An update on the use and discovery of prognostic biomarkers in acute decompensated heart failure

Comprehensive Quality Analysis of Conventional and Novel Biomarkers in Diagnosing and Predicting Prognosis of Coronary Artery Disease, Acute Coronary Syndrome, and Heart Failure, a Comprehensive Literature Review

Coronary artery disease (CAD), acute coronary syndrome (ACS), and heart failure (HF) are major global health issues with high morbidity and mortality rates. Biomarkers like cardiac troponins (cTn) and natriuretic peptides (NPs) are crucial tools in cardiology, but numerous new biomarkers have emerged, proving increasingly valuable in CAD/ACS. These biomarkers are classified based on their mechanisms, such as fibrosis, metabolism, inflammation, and congestion. The integration of established and emerging biomarkers into clinical practice is an ongoing process, and recognizing their strengths and limitations is crucial for their accurate interpretation, incorporation into clinical settings, and improved management of CVD patients. We explored established biomarkers like cTn, NPs, and CRP, alongside newer biomarkers such as Apo-A1, IL-17E, IgA, Gal-3, sST2, GDF-15, MPO, H-FABP, Lp-PLA2, and ncRNAs; provided evidence of their utility in CAD/ACS diagnosis and prognosis; and empowered clinicians to confidently integrate these biomarkers into clinical practice based on solid evidence.

Diagnostic Modalities in Heart Failure: A Narrative Review

Heart failure (HF) can present acutely or progress over time. It can lead to morbidity and mortality affecting 6.5 million Americans over the age of 20. The HF type is described according to the ejection fraction classification, defined as the percentage of blood volume that exits the left ventricle after myocardial contraction, undergoing ejection into the circulation, also called stroke volume, and is proportional to the ejection fraction. Cardiac catheterization is an invasive procedure to evaluate coronary artery disease leading to HF. Several biomarkers are being studied that could lead to early detection of HF and better symptom management. Testing for various biomarkers in the patient's blood is instrumental in confirming the diagnosis and elucidating the etiology of HF. There are various biomarkers elevated in response to increased myocardial stress and volume overload, including B-type natriuretic peptide (BNP) and its N-terminal prohormone BNP. We explored online libraries such as PubMed, Google Scholar, and Cochrane to find relevant articles. Our narrative review aims to extensively shed light on diagnostic modalities and novel techniques for diagnosing HF.

Therapeutic and Prognostic Significance of Arachidonic Acid in Heart Failure

BACKGROUND

Accurate prediction of death is an unmet need in patients with acute decompensated heart failure (HF). Arachidonic acid (AA) metabolites play an important role in the multiple pathophysiological processes. We aimed to develop an AA score to accurately predict mortality in patients with acute decompensated HF and explore the causal relationship between the AA predictors and HF.

METHODS

The serum AA metabolites was measured in patients with acute decompensated HF (discovery cohort n=419; validation cohort n=386) by mass spectroscopy. We assessed the prognostic importance of AA metabolites for 1-year death using Cox regression and machine learning approaches. An machine learning-based AA score for predicting 1-year death was created and validated. We explored the mechanisms using transcriptome and functional experiments in a mouse model of early ischemic cardiomyopathy.

RESULTS

Among the 27 AA metabolites, elevated 14,15-DHET/14,15-EET ratio was the strongest predictor of 1-year death (hazard ratio, 2.10, P=3.1×10^-6). Machine learning-based AA score using a combination of the 14,15-DHET/14,15-EET ratio, 14,15-DHET, PGD2, and 9-HETE performed best (area under the curve [AUC]: 0.85). The machine learning-based AA score provided incremental information to predict mortality beyond BNP (B-type natriuretic peptide; ΔAUC: 0.19), clinical score (ΔAUC: 0.09), and preexisting ADHERE, Organized Program to Initiate Lifesaving Treatment in Hospitalized Patients With Heart Failure, and Get With The Guidelines Heart Failure scores (ΔAUC: 0.17, 0.17, 0.15, respectively). In the validation cohort, the AA score accurately predicted mortality (AUC:0.81). False-negative and false-positive findings, as classified by the BNP threshold, were correctly reclassified by the AA score (46.2% of false-negative and 84.5% of false-positive). In a murine model, the expression and enzymatic activity of sEH (soluble epoxide hydrolase) increased after myocardial infarction. Genetic deletion of sEH improved HF and the blockade of 14,15-EET abolished this cardioprotection. We mechanistically revealed the beneficial effect of 14,15-EET by impairing the activation of monocytes/macrophages.

CONCLUSIONS

Our studies propose that the AA score predicts death in patients with acute decompensated HF and inhibiting sEH serves as a therapeutic target for treating HF.

REGISTRATION

URL: https://www.

CLINICALTRIALS

gov; Unique identifier: NCT04108182.

Frequency of Atrial Fibrillation in Patients Presenting With Decompensated Heart Failure

Background

Atrial fibrillation (AF) is a common concern in patients with heart disease, especially those with acute decompensated heart failure (ADHF). We conducted a cross-sectional study to determine the frequency of AF and associated risk factors among patients with ADHF at a tertiary care hospital in Peshawar, Pakistan.

Methods

We conducted a cross-sectional analytical study of hospitalized patients with ADHF treated in a tertiary care hospital in Peshawar, Pakistan, from June 5 to October 30, 2021. The study's primary outcome was the proportion of patients with ADHF who had AF, and our secondary outcome was examining the risk factors for AF. The College of Physicians and Surgeons Pakistan provided ethical approval of the study design. Data were analyzed using IBM SPSS Statistics for Windows version 24.0 (IBM Corp., Armonk, NY, USA). We applied the chi-square test to compare the proportion of AF concerning risk factors (i.e., comorbidities).

Results

One hundred ninety-four patients with ADHF were included in the study; 54.6% were male and 45.4% female. Most (56.7%) were older than 60, and 38.1% were aged 40-60. The prevalence of AF was 38.1%. Diabetes, hypertension, previous stroke, myocardial infarction (MI), and chronic obstructive pulmonary disease (COPD) were the most common comorbidities. All patients with ADHF with AF also had MI and hypertension. Patients of known coronary artery disease (CAD) but without MI, previous percutaneous coronary intervention (PCI), or coronary artery bypass graft (CABG) surgery were less associated with AF than other comorbidities.

Conclusions

We conducted this study to determine the incidence of AF among patients with ADHF. AF occurs in a significant amount of patients with ADHF, and the risk factors associated with AF in these patients include hypertension, history of MI, diabetes, and COPD. Healthcare professionals should screen patients with ADHF for AF, especially those with common risk factors.

Novel Biomarkers in Heart Failure: New Insight in Pathophysiology and Clinical Perspective

Heart failure (HF) is a complex clinical syndrome with a huge social burden in terms of cost, morbidity, and mortality. Brain natriuretic peptide (BNP) appears to be the gold standard in supporting the daily clinical management of patients with HF. Novel biomarkers may supplement BNP to improve the understanding of this complex disease process and, possibly, to personalize care for the different phenotypes, in order to ameliorate prognosis. In this review, we will examine some of the most promising novel biomarkers in HF. Inflammation plays a pivotal role in the genesis and progression of HF and, therefore, several candidate molecules have been investigated in recent years for diagnosis, prognosis, and therapy monitoring. Noncoding RNAs are attractive as biomarkers and their potential clinical applications may be feasible in the era of personalized medicine. Given the complex pathophysiology of HF, it is reasonable to expect that the future of biomarkers lies in the application of precision medicine, through wider testing panels and “omics” technologies, to further improve HF care delivery.