Biomarker Profiles of Acute Heart Failure Patients With a Mid-Range Ejection Fraction

Interplay of the heart, spleen, and bone marrow in heart failure: the role of splenic extramedullary hematopoiesis

Improvements in therapies for heart failure with preserved ejection fraction (HFpEF) are crucial for improving patient outcomes and quality of life. Although HFpEF is the predominant heart failure type among older individuals, its prognosis is often poor owing to the lack of effective therapies. The roles of the spleen and bone marrow are often overlooked in the context of HFpEF. Recent studies suggest that the spleen and bone marrow could play key roles in HFpEF, especially in relation to inflammation and immune responses. The bone marrow can increase production of certain immune cells that can migrate to the heart and contribute to disease. The spleen can contribute to immune responses that either protect or exacerbate heart failure. Extramedullary hematopoiesis in the spleen could play a crucial role in HFpEF. Increased metabolic activity in the spleen, immune cell production and mobilization to the heart, and concomitant cytokine production may occur in heart failure. This leads to systemic chronic inflammation, along with an imbalance of immune cells (macrophages) in the heart, resulting in chronic inflammation and progressive fibrosis, potentially leading to decreased cardiac function. The bone marrow and spleen are involved in altered iron metabolism and anemia, which also contribute to HFpEF. This review presents the concept of an interplay between the heart, spleen, and bone marrow in the setting of HFpEF, with a particular focus on extramedullary hematopoiesis in the spleen. The aim of this review is to discern whether the spleen can serve as a new therapeutic target for HFpEF.

The role of urine chloride in acute heart failure

In our retrospective study, we aimed to investigate the relationship between urinary chloride (uCl-) and selected clinical and laboratory biomarkers, renal function, and patient outcomes in the acute heart failure (AHF) population. We divided 248 adult patients (≥ 18 years) with AHF into two groups: low uCl- (< 115 mmol/L) and high uCl-. The mean age of the patient group was 70.2 ± 12.6, and 182 patients were male (73.4%). Clinical endpoints included in-hospital mortality, one-year mortality, and a composite endpoint of one-year mortality and rehospitalization for heart failure. Patients were followed up for at least one year. Relevant clinical and baseline biomarker data were collected, including markers concerning inflammation, liver and kidney function, perfusion and congestion, iron status, cardiac remodeling, gasometry, renin and aldosterone. Low uCl- was associated with worse in-hospital outcomes, including higher in-hospital mortality (7.7% vs. 1.4%, p = 0.014), the need for inotropic support (20.19% vs. 2.08%, p ≤ 0.001), worsening of HF during therapy (17.31% vs. 4.86%, p ≤ 0.001), and the need for treatment in an intensive cardiac care unit (33.65% vs. 15.28%, p ≤ 0.001). Low uCl- was a significant predictor of one-year mortality (40.4% vs. 16.7%, p < 0.05) and the composite outcome (HR 2.42, 95% CI 1.43-4.08, p < 0.001). In the multivariable analysis, uCl- was independently associated with the risk of one-year mortality (HR 0.92, 95% CI 0.87-0.98, p < 0.05) and the composite outcome (HR 0.95, 95% CI 0.92-0.99, p < 0.05). Our findings suggest that low uCl- is a marker of more advanced heart failure, activation of the renin-angiotensin-aldosterone system and is related to worse one-year outcomes.

Artificial intelligence-assisted automated heart failure detection and classification from electronic health records

AIMS

Electronic health records (EHR) linked to Digital Imaging and Communications in Medicine (DICOM), biological specimens, and deep learning (DL) algorithms could potentially improve patient care through automated case detection and surveillance. We hypothesized that by applying keyword searches to routinely stored EHR, in conjunction with AI-powered automated reading of DICOM echocardiography images and analysing biomarkers from routinely stored plasma samples, we were able to identify heart failure (HF) patients.

METHODS AND RESULTS

We used EHR data between 1993 and 2021 from Tayside and Fife (~20% of the Scottish population). We implemented a keyword search strategy complemented by filtering based on International Classification of Diseases (ICD) codes and prescription data to EHR data set. We then applied DL for the automated interpretation of echocardiographic DICOM images. These methods were then integrated with the analysis of routinely stored plasma samples to identify and categorize patients into HF with reduced ejection fraction (HFrEF), HF with preserved ejection fraction (HFpEF), and controls without HF. The final diagnosis was verified through a manual review of medical records, measured natriuretic peptides in stored blood samples, and by comparing clinical outcomes among groups. In our study, we selected the patient cohort through an algorithmic workflow. This process started with 60 850 EHR data and resulted in a final cohort of 578 patients, divided into 186 controls, 236 with HFpEF, and 156 with HFrEF, after excluding individuals with mismatched data or significant valvular heart disease. The analysis of baseline characteristics revealed that compared with controls, patients with HFrEF and HFpEF were generally older, had higher BMI, and showed a greater prevalence of co-morbidities such as diabetes, COPD, and CKD. Echocardiographic analysis, enhanced by DL, provided high coverage, and detailed insights into cardiac function, showing significant differences in parameters such as left ventricular diameter, ejection fraction, and myocardial strain among the groups. Clinical outcomes highlighted a higher risk of hospitalization and mortality for HF patients compared with controls, with particularly elevated risk ratios for both HFrEF and HFpEF groups. The concordance between the algorithmic selection of patients and manual validation demonstrated high accuracy, supporting the effectiveness of our approach in identifying and classifying HF subtypes, which could significantly impact future HF diagnosis and management strategies.

CONCLUSIONS

Our study highlights the feasibility of combining keyword searches in EHR, DL automated echocardiographic interpretation, and biobank resources to identify HF subtypes.

Pharmacological Effects of Botanical Drugs on Myocardial Metabolism in Chronic Heart Failure

Although there have been significant advances in the treatment of heart failure in recent years, chronic heart failure remains a leading cause of cardiovascular disease-related death. Many studies have found that targeted cardiac metabolic remodeling has good potential for the treatment of heart failure. However, most of the drugs that increase cardiac energy are still in the theoretical or testing stage. Some research has found that botanical drugs not only increase myocardial energy metabolism through multiple targets but also have the potential to restore the balance of myocardial substrate metabolism. In this review, we summarized the mechanisms by which botanical drugs (the active ingredients/formulas/Chinese patent medicines) improve substrate utilization and promote myocardial energy metabolism by activating AMP-activated protein kinase (AMPK), peroxisome proliferator-activated receptors (PPARs) and other related targets. At the same time, some potential protective effects of botanical drugs on myocardium, such as alleviating oxidative stress and dysbiosis signaling, caused by metabolic disorders, were briefly discussed.

Inflammation in heart failure: pathophysiology and therapeutic strategies

A role for inflammation in the development and progression of heart failure (HF) has been proposed for decades. Multiple studies have demonstrated the potential involvement of several groups of cytokines and chemokines in acute and chronic HF, though targeting these pathways in early therapeutic trials have produced mixed results. These studies served to highlight the complexity and nuances of how pro-inflammatory pathways contribute to the pathogenesis of HF. More recent investigations have highlighted how inflammation may play distinct roles based on HF syndrome phenotypes, findings that may guide the development of novel therapies. In this review, we propose a contemporary update on the role of inflammation mediated by the innate and adaptive immune systems with HF, highlighting differences that exist across the ejection fraction spectrum. This will specifically be looked at through the lens of established and novel biomarkers of inflammation. Subsequently, we review how improvements in inflammatory pathways may mediate clinical benefits of existing guideline-directed medical therapies for HF, as well as future therapies in the pipeline targeting HF and inflammation.

Exploring the mechanism of ShenGui capsule in treating heart failure based on network pharmacology and molecular docking: A review

ShenGui capsule (SGC), as a herbal compound, has significant effects on the treatment of heart failure (HF), but its mechanism of action is unclear. In this study, we aimed to explore the potential pharmacological targets and mechanisms of SGC in the treatment of HF using network pharmacology and molecular docking approaches. Potential active ingredients of SGC were obtained from the traditional Chinese medicine systems pharmacology database and analysis platform database and screened by pharmacokinetic parameters. Target genes of HF were identified by comparing the toxicogenomics database, GeneCards, and DisGeNET databases. Protein interaction networks and gene-disorder-target networks were constructed using Cytoscape for visual analysis. Gene ontology and Kyoto Encyclopedia of Genes and Genomes were also performed to identify protein functional annotations and potential target signaling pathways through the DAVID database. CB-DOCK was used for molecular docking to explore the role of IL-1β with SGC compounds. Sixteen active ingredients in SGC were screened from the traditional Chinese medicine systems pharmacology database and analysis platform, of which 36 target genes intersected with HF target genes. Protein-protein interactions suggested that each target gene was closely related, and interleukin-1β (IL-1β) was identified as Hub gene. The network pharmacology analysis suggested that these active ingredients were well correlated with HF. Kyoto Encyclopedia of Genes and Genomes enrichment analysis suggested that target genes were highly enriched in pathways such as inflammation. Molecular docking results showed that IL-1β binds tightly to SGC active components. This experiment provides an important research basis for the mechanism of action of SGC in the treatment of HF. In this study, the active compounds of SGC were found to bind IL-1β for the treatment of heart failure.

Distinguishing heart failure with reduced ejection fraction from heart failure with preserved ejection fraction: A phenomics approach

AIM

Pathophysiological differences between patients with heart failure with preserved (HFpEF) and reduced (HFrEF) ejection fraction (EF) remain unclear. Therefore we used a phenomics approach, integrating selected proteomics data with patient characteristics and cardiac structural and functional parameters, to get insight into differential pathophysiological mechanisms and identify potential treatment targets.

METHODS AND RESULTS

We report data from a representative subcohort of the prospective Singapore Heart Failure Outcomes and Phenotypes (SHOP), including patients with HFrEF (EF <40%, n = 217), HFpEF (EF ≥50%, n = 213), and age- and sex-matched controls without HF (n = 216). We measured 92 biomarkers using a proximity extension assay and assessed cardiac structure and function in all participants using echocardiography. We used multi-block projection to latent structure analysis to integrate clinical, echocardiographic, and biomarker variables. Candidate biomarker targets were cross-referenced with small-molecule and drug databases. The total cohort had a median age of 65 years (interquartile range 60-71), and 50% were women. Protein profiles strongly discriminated patients with HFrEF (area under the curve [AUC] = 0.89) and HFpEF (AUC = 0.94) from controls. Phenomics analyses identified unique druggable inflammatory markers in HFpEF from the tumour necrosis factor receptor superfamily (TNFRSF), which were positively associated with hypertension, diabetes, and increased posterior and relative wall thickness. In HFrEF, interleukin (IL)-8 and IL-6 were possible targets related to lower EF and worsening renal function.

CONCLUSION

We identified pathophysiological mechanisms related to increased cardiac wall thickness parameters and potentially druggable inflammatory markers from the TNFRSF in HFpEF.

Myeloperoxidase, carnitine, and derivatives of reactive oxidative metabolites in heart failure with preserved versus reduced ejection fraction: A meta-analysis

BACKGROUND

Understanding the pathophysiology of heart failure (HF) with preserved ejection fraction (HFpEF) continues to be challenging. Several inflammatory and metabolic biomarkers have recently been suggested to be involved in HFpEF.

OBJECTIVES

The purpose of this review was to synthesize the evidence on non-traditional biomarkers from metabolomic studies that may distinguish HFpEF from heart failure with reduced ejection fraction (HFrEF) and controls without HF.

METHODS

A systematic search was conducted using Medline and PubMed with search terms such as "HFpEF" and "metabolomics", and a meta-analysis was conducted.

RESULTS

Myeloperoxidase (MPO) levels were significantly (p < 0.001) higher in HFpEF than controls without HF, but comparable (p = 0.838) between HFpEF and HFrEF. Carnitine levels were significantly (p < 0.0001) higher in HFrEF than HFpEF, but comparable (p = 0.443) between HFpEF and controls without HF. Derivatives of reactive oxidative metabolites (DROMs) were not significantly (p = 0.575) higher in HFpEF than controls without HF.

CONCLUSION

These data suggest that MPO is operative in HFpEF and HFrEF and may be a biomarker for HF. Furthermore, circulating carnitine levels may distinguish HFrEF from HFpEF.

The impact of platelet-to-lymphocyte ratio on clinical outcomes in heart failure: a systematic review and meta-analysis

BACKGROUND

Inflammation has been suggested to play a role in heart failure (HF) pathogenesis. However, the role of platelet-to-lymphocyte ratio (PLR), as a novel biomarker, to assess HF prognosis needs to be investigated. We sought to evaluate the impact of PLR on HF clinical outcomes.

METHODS

English-published records in PubMed/Medline, Scopus, and Web-of-science databases were screened until December 2023. Relevant articles evaluated PLR with clinical outcomes (including mortality, rehospitalization, HF worsening, and HF detection) were recruited, with PLR difference analysis based on death/survival status in total and HF with reduced ejection fraction (HFrEF) patients.

RESULTS

In total, 21 articles (n = 13,924) were selected. The total mean age was 70.36 ± 12.88 years (males: 61.72%). Mean PLR was 165.54 [95% confidence interval (CI): 154.69-176.38]. In total, 18 articles (n = 10,084) reported mortality [either follow-up (PLR: 162.55, 95% CI: 149.35-175.75) or in-hospital (PLR: 192.83, 95% CI: 150.06-235.61) death rate] and the mean PLR was 166.68 (95% CI: 154.87-178.50). Further analysis revealed PLR was significantly lower in survived HF patients rather than deceased group (152.34, 95% CI: 134.01-170.68 versus 194.73, 95% CI: 175.60-213.85, standard mean difference: -0.592, 95% CI: -0.857 to -0.326, p < 0.001). A similar trend was observed for HFrEF patients. PLR failed to show any association with mortality risk (hazard ratio: 1.02, 95% CI: 0.99-1.05, p = 0.289). Analysis of other aforementioned outcomes was not possible due to the presence of few studies of interest.

CONCLUSION

PLR should be used with caution for prognosis assessment in HF sufferers and other studies are necessary to explore the exact association.

Inflammation in Heart Failure-Future Perspectives

Chronic heart failure is a terminal point of a vast majority of cardiac or extracardiac causes affecting around 1-2% of the global population and more than 10% of the people above the age of 65. Inflammation is persistently associated with chronic diseases, contributing in many cases to the progression of disease. Even in a low inflammatory state, past studies raised the question of whether inflammation is a constant condition, or if it is, rather, triggered in different amounts, according to the phenotype of heart failure. By evaluating the results of clinical studies which focused on proinflammatory cytokines, this review aims to identify the ones that are independent risk factors for heart failure decompensation or cardiovascular death. This review assessed the current evidence concerning the inflammatory activation cascade, but also future possible targets for inflammatory response modulation, which can further impact the course of heart failure.

Plasma tumour necrosis factor-alpha-related proteins in prognosis of heart failure with pulmonary hypertension

AIMS

Patients with heart failure (HF) exhibit poor prognosis, which is further deteriorated by pulmonary hypertension (PH), with negative impact on morbidity and mortality. As PH due to left HF (LHF-PH) is among the most common causes of PH, there is an urge according to the 2021 European Society of Cardiology HF guidelines to find new biomarkers that aid in prognostication of this patient cohort. Given the role of tumour necrosis factor-alpha (TNF-α) in HF progression, we aimed to investigate the prognostic value of plasma proteins related to TNF-α in patients with LHF-PH, in relation to haemodynamic changes following heart transplantation (HT).

METHODS AND RESULTS

Twenty TNF-α-related plasma proteins were analysed using proximity extension assay in healthy controls (n = 20) and patients with LHF-PH (n = 67), before and 1 year after HT (n = 19). Plasma levels were compared between the groups, and the prognostic values were determined using Kaplan-Meier and Cox regression analyses. Plasma levels of lymphotoxin-beta receptor (LTBR), TNF receptor superfamily member 6B (TNFRSF6B), and TNF-related apoptosis-inducing ligand receptors 1 and 2 (TRAIL-R1 and TRAIL-R2, respectively) were higher in LHF-PH pre-HT vs. controls (P < 0.0001), as well as higher in pre-HT vs. post-HT (P < 0.001). The elevated pre-HT levels of LTBR, TNFRSF6B, TRAIL-R1, and TRAIL-R2 decreased towards the levels of healthy controls after HT. Higher preoperative levels of LTBR, TNFRSF6B, TRAIL-R1, and TRAIL-R2 in LHF-PH were associated with worse survival rates (P < 0.002). In multivariate Cox regression models, each adjusted for age and sex, LTBR, TNFRSF6B, TRAIL-R1, and TRAIL-R2 predicted mortality (P < 0.002) [hazard ratio (95% confidence interval): 1.12 (1.04-1.19), 1.01 (1.004-1.02), 1.28 (1.14-1.42), and 1.03 (1.02-1.04), respectively].

CONCLUSIONS

Elevated pre-HT plasma levels of the TNF-α-related proteins LTBR, TNFRSF6B, TRAIL-R1, and TRAIL-R2 in LHF-PH decreased 1 year after HT, displaying a normalization pattern towards the levels of the healthy controls. These proteins were also prognostic, where higher levels were associated with worse survival rates in LHF-PH, providing new insight in their potential role as prognostic biomarkers. Larger studies are warranted to validate our findings and to investigate their possible pathobiological mechanisms in LHF-PH.

Proteomic Pathways across Ejection Fraction Spectrum in Heart Failure: an EXSCEL Substudy

Background

Ejection fraction (EF) is a key component of heart failure (HF) classification, including the increasingly codified HF with mildly reduced EF (HFmrEF) category. However, the biologic basis of HFmrEF as an entity distinct from HF with preserved EF (HFpEF) and reduced EF (HFrEF) has not been well characterized.

Methods

The EXSCEL trial randomized participants with type 2 diabetes (T2DM) to once-weekly exenatide (EQW) vs. placebo. For this study, profiling of ∼5000 proteins using the SomaLogic SomaScan platform was performed in baseline and 12-month serum samples from N=1199 participants with prevalent HF at baseline. Principal component analysis (PCA) and ANOVA (FDR p<0.1) were used to determine differences in proteins between three EF groups, as previously curated in EXSCEL (EF>55% [HFpEF], EF 40-55% [HFmrEF], EF<40% [HFrEF]). Cox proportional hazards was used to assess association between baseline levels of significant proteins, and changes in protein level between baseline and 12-month, with time-to-HF hospitalization. Mixed models were used to assess whether significant proteins changed differentially with exenatide vs. placebo therapy.

Results

Of N=1199 EXSCEL participants with prevalent HF, 284 (24%), 704 (59%) and 211 (18%) had HFpEF, HFmrEF and HFrEF, respectively. Eight PCA protein factors and 221 individual proteins within these factors differed significantly across the three EF groups. Levels of the majority of proteins (83%) demonstrated concordance between HFmrEF and HFpEF, but higher levels in HFrEF, predominated by the domain of extracellular matrix regulation, e.g. COL28A1 and tenascin C [TNC]; p<0.0001. Concordance between HFmrEF and HFrEF was observed in a minority of proteins (1%) including MMP-9 (p<0.0001). Biologic pathways of epithelial mesenchymal transition, ECM receptor interaction, complement and coagulation cascades, and cytokine receptor interaction demonstrated enrichment among proteins with the dominant pattern, i.e. HFmrEF-HFpEF concordance. Baseline levels of 208 (94%) of the 221 proteins were associated with time-to-incident HF hospitalization including domains of extracellular matrix (COL28A1, TNC), angiogenesis (ANG2, VEGFa, VEGFd), myocyte stretch (NT-proBNP), and renal function (cystatin-C). Change in levels of 10 of the 221 proteins from baseline to 12 months (including increase in TNC) predicted incident HF hospitalization (p<0.05). Levels of 30 of the 221 significant proteins (including TNC, NT-proBNP, ANG2) were reduced differentially by EQW compared with placebo (interaction p<0.0001).

Conclusions

In this HF substudy of a large clinical trial of people with T2DM, we found that serum levels of most proteins across multiple biologic domains were similar between HFmrEF and HFpEF. HFmrEF may be more biologically similar to HFpEF than HFrEF, and specific related biomarkers may offer unique data on prognosis and pharmacotherapy modification with variability by EF.

Identification of patient subtypes based on protein expression for prediction of heart failure after myocardial infarction

This study investigates the ability of high-throughput aptamer-based platform to identify circulating biomarkers able to predict occurrence of heart failure (HF), in blood samples collected during hospitalization of patients suffering from a first myocardial infarction (MI). REVE-1 (derivation) and REVE-2 (validation) cohorts included respectively 254 and 238 patients, followed up respectively 9 · 2 ± 4 · 8 and 7 · 6 ± 3 · 0 years. A blood sample collected during hospitalization was used for quantifying 4,668 proteins. Fifty proteins were significantly associated with long-term occurrence of HF with all-cause death as the competing event. k-means, an unsupervised clustering method, identified two groups of patients based on expression levels of the 50 proteins. Group 2 was significantly associated with a higher risk of HF in both cohorts. These results showed that a subset of 50 selected proteins quantified during hospitalization of MI patients is able to stratify and predict the long-term occurrence of HF.

C-Reactive Protein, Interleukin-6, Trimethylamine-N-Oxide, Syndecan-1, Nitric Oxide, and Tumor Necrosis Factor Receptor-1 in Heart Failure with Preserved Versus Reduced Ejection Fraction: a Meta-Analysis

PURPOSE OF REVIEW

The purpose of this review was to synthesize the evidence on non-traditional biomarkers from proteomic and metabolomic studies that may distinguish heart failure (HF) with preserved ejection fraction (HFpEF) from heart failure with reduced ejection fraction (HFrEF) and non-HF.

RECENT FINDINGS

Understanding the pathophysiology of HFpEF continues to be challenging. A number of inflammatory and metabolic biomarkers that have recently been suggested to be involved include C-reactive protein (CRP), interleukin-6 (IL-6), trimethylamine-N-oxide (TMAO), syndecan-1 (SDC-1), nitric oxide (NO), and tumor necrosis factor receptor-1 (TNFR-1). A systematic search was conducted using Medline, EMBASE, and Web of Science with search terms such as "HFpEF," "metabolomics," and "proteomics," and a meta-analysis was conducted. The results demonstrate significantly higher levels of TMAO, CRP, SDC-1, and IL-6 in HFpEF compared to controls without HF and significantly higher levels of TMAO and CRP in HFrEF compared to controls. The results further suggest that HFpEF might be distinguishable from HFrEF based on higher levels of IL-6 and lower levels of SDC-1 and NO. These data may reflect pathophysiological differences between HFpEF and HFrEF.

Blood pressure in heart failure management and prevention

Hypertension is a leading cause of heart failure and other cardiovascular diseases. Its role in the pathogenesis of heart failure with reduced ejection fraction (HFrEF) differs from that in heart failure with preserved ejection fraction (HFpEF). Moreover, rigorous blood pressure control may reduce the incidence of heart failure. However, once heart failure develops, prognosis is affected by blood pressure, which may differ between patients with and without heart failure. Therefore, the association between guideline-directed medical therapy (GDMT) for heart failure and its uptitration must be considered for blood pressure management and should not be overlooked. Heart failure medications affect the blood pressure and efficacy per baseline blood pressure value. This review discusses the potential mechanisms by which hypertension leads to HFrEF or HFpEF, the impact of hypertension on incident heart failure, and the recommended approaches for blood pressure management in patients with heart failure. Comparison between patients with and without heart failure regarding blood pressure The association between CV events and SBP is linear in patients without heart failure; however, it becomes J-shaped or inverse linear in those with heart failure. The management of BP, including optimal BP or pharmacotherapy, differs between the two populations. ACEi angiotensin-converting enzyme inhibitors, ARB angiotensin II receptor blockers; ARNi angiotensin receptor-neprilysin inhibitors, BB beta-blockers, BP blood pressure, CV cardiovascular, DASH Dietary Approaches to Stop Hypertension, GDMT guideline-directed medical therapy, HF heart failure, HFrEF heart failure with reduced ejection fraction, MRA mineralocorticoid receptor antagonists, SBP systolic blood pressure, SGLT2i sodium-glucose cotransporter 2 inhibitors.

Combination of Neutrophil-to-Lymphocyte and Platelet-to-Lymphocyte Ratios as a Novel Predictor of Cardiac Death in Patients With Acute Decompensated Heart Failure With Preserved Left Ventricular Ejection Fraction: A Multicenter Study

Background Neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) are novel inflammation markers. Their combined usefulness for estimating the prognosis of patients with heart failure with preserved ejection fraction (HFpEF) admitted for acute decompensated heart failure remains elusive. Methods and Results We investigated 1026 patients registered in the Prospective Multicenter Observational Study of Patients with Heart Failure with Preserved Ejection Fraction. Both NLR and PLR values were measured at the time of admission. Comorbidity burden was defined as the number of occurrences of 8 common comorbidities of HFpEF. The primary end point was cardiac death. The patients were stratified into 3 groups based on the optimal cut-off values of NLR and PLR on the receiver operating characteristic curve analysis for predicting cardiac death (low NLR and PLR, either high NLR or PLR, and both high NLR and PLR). After a median follow-up of 429 days, 195 patients died, with 85 of these deaths attributed to cardiac causes. An increased comorbidity burden was significantly associated with a higher proportion of patients with high NLR (>4.5) or PLR (>193), or both. High NLR and PLR values were independently associated with cardiac death, and a combination of both values was the strongest predictor (hazard ratio, 2.66 [95% CI, 1.51%-4.70%], P=0.0008). A significant difference was found in the rate of cardiac death among the 3 groups stratified by NLR and PLR values. Conclusions The combination of NLR and PLR is useful for the prediction of postdischarge cardiac death in patients with acute HFpEF. Registration URL: ClinicalTrials.gov; Unique identifier: UMIN000021831.

Assessing clinical and biomarker characteristics to optimize the benefits of sacubitril/valsartan in heart failure

Of the various medical therapies for heart failure (HF), sacubitril/valsartan is a first-in-class angiotensin receptor-neprilysin inhibitor that combines sacubitril, a pro-drug that is further metabolized to the neprilysin inhibitor sacubitrilat, and the angiotensin II type 1 receptor blocker valsartan. Inhibition of neprilysin and blockade of the angiotensin II type 1 receptor with sacubitril/valsartan increases vasoactive peptide levels, increasing vasodilation, natriuresis, and diuresis. Left ventricular ejection fraction (LVEF) is widely used to classify HF, to assist with clinical decision-making, for patient selection in HF clinical trials, and to optimize the benefits of sacubitril/valsartan in HF. However, as HF is a complex syndrome that occurs on a continuum of overlapping and changing phenotypes, patient classification based solely on LVEF becomes problematic. LVEF measurement can be imprecise, have low reproducibility, and often changes over time. LVEF may not accurately reflect inherent disease heterogeneity and complexity, and the addition of alternate criteria to LVEF may improve phenotyping of HF and help guide treatment choices. Sacubitril/valsartan may work, in part, by mechanisms that are not directly related to the LVEF. For example, this drug may exert antifibrotic and neurohumoral modulatory effects through inhibition or activation of several signaling pathways. In this review, we discuss markers of cardiac remodeling, fibrosis, systemic inflammation; activation of neurohormonal pathways, including the natriuretic system and the sympathetic nervous system; the presence of comorbidities; patient characteristics; hemodynamics; and HF signs and symptoms that may all be used to (1) better understand the mechanisms of action of sacubitril/valsartan and (2) help to identify subsets of patients who might benefit from treatment, regardless of LVEF.

Oxidative Stress as a Therapeutic Target of Cardiac Remodeling

Cardiac remodeling is defined as a group of molecular, cellular, and interstitial changes that clinically manifest as changes in the heart's size, mass, geometry, and function after different stimuli. It is important to emphasize that remodeling plays a pathophysiological role in the onset and progression of ventricular dysfunction and subsequent heart failure. Therefore, strategies to mitigate this process are critical. Different factors, including neurohormonal activation, can regulate the remodeling process and increase cell death, alterations in contractile and regulatory proteins, alterations in energy metabolism, changes in genomics, inflammation, changes in calcium transit, metalloproteases activation, fibrosis, alterations in matricellular proteins, and changes in left ventricular geometry, among other mechanisms. More recently, the role of reactive oxygen species and oxidative stress as modulators of remodeling has been gaining attention. Therefore, this review assesses the role of oxidative stress as a therapeutic target of cardiac remodeling.

From mid-range to mildly reduced ejection fraction heart failure: A call to treat

The historical classification of heart failure (HF) has considered two distinct subgroups, HF with reduced ejection fraction (HFrEF), generally classified as EF below 40%, and HF with preserved ejection fraction (HFpEF) variably classified as EF above 40%, 45% or 50%. One of the principal reasons behind this distinction was related to presence of effective therapy in HFrEF, but not in HFpEF. Recently the expanding knowledge in the specific subgroup of patient with a LVEF between 41% and 49% and the potential benefit of new therapies and of those used in patients with LVEF below 40%, has led to rename this group as HF with mildly reduced EF (HFmrEF). In this review we discuss the reasons behind this modification, we summarize the main characteristics of HFmrEF the similarities and differences with the two other EF categories, and finally we provide a comprehensive overview of the current available evidence supporting the treatment of patients with HFmrEF.

Short-Term Prognostic Efficacy of mGPS and LCS in Patients With Acute Heart Failure

Aim

Systemic inflammation plays an important role in the occurrence and development of acute heart failure. The modified Glasgow Prognostic Score (mGPS) and “lymphocyte C-reactive protein score” (LCS) are used to assess the inflammation levels in cancer patients. The purpose of this study was to assess the prognostic value of these two inflammation-related scoring systems in patients with acute heart failure.

Methods

Two hundred and fifty patients with acute heart failure were enrolled in this study. The mGPS and LCS scores were recorded after admission. All patients were divided into 2 groups: the death group and the survival group according to the 3-month follow-up results. The predictive values of mGPS and LCS were assessed using receiver-operating characteristic (ROC) analyses. Univariate and multivariate logistic analyses were used to evaluate the relationships between variables and endpoint.

Results

The levels of mGPS and LCS in the death group were significantly higher than those in the survival group (P < 0.05). The areas under the ROC curve of the mGPS and LCS for predicting death were 0.695 (95%CI: 0.567~0.823) and 0.736 (95%CI: 0.616~0.856), respectively. Multivariate analysis demonstrated that both LCS, LVEF and serum direct bilirubin were independent predictors of all-cause death, excluding mGPS.

Conclusions

Compared with mGPS, LCS is independently associated with short-term outcomes in patients with acute heart failure. LCS was a clinically promising and feasible prognostic scoring system for patients with acute heart failure.

Promise of sodium-glucose co-transporter-2 inhibitors in heart failure with mildly reduced ejection fraction

Heart failure with mildly reduced ejection fraction (HFmrEF) is associated with comparable poor outcomes as other subtypes of heart failure and remains a medical unmet need due to the paucity of effective therapies. According to large cardiovascular (CV) outcome trials in patients with heart failure, sodium–glucose co‐transporter‐2 inhibitors (SGLT2is) reduce CV mortality and hospitalizations for heart failure in patients with heart failure across the spectrum of left ventricular ejection fraction (LVEF). There has been a lack of dedicated trials in HFmrEF. However, several large outcome trials in heart failure that enrolled patients with HFmrEF could provide a hint on the role of SGLT2is in this subgroup. This review focuses on CV effects of three major SGLT2is—dapagliflozin, empagliflozin, and sotagliflozin—in patients with HFmrEF. A narrative review of trials investigating the efficacy of each medication in treating heart failure with LVEF > 40% is provided with a focus on their LVEF subgroup analyses. The purpose of this review is to discuss the current state of evidence regarding the potential of SGLT2is in HFmrEF management. Current limited evidence suggests that SGLT2is might be a favourable treatment modality for patients with HFmrEF to reduce hospitalization for heart failure and CV mortality. This conclusion needs to be further supported by clear HFmrEF subgroup analysis of the existing trials. Further outcome trials involving sufficient patients with different subtypes of HFmrEF are needed to confirm and assess CV benefits of SGLT2is in HFmrEF. Possible mechanisms by which SGLT2is exert their cardioprotective effect are also described briefly.

The Quantity of Epicardial Adipose Tissue in Patients Having Ablation for Atrial Fibrillation With and Without Heart Failure

The distribution of epicardial adipose tissue (EAT) across the spectrum of heart failure (HF) has yet to be fully elucidated. The present study investigated the distribution of EAT in an HF spectrum and its association with clinical and echocardiographic parameters. A total of 326 patients who underwent contrast-enhanced computed tomography before transcatheter atrial fibrillation ablation with and without HF symptoms, and a wide range of left ventricular (LV) ejection fractions (LVEF) were included. EAT mass was quantified on contrast-enhanced computed tomography using dedicated software. A total of 36 patients had HF with reduced LVEF (HFrEF) (11.0%), 46 had HF with mid-range LVEF (HFmrEF) (14.1%), 53 had HFpEF (16.3%), and 191 did not have HF symptoms (58.6%) and were considered controls. Patients with HFpEF had the largest EAT mass, significantly higher than the control group (128 ± 36 g vs 95 ± 35 g, p <0.001), the HFmrEF group (101 ± 37 g, p <0.001), and the HFrEF group (103 ± 37 g, p = 0.002). However, there were no differences in EAT mass between patients with HFrEF, HFmrEF, and controls. EAT was independently associated with E/e', LV mass index, and tricuspid regurgitation velocity. Male gender, body mass index, and C-reactive protein levels were independently associated with EAT. In conclusion, patients with HFpEF had more EAT than patients with HFmrEF, patients with HFpEF, and controls. EAT was associated with worse LV diastolic dysfunction, whereas C-reactive protein levels were independently associated with EAT, suggesting an active inflammatory component.

The cardiosplenic axis: the prognostic role of the spleen in heart failure

Despite the number of available methods to predict prognosis in patients with heart failure, prognosis remains poor, likely because of marked patient heterogeneity and varied heart failure etiologies. Thus, identification of novel prognostic indicators to stratify risk in patients with heart failure is of paramount importance. The spleen is emerging as a potential novel prognostic indicator for heart failure. In this article, we provide an overview of the current prognostic tools used for heart failure. We then introduce the spleen as a potential novel prognostic indicator, before outlining the structure and function of the spleen and introducing the concept of the cardiosplenic axis. This is followed by a focused discussion on the function of the spleen in the immune response and in hemodynamics, as well as a review of what is known about the usefulness of the spleen as an indicator of heart failure. Expert insight into the most effective spleen-related measurement indices for the prognostication of patients with heart failure is provided, and suggestions on how these could be measured in clinical practice are considered. In future, studies in humans will be required to draw definitive links between specific splenic measurements and different heart failure manifestations, as well as to determine whether splenic prognostic measurements differ between heart failure classes and etiologies. These contributions will provide a step forward in our understanding of the usefulness of the spleen as a prognostic predictor in heart failure.

Heart failure with preserved ejection fraction: key stumbling blocks for experimental drugs in clinical trials

INTRODUCTION

Heart failure with preserved ejection fraction (HFpEF) is a disease process with a high prevalence. Accounting for more than 50% of all heart failure cases, it carries a significant mortality. So far, there has been a lack of therapeutic options that truly show improvement in morbidity and mortality. Certain novel therapies have shown a decrease in heart failure hospitalizations, however, this beneficial effect was more pronounced for heart failure patients with mildly reduced ejection fraction (EF).

AREAS COVERED

This review summarizes the pathophysiology of the disease to help elucidate the differences between heart failure with reduced ejection fraction (HFrEF), and HFpEF, which could explain why therapies are successful in one (rather than the other). At the focus of this review are non-standardized nomenclature across major trials, the challenges of finding a therapeutic agent for such a heterogeneous population, and identification of specific phenotypes that have different outcomes and could be a target for future therapies.

EXPERT OPINION

Lack of standardized diagnostic criteria, associated with population heterogeneity, might explain why trials have failed to improve outcomes for patients with HFpEF. Standardizing phenotypes and recapitulating these phenotypes in animal models, as well as understanding the mechanisms of the disease at the molecular level could be the first steps in identifying promising therapeutic options.

Serum-Induced Expression of Brain Natriuretic Peptide Contributes to Its Increase in Patients with HFpEF

Brain natriuretic peptide (BNP) levels are increased in both patients with heart failure with preserved (HFpEF) and reduced ejection fraction (HFrEF), but the reasons for this remain unclear. Our purpose was to examine whether serum-induced BNP (iBNP) expression partly contributes to increased BNP in patients with HFpEF. BNP reporter cardiomyocytes from pBNP-luc-KI mice were stimulated with serum from patients with HFpEF or HFrEF (n = 114 and n = 82, respectively). Luciferase activity was examined as iBNP and the iBNP-to-BNP ratio was evaluated. Patient characteristics and clinical parameters were compared, and multivariate regression analysis was performed to determine independent predictors of the iBNP-to-BNP ratio. Female sex and frequencies of atrial fibrillation, hypertension and the use of a calcium channel blocker (CCB) were higher in HFpEF. The iBNP-to-BNP ratio was significantly higher in HFpEF (26.9) than in HFrEF (16.1, p < 0.001). Multivariate regression analysis identified the existence of HFpEF as an independent predictor of the iBNP-to-BNP ratio after adjusting for all other measurements (β = 0.154, p = 0.032). Age, hemoglobin, CCB usage and deceleration time were also independent predictors (β = 0.167, p = 0.025; β = 0.203, p = 0.006; β = 0.138, p = 0.049; and β = 0.143, p = 0.049, respectively). These results indicate that the elevated BNP in patients with HFpEF is partly due to iBNP from the heart.

Heart failure with mid-range or mildly reduced ejection fraction

Left ventricular ejection fraction (EF) remains the major parameter for diagnosis, phenotyping, prognosis and treatment decisions in heart failure. The 2016 ESC heart failure guidelines introduced a third EF category for an EF of 40-49%, defined as heart failure with mid-range EF (HFmrEF). This category has been largely unexplored compared with heart failure with reduced EF (HFrEF; defined as EF <40% in this Review) and heart failure with preserved EF (HFpEF; defined as EF ≥50%). The prevalence of HFmrEF within the overall population of patients with HF is 10-25%. HFmrEF seems to be an intermediate clinical entity between HFrEF and HFpEF in some respects, but more similar to HFrEF in others, in particular with regard to the high prevalence of ischaemic heart disease in these patients. HFmrEF is milder than HFrEF, and the risk of cardiovascular events is lower in patients with HFmrEF or HFpEF than in those with HFrEF. By contrast, the risk of non-cardiovascular adverse events is similar or greater in patients with HFmrEF or HFpEF than in those with HFrEF. Evidence from post hoc and subgroup analyses of randomized clinical trials and a trial of an SGLT1-SGLT2 inhibitor suggests that drugs that are effective in patients with HFrEF might also be effective in patients with HFmrEF. Although the EF is a continuous measure with considerable variability, in this comprehensive Review we suggest that HFmrEF is a useful categorization of patients with HF and shares the most important clinical features with HFrEF, which supports the renaming of HFmrEF to HF with mildly reduced EF.

Relationship of ejection fraction and natriuretic peptide trajectories in heart failure with baseline reduced and mid-range ejection fraction

BACKGROUND

The prognostic importance of trajectories of neurohormones relative to left ventricular function over time in heart failure with reduced and mid-range EF (HFrEF and HFmrEF) is poorly defined.

OBJECTIVE

To evaluate left ventricular ejection fraction (LVEF) and B-type natriuretic peptide (BNP) trajectories in HFrEF and HFmrEF.

METHODS

Analyses of LVEF and BNP trajectories after incident HF admissions presenting with abnormal LV systolic function were performed using 3 methods: a Cox proportional hazards model with time-varying covariates, a dual longitudinal-survival model with shared random effects, and an unsupervised analysis to capture 3 discrete trajectories for each parameter.

RESULTS

Among 1,158 patients (68.9 ± 13.0 years, 53.3% female), both time-varying LVEF measurements (P=.001) and log-transformed BNP measurements (p-values=2 × 10^-16) were independently associated with survival during 6 years after covariate adjustment. In the dual longitudinal/survival model, both LVEF and BNP trajectories again were independently associated with survival (P<.0001 in each model); however, LVEF was more dynamic than BNP (P <.0001 for time covariate in LVEF longitudinal model versus P=.88 for the time covariate in BNP longitudinal model). In the unsupervised analysis, 3 discrete LVEF trajectories (dividing the cohort into approximately thirds) and 3 discrete BNP trajectories were identified. Discrete LVEF and BNP trajectories had independent prognostic value in Kaplan-Meier analyses (P<.0001), and substantial membership variability across BNP and LVEF trajectories was noted.

CONCLUSION

Although LVEF trajectories have greater temporal variation, BNP trajectories provide additive prognostication and an even stronger association with survival times in heart failure patients with abnormal LV systolic function.

Deep Learning Predicts Heart Failure With Preserved, Mid-Range, and Reduced Left Ventricular Ejection Fraction From Patient Clinical Profiles

Background: Left ventricular ejection fraction (LVEF) is the gold standard for evaluating heart failure (HF) in coronary artery disease (CAD) patients. It is an essential metric in categorizing HF patients as preserved (HFpEF), mid-range (HFmEF), and reduced (HFrEF) ejection fraction but differs, depending on whether the ASE/EACVI or ESC guidelines are used to classify HF. Objectives: We sought to investigate the effectiveness of using deep learning as an automated tool to predict LVEF from patient clinical profiles using regression and classification trained models. We further investigate the effect of utilizing other LVEF-based thresholds to examine the discrimination ability of deep learning between HF categories grouped with narrower ranges. Methods: Data from 303 CAD patients were obtained from American and Greek patient databases and categorized based on the American Society of Echocardiography and the European Association of Cardiovascular Imaging (ASE/EACVI) guidelines into HFpEF (EF > 55%), HFmEF (50% ≤ EF ≤ 55%), and HFrEF (EF < 50%). Clinical profiles included 13 demographical and clinical markers grouped as cardiovascular risk factors, medication, and history. The most significant and important markers were determined using linear regression fitting and Chi-squared test combined with a novel dimensionality reduction algorithm based on arc radial visualization (ArcViz). Two deep learning-based models were then developed and trained using convolutional neural networks (CNN) to estimate LVEF levels from the clinical information and for classification into one of three LVEF-based HF categories. Results: A total of seven clinical markers were found important for discriminating between the three HF categories. Using statistical analysis, diabetes, diuretics medication, and prior myocardial infarction were found statistically significant (p < 0.001). Furthermore, age, body mass index (BMI), anti-arrhythmics medication, and previous ventricular tachycardia were found important after projections on the ArcViz convex hull with an average nearest centroid (NC) accuracy of 94%. The regression model estimated LVEF levels successfully with an overall accuracy of 90%, average root mean square error (RMSE) of 4.13, and correlation coefficient of 0.85. A significant improvement was then obtained with the classification model, which predicted HF categories with an accuracy ≥93%, sensitivity ≥89%, 1-specificity <5%, and average area under the receiver operating characteristics curve (AUROC) of 0.98. Conclusions: Our study suggests the potential of implementing deep learning-based models clinically to ensure faster, yet accurate, automatic prediction of HF based on the ASE/EACVI LVEF guidelines with only clinical profiles and corresponding information as input to the models. Invasive, expensive, and time-consuming clinical testing could thus be avoided, enabling reduced stress in patients and simpler triage for further intervention.

Differences in the Biomarker Profile of De Novo Acute Heart Failure versus Decompensation of Chronic Heart Failure

The perception of acute heart failure (AHF) as a single entity is increasingly outdated, as distinct patient profiles can be discerned. Key heart failure (HF) studies have previously highlighted the difference in both the course and prognosis of de novo AHF and acute decompensated chronic HF (ADHF). Accordingly, distinct AHF profiles with differing underlying pathophysiologies of disease progression can be shown. We compared a range of selected biomarkers in order to better describe the profile of de novo AHF and ADHF, including the inter alia—serum lactate, bilirubin, matrix metallopeptidase 9 (MMP-9), follistatin, intercellular adhesion molecule 1 (ICAM-1), lipocalin and galectin-3. The study comprised 248 AHF patients (de novo = 104), who were followed up for one year. The biomarker data of the de novo AHF and ADHF profiles was then compared in order to link biomarkers to their prognosis. Our study demonstrated that, although there are similarities between each patient profile, key biomarker differences do exist—predominantly in terms of NTproBNP, serum lactate, bilirubin, ICAM-1, follistatin, ferritin and sTfR (soluble transferrin receptor). ADHF tended to have compromised organ function and higher risks of both one-year mortality and composite endpoint (one-year mortality or rehospitalization for heart failure) hazard ratios (HR) (95% CI): 3.4 (1.8–6.3) and 2.8 (1.6–4.6), respectively, both p < 0.0001. Among the biomarkers of interest: sTfR HR (95% CI): 1.4 (1.04–1.8), NGAL_(log) (neutrophil gelatinase-associated lipocalin) HR (95% CI): 2.0 (1.3–3.1) and GDF-15_(log) (growth/differentiation factor-15) HR (95% CI): 4.0 (1.2–13.0) significantly impacted the one-year survival, all p < 0.05.

Similarities and Differences Between HFmrEF and HFpEF

The new guidelines classify heart failure (HF) into three subgroups based on the ejection fraction (EF): HF with reduced EF (HFrEF), HF with mid-range EF (HFmrEF), and HF with preserved EF (HFpEF). The new guidelines regarding the declaration of HFmrEF as a unique phenotype have achieved the goal of stimulating research on the basic characteristics, pathophysiology, and treatment of HF patients with a left ventricular EF of 40-49%. Patients with HFmrEF have more often been described as an intermediate population between HFrEF and HFpEF patients; however, with regard to etiology and clinical indicators, they are more similar to the HFrEF population. Concerning clinical prognosis, they are closer to HFpEF because both populations have a good prognosis and quality of life. Meanwhile, growing evidence indicates that HFmrEF and HFpEF show heterogeneity in presentation and pathophysiology, and the emergence of this heterogeneity often plays a crucial role in the prognosis and treatment of the disease. To date, the exact mechanisms and effective treatment strategies of HFmrEF and HFpEF are still poorly understood, but some of the current evidence, from observational studies and post-hoc analyses of randomized controlled trials, have shown that patients with HFmrEF may benefit more from HFrEF treatment strategies, such as beta-blockers, angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, mineralocorticoid receptor antagonists, and sacubitril/valsartan. This review summarizes available data from current clinical practice and mechanistic studies in terms of epidemiology, etiology, clinical indicators, mechanisms, and treatments to discuss the potential association between HFmrEF and HFpEF patients.

Pulmonary Hypertension in Patients With Heart Failure With Mid-Range Ejection Fraction

Pulmonary hypertension (PH) is common in patients with heart failure (HF). The role of PH in patients with HF with reduced (HFrEF) and preserved (HFpEF) left ventricular ejection fraction (LVEF) has been extensively characterized during the last years. In contrast, the pathophysiology of HF with mid-range LVEF (HFmrEF), and in particular the role of PH in this context, are largely unknown. There is a paucity of data in this field, and the prevalence of PH, the underlying mechanisms, and the optimal therapy are not well-defined. Although often studied together there is increasing evidence that despite similarities with both HFrEF and HFpEF, HFmrEF also differs from both entities. The present review provides a summary of the current concepts of the mechanisms and clinical impact of PH in patients with HFmrEF, a proposal for the non-invasive and invasive diagnostic approach required to define the pathophysiology of PH and its management, and a discussion of future directions based on insights from mechanistic studies and randomized trials. We also provide an outlook regarding gaps in evidence, future clinical challenges, and research opportunities.

Heart Failure With Mid-range Ejection Fraction: A Distinctive Subtype or a Transitional Stage?

Heart failure with mid-range ejection fraction (HFmrEF) was first proposed by Lam and Solomon in 2014, and was listed as a new subtype of heart failure (HF) in 2016 European Society of Cardiology guidelines. Since then, HFmrEF has attracted an increasing amount of attention, and the number of related studies on this topic has grown rapidly. The diagnostic criteria on the basis of left ventricular ejection fraction (LVEF) are straightforward; however, LVEF is not a static parameter, and it changes dynamically during the course of HF. Thus, HFmrEF may not be an independent disease with a uniform pathophysiological process, but rather a collection of patients with different characteristics. HFmrEF is often associated with various cardiovascular and non-cardiovascular diseases. Thus, the pathophysiological mechanisms of HFmrEF are particularly complex, and its clinical phenotypes are diverse. The complexity and heterogeneity of HFmrEF may be one reason for inconsistent results between clinical studies. In fact, whether HFmrEF is a distinctive subtype or a transitional stage between HF with reduced ejection fraction (HFrEF) and HF with preserved ejection fraction (HFpEF) is controversial. In this review, we discuss the clinical characteristics, treatment and prognosis of patients with HFmrEF, as well as the differences among HFmrEF, HFrEF, and HFpEF.

Heart failure with mid-range ejection fraction and the effect of β-blockers after acute myocardial infarction

There is currently an ongoing debate about the 'grey area' of heart failure with mid-range ejection fraction (HFmrEF). We evaluated characteristics, prognosis, and the effect of β-blockers on clinical outcomes in patients with HFmrEF after acute myocardial infarction (AMI). We included a total of 10,785 patients and divided them into three groups: EF 40-49% (HFmrEF; n = 2717; reference); EF < 40% (reduced EF [HFrEF]; n = 1194); and EF ≥ 50% (preserved EF [HFpEF]; n = 6874). The primary outcome was 2-year all-cause mortality. HFmrEF was intermediate between HFrEF and HFpEF for baseline characteristics. The risk of all-cause mortality was lower for HFmrEF patients compared to HFrEF patients (adjusted hazard ratio [HR] 0.710; 95% confidence interval [CI] 0.544-0.927; P = 0.012). However, HFmrEF patients tended to be at higher risk for 2-year all-cause mortality than HFpEF patients (adjusted HR 1.235; 95% CI 0.989-1.511; P = 0.090). β-blockers were associated with reductions in all-cause mortality for the entire cohort (adjusted HR 0.760; 95% CI 0.592-0.975; P = 0.031). β-blockers were effective in patients with HFrEF (adjusted HR 0.667; 95% CI 0.471-0.944; P = 0.022), tended to be effective in patients with HFmrEF (adjusted HR 0.665; 95% CI 0.426-1.038; P = 0.072), but not effective in patients with HFpEF (adjusted HR 0.852; 95% CI 0.548-1.326; P = 0.478; interaction P = 0.026). In conclusion, clinical profiles and prognosis of patients with post-AMI HFmrEF are largely intermediate between HFrEF and HFpEF. β-blockers reduced or tended to reduce 2-year all-cause mortality in patients with HFrEF or HFmrEF, respectively, but not those with HFpEF after AMI.

Are HFpEF and HFmrEF So Different? The Need to Understand Distinct Phenotypes

Traditionally, patients with heart failure (HF) are divided according to ejection fraction (EF) threshold more or <50%. In 2016, the ESC guidelines introduced a new subgroup of HF patients including those subjects with EF ranging between 40 and 49% called heart failure with midrange EF (HFmrEF). This group is poorly represented in clinical trials, and it includes both patients with previous HFrEF having a good response to therapy and subjects with initial preserved EF appearance in which systolic function has been impaired. The categorization according to EF has recently been questioned because this variable is not really a representative of the myocardial contractile function and it could vary in relation to different hemodynamic conditions. Therefore, EF could significantly change over a short-term period and its measurement depends on the scan time course. Finally, although EF is widely recognized and measured worldwide, it has significant interobserver variability even in the most accredited echo laboratories. These assumptions imply that the same patient evaluated in different periods or by different physicians could be classified as HFmrEF or HFpEF. Thus, the two HF subtypes probably subtend different responses to the underlying pathophysiological mechanisms. Similarly, the adaptation to hemodynamic stimuli and to metabolic alterations could be different for different HF stages and periods. In this review, we analyze similarities and dissimilarities and we hypothesize that clinical and morphological characteristics of the two syndromes are not so discordant.

Pathophysiology and Therapeutic Approaches to Acute Decompensated Heart Failure

Acute decompensated heart failure (ADHF) is one of the leading admission diagnoses worldwide, yet it is an entity with incompletely understood pathophysiology and limited therapeutic options. Patients admitted for ADHF have high in-hospital morbidity and mortality, as well as frequent rehospitalizations and subsequent cardiovascular death. This devastating clinical course is partly due to suboptimal medical management of ADHF with persistent congestion upon hospital discharge and inadequate predischarge initiation of life-saving guideline-directed therapies. While new drugs for the treatment of chronic HF continue to be approved, there has been no new therapy approved for ADHF in decades. This review will focus on the current limited understanding of ADHF pathophysiology, possible therapeutic targets, and current limitations in expanding available therapies in light of the unmet need among these high-risk patients.

Rationale for the Use of Pirfenidone in Heart Failure With Preserved Ejection Fraction

Heart failure with preserved ejection fraction (HFpEF) is a major public health problem with growing prevalence and poor outcomes, mainly due to the lack of an effective treatment. HFpEF pathophysiology is heterogeneous and complex. Recently a “new paradigm” has been proposed, suggesting that cardiovascular and non-cardiovascular coexisting comorbidities lead to a systemic inflammatory state, perturbing the physiology of the endothelium and the perivascular environment and engaging molecular pathways that ultimately converge to myocardial fibrosis. If inflammation and fibrosis are the “fil rouge” in the heterogeneous spectrum of HFpEF, anti-fibrotic and anti-inflammatory drugs may have a role in its treatment. Pirfenidone is an orally bioavailable drug with antifibrotic and anti-inflammatory properties already approved for the treatment of idiopathic pulmonary fibrosis. Pirfenidone has been recently tested in animal models of myocardial fibrosis with promising results. Here we will review the rationale underlying the potential therapeutic effect of Pirfenidone in HFpEF.

Current gaps in HFpEF trials: Time to reconsider patients' selection and to target phenotypes

Heart Failure with preserved Ejection Fraction (HFpEF) is an increasingly prevalent clinical condition associated with cardiovascular aging, characterized by different pathophysiological mechanisms and poor outcomes. In this manuscript, we analysed the main differences in terms of updated diagnostic criteria and patients' selection in the most recent HFpEF trials. Recent algorithm purposed for HFpEF diagnosis, does not reflect common criteria adopted in clinical trials. Patients included in the larger studies experienced different characteristics in terms of clinical presentation and echocardiographic features. Current concerns complicate results interpretation and could hypothesize different stages of disease progression, rather than different cardiac phenotypes. Both the lack of diagnostic standardization and the population heterogeneity, might explain why trials investigating the effects of different therapeutic interventions failed to show improved outcomes for patients with HFpEF. Accordingly, we propose to exceed current view mainly based on the morphological adaptations evaluating patients' characterisation, their cardiovascular risk, associated diseases, and structural features consistent with disease progression. Detailed clinical, imaging and biological characterisation of this population, along with the identification of mechanisms linked with disease progression and prognosis, would allow for tailored treatments and provide important mechanistic insights into the complex HFpEF pathophysiology.

Role of confirmed and potential predictors of an unfavorable outcome in heart failure in everyday clinical practice

Heart failure (HF) is the only cardiovascular disease with an ever increasing incidence. HF, through reduced functional capacity, frequent exacerbations of disease, and repeated hospitalizations, results in poorer quality of life, decreased work productivity, and significantly increased costs of the public health system. The main challenge in the treatment of HF is the availability of reliable prognostic models that would allow patients and doctors to develop realistic expectations about the prognosis and to choose the appropriate therapy and monitoring method. At this moment, there is a lack of universal parameters or scales on the basis of which we could easily capture the moment of deterioration of HF patients’ condition. Hence, it is crucial to identify such factors which at the same time will be widely available, cheap, and easy to use. We can find many studies showing different predictors of unfavorable outcome in HF patients: thorough assessment with echocardiography imaging, exercise testing (e.g., 6-min walk test, cardiopulmonary exercise testing), and biomarkers (e.g., N-terminal pro-brain type natriuretic peptide, high-sensitivity troponin T, galectin-3, high-sensitivity C-reactive protein). Some of them are very promising, but more research is needed to create a specific panel on the basis of which we will be able to assess HF patients. At this moment despite identification of many markers of adverse outcomes, clinical decision-making in HF is still predominantly based on a few basic parameters, such as the presence of HF symptoms (NYHA class), left ventricular ejection fraction, and QRS complex duration and morphology.

Proteomic Signatures of Heart Failure in Relation to Left Ventricular Ejection Fraction

BACKGROUND

There is a growing recognition of the inherent limitations of the use of the left ventricular ejection fraction (LVEF) to accurately phenotype patients with heart failure (HF).

OBJECTIVES

The authors sought to identify unique proteomic signatures for patients with HF with reduced ejection fraction (HFrEF), HF with a midrange LVEF (HFmrEF), and HF with preserved ejection fraction (HFpEF), as well as to identify molecular differences between patients with ischemic and nonischemic HF.

METHODS

We used high-content aptamer-based proteomics technology (SOMAscan) to interrogate the blood proteome of age- and sex-matched patients with HF within different LVEF groups.

RESULTS

Within the Washington University Heart Failure Registry, we identified age/sex-matched patients within 3 LVEF categories: HFrEF (LVEF <40%), HFmrEF (LVEF 40% to 50%), and HFpEF (LVEF >50%). We found that patients with HFrEF, HFmrEF, and HFpEF had unique variations in circulating proteins that reflected distinct biological pathophysiologies. Bioinformatics analysis revealed that there were biological themes that were unique to patients with HFrEF, HFpEF, or HFmrEF. Comparative analyses of patients with HFmrEF with improved LVEF and patients with HFmrEF with unchanged LVEF revealed marked differences between these 2 patient populations and indicated that patients with recovered LVEF are more similar to patients with HFpEF than to patients with HFrEF. Moreover, there were marked differences in the proteomic signatures of patients with ischemic and nonischemic HF.

CONCLUSIONS

Viewed together, these findings suggest that it may be possible to use high-content multiplexed proteomics assays in combination with the clinical assessment of LVEF to more accurately identify clinical phenotypes of patients with HF.

Treatment of Heart Failure with Mid-Range Ejection Fraction: What Is the Evidence

In this review, we briefly outline our current knowledge on the epidemiology, outcomes, and pathophysiology of heart failure (HF) with mid-range ejection fraction (HFmrEF), and discuss in more depth the evidence on current treatment options for this group of patients. In most studies, the clinical background of patients with HFmrEF is intermediate between that of patients with HF and reduced ejection fraction (HFrEF) and patients with HF and preserved ejection fraction (HFpEF) in terms of demographics and comorbid conditions. However, the current evidence, stemming from observational studies and post hoc analyses of randomized controlled trials, suggests that patients with HFmrEF benefit from medications that target the neurohormonal axes, a pathophysiological behavior that resembles that of HFrEF. Use of β-blockers, angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, mineralocorticoid receptor antagonists, and sacubitril/valsartan is reasonable in patients with HFmrEF, whereas evidence is currently scarce for other therapies. In clinical practice, patients with HFmrEF are treated more like HFrEF patients, potentially because of history of systolic dysfunction that has partially recovered. Assessment of left ventricular systolic function with contemporary noninvasive modalities, e.g., echocardiographic strain imaging, is promising for the selection of patients with HFmrEF who will benefit from neurohormonal antagonists and other HFrEF-targeted therapies.

Metabolic Processes are Potential Biological Processes Distinguishing Nonischemic Dilated Cardiomyopathy from Ischemic Cardiomyopathy: A Clue from Serum Proteomics

BACKGROUND

Ischemic cardiomyopathy (ICM) and nonischemic dilated cardiomyopathy (DCM) are the two most common causes of heart failure. However, our understanding of the specific proteins and biological processes distinguishing DCM from ICM remains insufficient.

MATERIALS AND METHODS

The proteomics analyses were performed on serum samples from ICM (n=5), DCM (n=5), and control (n=5) groups. Proteomics and bioinformatics analyses, including weighted gene co-expression network analysis (WGCNA) and gene set enrichment analysis (GSEA), were performed to identify the hub circulating proteins and the hub biological processes in ICM and DCM.

RESULTS

The analysis of differentially expressed proteins and WGCNA identified the hub circulating proteins in ICM (GAPDH, CLSTN1, VH3, CP, and ST13) and DCM (one downregulated protein, FGG; 18 upregulated proteins, including HEL-S-276, IGK, ALDOB, HIST1H2BJ, HEL-S-125m, RPLP2, EL52, NCAM1, P4HB, HEL-S-99n, HIST1H4L, HIST2H3PS2, F8, ERP70, SORD, PSMA3, PSMB6, and PSMA6). The mRNA expression of the heart specimens from GDS651 validated that ALDOB, GAPDH, RPLP2, and IGK had good abilities to distinguish DCM from ICM. In addition, GSEA results showed that cell proliferation and differentiation were the hub biological processes related to ICM, while metabolic processes and cell signaling transduction were the hub biological processes associated with DCM.

CONCLUSION

The present study identified five dysregulated hub circulating proteins among ICM patients and 19 dysregulated hub circulating proteins among DCM patients. Cell proliferation and differentiation were significantly enriched in ICM. Metabolic processes were strongly enhanced in DCM and may be used to distinguish DCM from ICM.

The predictive value of global longitudinal strain in patients with heart failure mid-range ejection fraction

BACKGROUND

Heart failure (HF) with mid-range ejection fraction (HFmrEF) is defined as HF with a left ventricular (LV) ejection fraction (LVEF) of 41-49%. However, the change in LV function and the subsequent prognosis in these patients remain unclear. We aimed to investigate whether LV global longitudinal strain (LV GLS) could differentiate the changes in LVEF and predict the clinical outcomes in patients with HFmrEF.

METHODS

According to the changes in LVEF on follow-up echocardiography, 273 outpatients with HFmrEF were divided into 3 groups: HFwEF (HF with worse EF: <40%), HFsEF (HF with similar EF: 40-49%), and HFrecEF (HF with recovered EF: >50%). Further, the LV GLS at diagnosis was evaluated.

RESULTS

The average follow-up duration was 31 months. Among patients with HFmrEF, the more impaired the LV GLS at baseline, the higher probability of HFwEF development. In comparison with patients with HFwEF and HFsEF, those with HFrecEF had a lower risk of hospitalization for HF. At a cut-off value of -11%, LV GLS differentiated the subsequent risk of cardiovascular death in patients with HFmrEF. In Cox regression, patients with LV GLS >-11% had a high risk of cardiovascular death.

CONCLUSION

In patients with HFmrEF, LV GLS is associated with LVEF changes and subsequent cardiovascular death. Patients with HFrecEF had a lower risk of hospitalization for HF.

Congestion occurrence and evaluation in acute heart failure scenario: time to reconsider different pathways of volume overload

Although congestion is considered to be the main reason for hospital admission in patients with acute heart failure, a simplistic view considering idro saline retention and total body volume accumulation did not provide convincing data. Clinical congestion occurrence is often the tip of the iceberg of several different mechanisms ranging from increased filling pressure to extravascular fluid accumulation and blood flow redistribution. Therefore, the clinical evaluation is often restricted to a simple physical examination including few and inaccurate signs and symptoms. This superficial approach has led to contradictory data and patients have not been evaluated according to a more realistic clinical scenario. The integration with new diagnostic ultrasonographic and laboratory tools would substantially improve these weaknesses. Indeed, congestion could be assessed by following the most recognized HF subtypes including primitive cardiac defect, presence of right ventricular dysfunction, and organ perfusion. Moreover, there is a tremendous gap regarding the interchangeable concept of fluid retention and redistribution used with a univocal meaning. Overall, congestion assessment should be revised, considering it as either central, peripheral, or both. In this review, we aim to provide different evidence regarding the concept of congestion starting from the most recognized pathophysiological mechanisms of AHF decompensation. We highlight the fact that a better knowledge of congestion is a challenge for future investigation and it could lead to significant advances in HF treatment.

What Is the Role of the Inflammation in the Pathogenesis of Heart Failure?

PURPOSE OF REVIEW

In heart failure, whether it is associated with reduced or preserved ejection fraction, the immune system is activated and contributes to heart remodeling and impaired function.

RECENT FINDINGS

Studies indicate that cells of the immune system not only play a role in the pathology but are also critical regulators of heart function. Knowledge about the role of the immune system driving heart failure will lead to the development of new targets to this system, particularly in those patients that, despite the apparent wellness, relapse and worsen. In this review, we will address the diverse mechanisms that trigger inflammation and their impact on heart failure progression.

Proteomic Signatures During Treatment in Different Stages of Heart Failure

Background:

Proteomics have already provided novel insights into the pathophysiology of heart failure (HF) with reduced ejection fraction. Previous studies have evaluated cross-sectional protein signatures of HF, but few have characterized proteomic changes following HF with reduced ejection fraction treatment with ARNI (angiotensin receptor/neprilysin inhibitor) therapy or left ventricular assist devices.

Methods:

In this retrospective omics study, we performed targeted proteomics (N=625) of whole blood sera from patients with American College of Cardiology/American Heart Association stage D (N=29) and stage C (N=12) HF using proximity extension assays. Samples were obtained before and after (median=82 days) left ventricular assist device implantation (stage D; primary analysis) and ARNI therapy initiation (stage C; matched reference). Oblique principal component analysis and point biserial correlations were used for feature extraction and selection; standardized mean differences were used to assess within and between-group differences; and enrichment analysis was used to generate and cluster Gene Ontology terms.

Results:

Core sets of proteins were identified for stage C (N=9 proteins) and stage D (N=18) HF; additionally, a core set of 5 shared HF proteins (NT-proBNP [N-terminal pro-B type natriuretic peptide], ESM [endothelial cell-specific molecule]-1, cathepsin L1, osteopontin, and MCSF-1) was also identified. For patients with stage D HF, moderate (δ, 0.40–0.60) and moderate-to-large (δ, 0.60–0.80) sized differences were observed in 8 of their 18 core proteins after left ventricular assist devices implantation. Additionally, specific protein groups reached concentration levels equivalent ( g <0.10) to stage C HF after initiation on ARNI therapy.

Conclusions:

HF with reduced ejection fraction severity associates with distinct proteomic signatures that reflect underlying disease attributes; these core signatures may be useful for monitoring changes in cardiac function following initiation on ARNI or left ventricular assist device implantation.