was reduced, and expression of N-Myc, a negative regulator of Parkin, was increased. We further reveal that the RhoA-Rho kinase axis induced N-Myc phosphorylation, which led to N-Myc degradation and Parkin upregulation. Re-expression of Parkin in RhoA-depleted cardiomyocytes restored mitophagy, reduced mitochondrial damage, attenuated cardiomyocyte senescence, and rescued cardiac function both in vitro and in vivo. Finally, we found that patients with idiopathic dilated cardiomyopathy without causal mutations for dilated cardiomyopathy showed reduced cardiac expression of RhoA and Parkin. These results suggest that RhoA promotes Parkin-mediated mitophagy as an indispensable mechanism contributing to cardioprotection in the aging heart.

Clinical Utility of Cardiovascular Risk Scores for Identification of People With Type 2 Diabetes More Likely to Benefit From Either GLP-1 Receptor Agonist or SGLT2 Inhibitor Therapy

OBJECTIVE

Differentiation of risk for major adverse cardiovascular events (MACE) from heart failure hospitalization (HHF) or kidney disease is important when selecting glucose-lowering therapy. We investigated the ability of separate MACE and HHF risk scores to 1) differentiate MACE from HHF risk; and 2) identify individuals more likely to benefit from either glucagon-like peptide-1 receptor agonists (GLP-1RAs) or sodium-glucose cotransporter-2 inhibitors (SGLT2is).

RESEARCH DESIGN AND METHODS

We identified three trials in type 2 diabetes that reported cardiovascular outcomes stratified by Thrombolysis In Myocardial Infarction Risk Scores for MACE and HHF. Pooled placebo-arm rates of HHF, MACE, and their ratio and estimated GLP-1RA- and SGLT2i-mediated reductions in events (MACE and HHF combined) were compared across cardiovascular risk strata in the trial populations.

RESULTS

The HHF rate was less frequent than MACE at all risk levels but increased from 18% of the MACE rate at low-intermediate HHF risk to 61% at highest HHF risk. Similarly, with increasing MACE risk, the incidence of HHF increased from 19% of the MACE incidence in those at low MACE risk to 51% in those with the highest MACE risk. Estimated GLP-1RA- and SGLT2i-mediated reductions in cardiovascular events were similar in those at low-intermediate MACE or HHF risk but tended to favor SGLT2is at higher risk levels of both scores.

CONCLUSIONS

A greater increase in the rate of HHF relative to MACE was observed with progressively higher cardiovascular risk, regardless of the risk score applied. Consequently, SGLT2is may offer greater overall cardiovascular protection in those at highest MACE risk, not just those at highest HHF risk.

New strategies and therapies for the prevention of heart failure in high-risk patients

Despite declines in total cardiovascular mortality rates in the United States, heart failure (HF) mortality rates as well as hospitalizations and readmissions have increased in the past decade. Increases have been relatively higher among young and middle-aged adults (<65 years). Therefore, identification of individuals HF at-risk (Stage A) or with pre-HF (Stage B) before the onset of overt clinical signs and symptoms (Stage C) is urgently needed. Multivariate risk models (e.g., Pooled Cohort Equations to Prevent Heart Failure [PCP-HF]) have been externally validated in diverse populations and endorsed by the 2022 HF Guidelines to apply a risk-based framework for the prevention of HF. However, traditional risk factors included in the PCP-HF model only account for half of an individual's lifetime risk of HF; novel risk factors (e.g., adverse pregnancy outcomes, impaired lung health, COVID-19) are emerging as important risk-enhancing factors that need to be accounted for in personalized approaches to prevention. In addition to determining the role of novel risk-enhancing factors, integration of social determinants of health (SDoH) in identifying and addressing HF risk is needed to transform the current clinical paradigm for the prevention of HF. Comprehensive strategies to prevent the progression of HF must incorporate pharmacotherapies (e.g., sodium glucose co-transporter-2 inhibitors that have also been termed the "statins" of HF prevention), intensive blood pressure lowering, and heart-healthy behaviors. Future directions include investigation of novel prediction models leveraging machine learning, integration of risk-enhancing factors and SDoH, and equitable approaches to interventions for risk-based prevention of HF.

Validation of Heart Failure-Specific Risk Equations in 1.3 Million Israeli Adults and Usefulness of Combining Ambulatory and Hospitalization Data from a Large Integrated Health Care Organization

Heart failure (HF) prevalence is increasing worldwide and is associated with significant morbidity and mortality. Guidelines emphasize prevention in those at-risk, but HF-specific risk prediction equations developed in United States population-based cohorts lack external validation in large, real-world datasets outside of the United States. The purpose of this study was to assess the model performance of the pooled cohort equations to prevent HF (PCP-HF) within a contemporary electronic health record for 5- and 10-year risk. Using a retrospective cohort study design of Israeli residents between 2008 and 2018 with continuous membership until end of follow-up, HF, or death, we quantified 5- and 10-year estimated risks of HF using the PCP-HF equations, which integrate demographics (age, gender, and race) and risk factors (body mass index, systolic blood pressure, glucose, medication use for hypertension or diabetes, and smoking status). Of 1,394,411 patients included, 56% were women with mean age of 49.6 (SD 13.2) years. Incident HF occurred in 1.2% and 4.5% of participants over 5 and 10 years of follow-up. The PCP-HF model had excellent discrimination for 5- and 10-year predictions of incident HF (C Statistic 0.82 [0.82 to 0.82] and 0.84 [0.84 to 0.84]), respectively. In conclusion, HF-specific risk equations (PCP-HF) accurately predict the risk of incident HF in ambulatory and hospitalized patients using routinely available clinical data.

Clinical Phenotypes of Cardiovascular and Heart Failure Diseases Can Be Reversed? The Holistic Principle of Systems Biology in Multifaceted Heart Diseases

Recent advances in cardiology and biological sciences have improved quality of life in patients with complex cardiovascular diseases (CVDs) or heart failure (HF). Regardless of medical progress, complex cardiac diseases continue to have a prolonged clinical course with high morbidity and mortality. Interventional coronary techniques together with drug therapy improve quality and future prospects of life, but do not reverse the course of the atherosclerotic process that remains relentlessly progressive. The probability of CVDs and HF phenotypes to reverse can be supported by the advances made on the medical holistic principle of systems biology (SB) and on artificial intelligence (AI). Studies on clinical phenotypes reversal should be based on the research performed in large populations of patients following gathering and analyzing large amounts of relative data that embrace the concept of complexity. To decipher the complexity conundrum, a multiomics approach is needed with network analysis of the biological data. Only by understanding the complexity of chronic heart diseases and explaining the interrelationship between different interconnected biological networks can the probability for clinical phenotypes reversal be increased.

Moving the Paradigm Forward for Prediction and Risk-Based Primary Prevention of Heart Failure in Special Populations

PURPOSE OF REVIEW

Heart failure (HF) treatment paradigms increasingly recognize the importance of primary prevention. This review explores factors that enhance HF risk, summarizes evidence supporting the pharmacologic primary prevention of HF, and notes barriers to the implementation of primary prevention of HF with a focus on female and sexual and gender minority patients.

RECENT FINDINGS

HF has pathophysiologic sex-specific distinctions, suggesting that sex-specific preventive strategies may be beneficial. Pharmacologic agents that have shown benefit in reducing the risk of HF address the pathobiology underpinning these sex-specific risk factors. The implementation of pharmacologic therapies for primary prevention of HF needs to consider a risk-based model. Current pharmacotherapies hold mechanistic promise for the primary prevention of HF in females and gender and sexual minorities, although research is needed to understand the specific populations most likely to benefit. There are significant systemic barriers to the equitable provision of HF primary prevention.

The short physical performance battery and incident heart failure among older women: the OPACH study

OBJECTIVE

Reduced functional capacity is a hallmark of early pre-clinical stages of heart failure (HF). The Short Physical Performance Battery (SPPB) is a valid measure of lower extremity physical function, has relatively low implementation burden, and is associated with cardiovascular disease and mortality. However, the SPPB-HF association is understudied in older women among whom HF burden is high.

METHODS

Women (n = 5325; mean age 79 ± 7 years; 34% Black, 18% Hispanic, and 49% White) without prior HF completed the SPPB consisting of standing balance, strength, and walking tests that were summarized as a composite score from 0 (lowest) to 12 (highest), categorized as very low (0-3), low (4-6), medium (7-9), or high (10-12). Participants were followed for up to 8 years for incident HF (306 cases identified). Cox proportional hazards regression estimated hazard ratios (HR) adjusting for age, race/ethnicity, education, smoking, alcohol, diabetes, hypertension, COPD, osteoarthritis, depression, BMI, systolic blood pressure, lipids, glucose, and accelerometer-measured moderate-vigorous physical activity (MVPA) and sedentary time.

RESULTS

Incident HF cases (crude rate per 1000 person-years) in the four SPPB categories (very low to high) were 34 (26.0), 79 (14.5), 128 (9.3), and 65 (5.6). Corresponding multivariable-adjusted HRs (95% CIs) were 2.22 (1.34-3.66), 1.63 (1.11-2.38), 1.39 (1.00-1.94), and 1.00 (referent; P-trend<0.001). Higher HF risk was associated with lower SPPB in women with major modifiable HF risk factors including obesity (HR per 3-unit SPPB decrement: present HR = 1.41, absent HR = 1.41), hypertension (present HR = 1.45, absent HR = 1.30), diabetes (present HR = 1.32, absent HR = 1.44), and lower accelerometer-measured MVPA (<45 min/day HR = 1.29, ≥45 min/day HR = 1.60); all P-interaction>0.10.

CONCLUSION

Lower SPPB scores were associated with greater risk of incident HF in older women even after accounting for differences in HF risk factors and objectively measured PA. Implementing the SPPB in clinical settings could potentially enhance individual-level HF risk assessment, which should be further explored.