Aims Endothelin‐1 (ET‐1) is a potent vasoconstrictor, which regulates renal and vascular function. We aimed to relate plasma levels of ET‐1 with the clinical picture and outcomes in acute heart failure (AHF). Methods and results We studied 113 patients with AHF [mean age 65 ± 13 (years), median (upper and lower quartiles) N‐terminal pro‐B‐type natriuretic peptide, 5422 (2689; 8582) (pg/mL)], in whom plasma levels of ET‐1 were serially measured at admission (10.8 ± 5.2), Day 1 (9.5 ± 3.4), and Day 2 (8.9 ± 3.8) (pg/mL). The population was divided into tertiles across baseline ET‐1 levels. Patients in the highest ET‐1 tertile had predominant clinical signs of peripheral congestion; however, no difference was observed in pulmonary congestion and severity of dyspnoea. They also presented lower spot urine sodium at admission (75 ± 35 vs. 99 ± 43 vs. 108 ± 30), 6 h (84 ± 34 vs. 106 ± 43 vs. 106 ± 35), and Day 1 (75 ± 38 vs. 96 ± 36 vs. 100 ± 35) (mmol/L), when compared with the second and first tertile, respectively (all P < 0.05); furthermore, they received higher doses of intravenous furosemide from Day 2 and had longer intravenous diuretics, as median switch to oral furosemide was 4 (3; 4) vs. 3 (2; 4) vs. 2 (2; 3) (days), respectively, P < 0.05. There was no difference in serum creatinine, urea, and renal injury biomarkers (kidney injury molecule‐1, serum cystatin C, and urine neutrophil gelatinase‐associated lipocalin) between the ET‐1 tertiles. Higher values of ET‐1 measured at each time point were related with a higher risk of 1 year mortality. Conclusions Elevation of ET‐1 is related to clinical signs of peripheral congestion, low urine sodium excretion, and poor outcome in AHF.

Despite the progress of its management, COVID-19 maintains an ominous condition which constitutes a threat, especially for the susceptible population. The cardiac injury occurs in approximately 30% of COVID-19 infections and is associated with a worse prognosis. The clinical presentation of cardiac involvement can be COVID-19-related myocarditis. Our review aims to summarise current evidence about that complication. The research was registered at PROSPERO (CRD42022338397). We performed a systematic analysis using five different databases, including i.a. MEDLINE. Further, the backward snowballing technique was applied to identify additional papers. Inclusion criteria were: full-text articles in English presenting cases of COVID-19-related myocarditis diagnosed by the ESC criteria and patients over 18 years old. The myocarditis had to occur after the COVID-19 infection, not vaccination. Initially, 1588 papers were screened from the database search, and 1037 papers were revealed in the backward snowballing process. Eventually, 59 articles were included. Data about patients’ sex, age, ethnicity, COVID-19 confirmation technique and vaccination status, reported symptoms, physical condition, laboratory and radiological findings, applied treatment and patient outcome were investigated and summarised. COVID-19-related myocarditis is associated with the risk of sudden worsening of patients’ clinical status, thus, knowledge about its clinical presentation is essential for healthcare workers.

Acute heart failure (AHF) is a life-threatening, heterogeneous disease requiring urgent diagnosis and treatment. The clinical severity and medical procedures differ according to a complex interplay between the deterioration cause, underlying cardiac substrate, and comorbidities. This study aimed to analyze the natural phenotypic heterogeneity of the AHF population and evaluate the possibilities offered by clustering (unsupervised machine-learning technique) in a medical data assessment. We evaluated data from 381 AHF patients. Sixty-three clinical and biochemical features were assessed at the admission of the patients and were included in the analysis after the preprocessing. The K-medoids algorithm was implemented to create the clusters, and optimization, based on the Davies-Bouldin index, was used. The clustering was performed while blinded to the outcome. The outcome associations were evaluated using the Kaplan-Meier curves and Cox proportional-hazards regressions. The algorithm distinguished six clusters that differed significantly in 58 variables concerning i.e., etiology, clinical status, comorbidities, laboratory parameters and lifestyle factors. The clusters differed in terms of the one-year mortality (p = 0.002). Using the clustering techniques, we extracted six phenotypes from AHF patients with distinct clinical characteristics and outcomes. Our results can be valuable for future trial constructions and customized treatment.

This narrative review explores the multifaceted role of lactate in heart failure (HF), focusing on its diagnostic and prognostic significance in both acute and chronic HF. Lactate functions not only as a marker of hypoperfusion and anaerobic metabolism but also as an active metabolic substrate. In acute HF, elevated lactate levels often signal circulatory insufficiency and predict adverse outcomes. In chronic HF, especially HFpEF, lactate dynamics during exercise reflect metabolic inefficiency and correlate with functional impairment. This review emphasizes the dual nature of lactate and discusses its potential utility in risk stratification and therapeutic guidance.

Heart failure (HF) is a complex clinical syndrome characterized by the heart’s inability to maintain sufficient circulation, leading to inadequate organ perfusion and fluid buildup. A thorough understanding of the molecular, biochemical, and hemodynamic interactions that underlie this condition is essential for improving its management and enhancing patient outcomes. Recent advancements in cardiovascular research have emphasized the critical role of microRNAs (miRNAs) as post-transcriptional regulators of gene expression, playing an important part in the development and progression of HF. This review aims to explore the contributions of miRNAs, systemic congestion markers, and traditional biomarkers to the pathophysiology of heart failure, with the objective of clarifying their prognostic value and potential clinical applications. Among the miRNAs studied, miR-30d, miR-126-3p, and miR-483-3p have been identified as key players in processes such as left ventricular remodeling, regulation of pulmonary artery pressure, and adaptation of the right ventricle. These findings underscore the importance of miRNAs in modulating the structural and functional changes seen in HF. Beyond the heart, HF affects multiple organ systems, including the kidneys and liver, with markers of dysfunction in these organs—such as worsening renal function and liver stiffness—being closely linked to increased morbidity and mortality. This highlights the interdependence of the heart and other organs, where systemic congestion, indicated by elevated venous pressures, exacerbates organ dysfunction. In this context, traditional biomarkers like natriuretic peptides and cardiac troponins remain vital tools in the diagnosis and management of HF. Natriuretic peptides reflect ventricular strain, while troponins are indicators of myocardial injury, both of which are critical for risk stratification and monitoring disease progression. Emerging diagnostic techniques, such as lung ultrasonography and advanced echocardiographic methods, offer new ways to assess hemodynamic status, further aiding therapeutic decision-making. These techniques, alongside established biomarkers, provide a more comprehensive approach to understanding the complexities of heart failure and managing its impact on patients. In conclusion, miRNAs, systemic congestion markers, and traditional biomarkers are indispensable for understanding HF pathophysiology and determining patient prognosis. The integration of novel diagnostic tools with existing biomarkers holds the promise of improved strategies for the management of heart failure. However, further research is needed to validate their prognostic value and refine their role in optimizing treatment outcomes.

Heart failure (HF) is a challenging syndrome, affecting 64 million people worldwide, and is associated with high mortality rates. There are several potential biomarkers that help us diagnose the disease as well as help us assess the prognosis. Cardiac troponins I and T are effective tools for predicting poor outcomes in HF. Cardiac troponins are intracellular proteins responsible for regulating and conducting muscle contractions. They indicate cardiomyocyte injury caused by ischemia, toxins, inflammation, wall stress, and other factors. Some of these injuries may be reversible. The blood level of troponins is influenced by various factors, both physiological—such as sex, age, and weight—and pathological, including microbiological organisms, autoantibody complexes, and conditions like pulmonary embolism, stroke, sepsis, or kidney disease. Numerous studies demonstrate the effectiveness of troponin measurement in prognostication for patients with acute and chronic HF. However, it has been found that many patients with chronic heart failure have undetectable serum levels of cardiac troponins, leading to the adoption of high-sensitivity cardiac troponins (hs-cTn). Expanding this knowledge is crucial for enabling more intensive stratification and early identification of patients with poorer prognoses.