Multiple biomarker strategies for risk stratification in heart failure

The role of biomarkers in the prognosis and risk stratification in heart failure: A systematic review

Acute heart failure (AHF) episodes are marked by high rates of morbidity and mortality during the episode and minimal advancements in its care. Multiple biomarker monitoring is now a crucial supplementary technique in the therapy of AHF. A scientific literature search was conducted by assessing and evaluating the most pertinent research that has been published, including original papers and review papers with the use of PubMed, Medline, and Cochrane databases. Established biomarkers like natriuretic peptides (BNP, NT-proBNP) and cardiac troponins play crucial roles in diagnostic and prognostic evaluation. Emerging biomarkers such as microRNAs, osteopontin, galectin-3, ST2, and GDF-15 show promise in enhancing risk stratification and predicting adverse outcomes in HF. However, while these biomarkers offer valuable insights, their clinical utility requires further validation and integration into practice. Continued research into novel biomarkers holds promise for early HF detection and risk assessment, potentially mitigating the global burden of HF. Understanding the nuances of biomarker utilization is crucial for their effective incorporation into clinical practice, ultimately improving HF management and patient care.

sST2 and Big ET-1 as Alternatives of Multi-Biomarkers Strategies for Prognosis Evaluation in Patients Hospitalized with Heart Failure

Objective

To identify biomarkers with independent prognostic value and investigate the prognostic value of multiple biomarkers in combination in patients hospitalized with heart failure.

Methods

A total of 884 consecutive patients hospitalized with heart failure from 2015 to 2017 were enrolled. Twelve biomarkers were measured on admission, and the relationships between biomarkers and outcomes were assessed.

Results

During the median follow-up of 913 days, 291 patients (32.9%) suffered from primary endpoint events. Soluble suppression of tumorigenicity-2 (sST2) (per log [unit] increase, adjusted HR [95% CI]: 1.39 [1.13,1.72], P = 0.002) and big endothelin-1 (big ET-1) (per log [unit] increase, adjusted HR [95% CI]: 1.56 [1.23,1.97], P < 0.001) remained independent predictors of primary endpoint event after adjusting for other predictors including N-terminal pro-B-type natriuretic peptide (NT-proBNP) and high-sensitivity cardiac troponin T (hs-cTnT). Both sST2 (C-statistic: 0.810 vs 0.801, P = 0.005, and 0.832 vs 0.826, P = 0.024, respectively) and big ET-1 (C-statistic: 0.829 vs 0.801, P = 0.001, and 0.843 vs 0.826, P < 0.001, respectively) significantly improved the predictive value for primary endpoint event at 1 year and 3 years. However, only big ET-1 (C-statistic: 0.852 vs 0.846, P = 0.014) significantly improved the predictive value at 3 months when added to clinical predictors and known biomarkers. According to the number of elevated biomarkers (including NT-proBNP, hs-cTnT, sST2, and big ET-1), patients with three or more elevated biomarkers had a higher risk of primary endpoint event compared to those with two elevated biomarkers (P = 0.001), as well as in patients with two elevated biomarkers compared to those with one elevated biomarker (P = 0.004). However, the risk of primary endpoint event was comparable between patients with one elevated biomarker and those with no elevated biomarker (P = 0.582).

Conclusion

Multiple biomarkers in combination could provide a better prognostic value than a single biomarker. sST2 and big ET-1 could act as alternatives of multi-biomarkers strategies for prognosis evaluation beyond NT-proBNP and hs-cTnT in patients hospitalized with heart failure.

Incremental prognostic value of biomarkers in PARADIGM-HF

AIMS

It is uncertain how much candidate biomarkers improve risk prediction when added to comprehensive models including routinely collected clinical and laboratory variables in heart failure.

METHODS AND RESULTS

Aldosterone, cystatin C, high-sensitivity troponin T (hs-TnT), galectin-3, growth differentiation factor-15 (GDF-15), kidney injury molecule-1, matrix metalloproteinase-2 and -9, soluble suppression of tumourigenicity-2, tissue inhibitor of metalloproteinase-1 (TIMP-1) and urinary albumin to creatinine ratio were measured in 1559 of PARADIGM-HF participants. We tested whether these biomarkers, individually or collectively, improved the performance of the PREDICT-HF prognostic model, which includes clinical, routine laboratory, and natriuretic peptide data, for the primary endpoint and cardiovascular and all-cause mortality. The mean age of participants was 67.3 ± 9.9 years, 1254 (80.4%) were men and 1103 (71%) were in New York Heart Association class II. During a mean follow-up of 30.7 months, 300 patients experienced the primary outcome and 197 died. Added individually, only four biomarkers were independently associated with all outcomes: hs-TnT, GDF-15, cystatin C and TIMP-1. When all biomarkers were added simultaneously to the PREDICT-HF models, only hs-TnT remained an independent predictor of all three endpoints. GDF-15 also remained predictive of the primary endpoint; TIMP-1 was the only other predictor of both cardiovascular and all-cause mortality. Individually or in combination, these biomarkers did not lead to significant improvements in discrimination or reclassification.

CONCLUSIONS

None of the biomarkers studied individually or collectively led to a meaningful improvement in the prediction of outcomes over what is provided by clinical, routine laboratory, and natriuretic peptide variables.

Global historical retrospect and future prospects on biomarkers of heart failure: A bibliometric analysis and science mapping

Introduction

Heart failure is a rapidly growing public health problem and has become a major cause of hospitalization in middle-aged and older adults. Biomarkers are clinically important in managing heart failure and have attracted more attention from researchers in recent years. This study aimed to evaluate the global research of heart failure biomarkers by bibliometrics and to identify the hot spots and perspectives for further advancement.

Methods

Selection of relevant documents was from the Web of Science Core Collection. Microsoft Excel, VOSviewer, SciMA, and CiteSpace software were used for bibliometric analysis.

Results

As of October 29, 2021, 5,978 documents for heart failure biomarkers have been identified from 1989 to 2021. European Journal of Heart Failure and Circulation respectively ranked first in terms of the number of publications and the number of co-citations. A total of 5,698 institutions from 90 countries participated in these publications, with the USA leading with 2,045 documents. The most productive institution was Harvard University. Januzzi, J.L. and Maisel, A.S. were the most productive and most cited authors respectively. Natriuretic peptide, copeptin, valsartan, ferric carboxymaltose, empagliflozin, preserved ejection fraction, myocardial fibrosis, and heart transplantation were hot themes.

Conclusions

Extensive national and inter-institutional collaboration should be enhanced to bridge the gap between developed and less developed countries in heart failure biomarkers research. The research in this field seems to have reached a relatively mature stage, with a decrease in research fervor in recent years. The study of the natriuretic peptide family still has high centrality, with advances in the study of expression products and inflammatory markers. Cardiac fibrosis, cardiac remodeling, and therapies regarding heart failure have become hot spots.

A retrospective cohort study on the association between early coagulation disorder and short-term all-cause mortality of critically ill patients with congestive heart failure

Purpose

Coagulation disorder in congestive heart failure (CHF) has been well-documented. The prognostic value of a composite coagulation disorder score, which combines the absolute platelet count, international normalized ratio (INR), and activated partial thromboplastin time (APTT), has not been assessed in CHF. The present study endeavored to explore the association between the coagulation disorder score and adverse outcomes of critically ill patients with CHF.

Methods

Patients diagnosed with CHF in the Medical Information Mart for Intensive Care III (MIMIC-III) database were included in the present retrospective cohort study. The coagulation disorder score was calculated according to the abnormalities of the absolute platelet count, INR, and APTT within 24 h after intensive care unit admission. The primary outcomes were the short-term all-cause mortality, including 30-, 90-day and in-hospital mortalities. The Kaplan-Meier (K-M) survival curve and the Cox proportional hazard model were performed to assess the correlation between coagulation disorder score and outcome events.

Results

A total of 6,895 patients were enrolled in this study and divided into four groups according to the coagulation disorder score. K-M survival curve preliminarily indicated that subjects with higher coagulation disorder score presented lower survival rate and shorter survival time. After adjustment for potential confounders, the multivariate Cox analysis further illustrated that elevated coagulation disorder score as a quartile variable was significantly associated with increased all-cause mortality (quartile 4 vs. quartile 1, 30-day: HR [95% CI], 1.98 [1.50, 2.62], 90-day: HR [95% CI], 1.88 [1.49, 2.37], in-hospital: HR [95%CI], 1.93 [1.42, 2.61]).

Conclusion

In critically ill patients with CHF, ones with high coagulation disorder score tend to be worse clinical prognosis, which would be a promising biomarker and helpful for the management of CHF patients.

New Advanced Imaging Parameters and Biomarkers-A Step Forward in the Diagnosis and Prognosis of TTR Cardiomyopathy

Transthyretin amyloid cardiomyopathy (ATTR-CM) is an infiltrative disorder characterized by extracellular myocardial deposits of amyloid fibrils, with poor outcome, leading to heart failure and death, with significant treatment expenditure. In the era of a novel therapeutic arsenal of disease-modifying agents that target a myriad of pathophysiological mechanisms, timely and accurate diagnosis of ATTR-CM is crucial. Recent advances in therapeutic strategies shown to be most beneficial in the early stages of the disease have determined a paradigm shift in the screening, diagnostic algorithm, and risk classification of patients with ATTR-CM. The aim of this review is to explore the utility of novel specific non-invasive imaging parameters and biomarkers from screening to diagnosis, prognosis, risk stratification, and monitoring of the response to therapy. We will summarize the knowledge of the most recent advances in diagnostic, prognostic, and treatment tailoring parameters for early recognition, prediction of outcome, and better selection of therapeutic candidates in ATTR-CM. Moreover, we will provide input from different potential pathways involved in the pathophysiology of ATTR-CM, on top of the amyloid deposition, such as inflammation, endothelial dysfunction, reduced nitric oxide bioavailability, oxidative stress, and myocardial fibrosis, and their diagnostic, prognostic, and therapeutic implications.

Serum Cardiac Biomarkers in Asymptomatic Hemodialysis Patients: Role of Soluble Suppression of Tumorigenicity-2

INTRODUCTION

Cardiovascular events (CVE) remain the leading cause of mortality in hemodialysis (HD) patients. The ability to assess the risk of short-term CVE is of great importance. Soluble suppression of tumorogenicity-2 (sST2) is a novel biomarker that better stratifies risk of CVE than troponins in patients with heart failure. Few studies have investigated the role of sST2 in the HD population. The aim of this single-center study was to assess the predictive ability of sST2 on CVE in comparison to high-sensitive cardiac troponin I (hs-cTnI) and B-type natriuretic peptide (BNP) in HD patients.

METHODS

This study used a prospective, observational cohort design. We enrolled 40 chronic HD patients asymptomatic for chest pain and without recent history of acute coronary syndrome. We tested sST2 pre-/post-HD, hs-cTnI, and BNP. Demographic/dialytic/echocardiographic data were evaluated. We recorded the number of CVE for 12 months. The patients were classified into 2 groups: those who developed CVE and those who did not.

RESULTS

Ten of the 40 patients (25%) developed CVE during a 12-month follow-up. Increased sST2 levels (p < 0.0001) as well as hs-cTnI and BNP are predictive of CVE. When analyzing biomarkers as binary variables for values above or below the normal range, the correlation remained significant only for sST2 (p = 0.001). A small variation in sST2 levels before and after HD sessions was found (-2.1 ng/mL). sST2 was correlated with left ventricular (LV) echocardiographic data: LV mass index (p = 0.0001), LV ejection fraction (p = 0.01), and diastolic bulging of septum (p = 0.015). BNP and sST2 combination increased the prediction of CVE in a statistical model.

CONCLUSION

Our study confirms that sST2 is useful for stratifying CV risk in the HD population. sST2 can be evaluated simply as a dichotomous value higher or lower than the normal range, making it easily interpretable. Dialysis and residual diuresis did not affect significantly sST2. A multimarker approach that incorporates sST2 and BNP may improve the prediction of CVE.

Ceruloplasmin, NT-proBNP, and Clinical Data as Risk Factors of Death or Heart Transplantation in a 1-Year Follow-Up of Heart Failure Patients

We investigated whether the additional determination of ceruloplasmin (Cp) levels could improve the prognostic value of N-terminal pro-B-type natriuretic peptide (NT-proBNP) in heart failure (HF) patients in a 1-year follow-up. Cp and NT-proBNP levels and clinical and laboratory parameters were assessed simultaneously at baseline in 741 HF patients considered as possible heart transplant recipients. The primary endpoint (EP) was a composite of all-cause death (non-transplant patients) or heart transplantation during one year of follow-up. Using a cut-off value of 35.9 mg/dL for Cp and 3155 pg/mL for NT-proBNP (top interquartile range), a univariate Cox regression analysis showed that Cp (hazard ratio (HR) = 2.086; 95% confidence interval (95% CI, 1.462–2.975)), NT-proBNP (HR = 3.221; 95% CI (2.277–4.556)), and the top quartile of both Cp and NT-proBNP (HR = 4.253; 95% CI (2.795–6.471)) were all risk factors of the primary EP. The prognostic value of these biomarkers was demonstrated in a multivariate Cox regression model using the top Cp and NT-proBNP concentration quartiles combined (HR = 2.120; 95% CI (1.233–3.646)). Lower left ventricular ejection fraction, VO₂max, lack of angiotensin-converting enzyme inhibitor or angiotensin receptor blocker therapy, and nonimplantation of an implantable cardioverter-defibrillator were also independent risk factors of a poor outcome. The combined evaluation of Cp and NT-proBNP had advantages over separate NT-proBNP and Cp assessment in selecting a group with a high 1-year risk. Thus multi-biomarker assessment can improve risk stratification in HF patients.

Development of heart failure risk prediction models based on a multi-marker approach using random forest algorithms

Background:

The early identification of heart failure (HF) risk may favorably affect outcomes, and the combination of multiple biomarkers may provide a more comprehensive and valuable means for improving the risk of stratification. This study was conducted to assess the importance of individual cardiac biomarkers creatine kinase MB isoenzyme (CK-MB), B-type natriuretic peptide (BNP), galectin-3 (Gal-3) and soluble suppression of tumorigenicity-2 (sST2) for HF diagnosis, and the predictive performance of the combination of these four biomarkers was analyzed using random forest algorithms.

Methods:

A total of 193 participants (80 patients with HF and 113 age- and gender-matched healthy controls) were included from June 2017 to December 2017. The correlation and regression analysis were conducted between cardiac biomarkers and echocardiographic parameters. The accuracy and importance of these predictor variables were assessed using random forest algorithms.

Results:

Patients with HF exhibited significantly higher levels of CK-MB, BNP, Gal-3, and sST2. BNP exhibited a good independent predictive capacity for HF (AUC 0.956). However, CK-MB, sST2, and Gal-3 exhibited a modest diagnostic performance for HF, with an AUC of 0.709, 0.711, and 0.777, respectively. BNP was the most important variable, with a remarkably higher mean decrease accuracy and Gini. Furthermore, there was a general increase in predictive performance using the multi-marker model, and the sensitivity, specificity was 91.5% and 96.7%, respectively.

Conclusion:

The random forest algorithm provides a robust method to assess the accuracy and importance of predictor variables. The combination of CK-MB, BNP, Gal-3, and sST2 achieves improvement in prediction accuracy for HF.

Circulating Biomarkers in Heart Failure

Biological markers have served for diagnosis, risk stratification and guided therapy of heart failure (HF). Our knowledge regarding abilities of biomarkers to relate to several pathways of HF pathogenesis and reflect clinical worsening or improvement in the disease is steadily expanding. Although there are numerous clinical guidelines, which clearly diagnosis, prevention and evidence-based treatment of HF, a strategy regarding exclusion of HF, as well as risk stratification of HF, nature evolution of disease is not well established and requires more development. The aim of the chapter is to discuss a role of biomarker-based approaches for more accurate diagnosis, in-depth risk stratification and individual targeting in treatment of patients with HF.

Monitoring Acute Myocardial Infarction Complicated with Cardiogenic Shock — from the Emergency Room to Coronary Care Units

Cardiogenic shock remains the leading cause of death in patients hospitalized for acute myocardial infarction, despite many advances encountered in the last years in reperfusion, mechanical, and pharmacological therapies addressed to stabilization of the hemodynamic condition of these critical patients. Such patients require immediate initiation of the most effective therapy, as well as a continuous monitoring in the Coronary Care Unit. Novel biomarkers have been shown to improve diagnosis and risk stratification in patients with cardiogenic shock, and their proper use may be especially important for the identification of the critical condition, leading to prompt therapeutic interventions. The aim of this review was to evaluate the current literature data on complex biomarker assessment and monitoring of patients with acute myocardial infarction complicated with cardiogenic shock in the Coronary Care Unit.

Growth-differentiation factor 15 as a predictor of mortality in patients with heart failure: a meta-analysis

AIMS

Measurement of the biomarker growth-differentiation factor 15 (GDF-15) in patients with heart failure may help in risk stratification. We assessed the relationship between GDF-15 and mortality in patients with heart failure by conducting a meta-analysis.

METHODS

PubMed, Embase, ISI Web of Science, SCOPUS, and Cochrane Library databases were searched for studies that reported data on the baseline GDF-15 levels and all-cause or cardiovascular mortality. Pooled hazard ratios for mortality were calculated and presented with 95% confidence intervals (CIs). Potential sources of heterogeneity were assessed by meta-regression, subgroup, and sensitivity analyses.

RESULTS

Eight studies with a total of 4126 heart failure patients were included. Pooled results showed that overexpression of GDF-15 was associated with poor survival in heart failure patients (log unit GDF-15: hazard ratio = 1.86, 95% CI = 1.37-2.52). Subgroup analyses revealed similar results. However, there was evidence of heterogeneity and publication bias. The association disappeared after correction using the trim-and-fill method (log unit GDF-15: hazard ratio 1.07, 95% CI 0.80-1.42).

CONCLUSION

The results of this meta-analysis indicate an association of elevated GDF-15 levels with increased risk of mortality in patients with heart failure. However, the results should be interpreted with caution due to substantial heterogeneity and publication bias among the studies included in the meta-analysis.

Treatment of Heart Failure With Reduced Ejection Fraction-Recent Developments

Heart failure with reduced ejection fraction (HFrEF) represents at least half of the cases of heart failure, which is a syndrome defined as the inability of the heart to supply the body's tissues with an adequate amount of blood under conditions of normal cardiac filling pressure. HFrEF is responsible for high costs and rates of mortality, morbidity, and hospital admissions, mainly in developed countries. Thus, the need for better diagnostic methods and therapeutic approaches and consequently better outcomes is clear. In this article, we review the principal aspects of pathophysiology and diagnosis of HFrEF, with focus on emerging biomarkers and on recent echocardiographic methods for the assessment of left ventricular function. Furthermore, we discuss several major developments in pharmacological and nonpharmacological treatment of HFrEF in the last years, including cardiac resynchronization therapy, implantable cardioverter defibrillators, and the recent and promising drug LCZ696, focusing on current indications, unanswered questions, and other relevant aspects.

Differences in biochemical and genetic biomarkers in patients with heart failure of various etiologies

BACKGROUND/OBJECTIVES

To evaluate whether biomarkers reflecting pathophysiological pathways and selected single nucleotide polymorphisms differ between patients (pts) with heart failure (HF).

METHODS

110 pts with were involved, including HF pts with preserved ejection fraction (HFpEF, n=51) with hypertensive origin, HF pts with reduced ejection fraction (HFrEF) with ischemic aetiology (ICM) (n=32) and HFrEF with dilated cardiomyopathy (DCM) (n=27). We assessed selected HF biomarkers, echocardiographic examinations and functional polymorphisms selected from six candidate genes: CYP27B1, NOS3, IL-6, TGF beta, TNF alpha, and PPAR gamma.

RESULTS

Higher concentrations of TNF alpha were observed in pts with hypertensive HFpEF compared to pts with DCM (p=0.008). Pts with HFpEF had higher concentrations of TGF beta 1 compared to DCM and ICM (p=0.0001 and p=0.0003, respectively). For the NOS3 -786 C/T rs2070744 polymorphism in DCM there were significantly more CT heterozygotes than in ICM and HFpEF. In multivariate analysis TGF beta 1 (p=0.001) and syndecan 4 (p=0.001) were the only factors distinguishing HFrEF pts with DCM vs HFpEF and also TGF beta 1 (p=0.001) and syndecan 4 (p=0.023) were the only factors distinguishing HFrEF pts with ICM vs HFpEF pts.

CONCLUSIONS

Inflammation mediated through TNF alpha and TGF beta 1 may represent an important component of an inflammatory response that partially drives the pathophysiology of HFpEF. NOS3 -786 C/T rs2070744 polymorphism in DCM may serve as a marker for more rapid progression of heart failure. The only biomarkers independently distinguishing HFpEF and HFrEF are syndecan 4 and TGF beta 1.

Multimarker Strategy for Heart Failure Prognostication. Value of Neurohormonal Biomarkers: Neprilysin vs NT-proBNP

INTRODUCTION AND OBJECTIVES

Neprilysin breaks down numerous vasoactive peptides. The soluble form of neprilysin, which was recently identified in heart failure, is associated with cardiovascular outcomes. Within a multibiomarker strategy, we directly compared soluble neprilysin and N-terminal pro-B-type natriuretic peptide as risk stratifiers in a real-life cohort of heart failure patients.

METHODS

Soluble neprilysin, N-terminal pro-B-type natriuretic peptide, ST2, and high-sensitivity troponin T levels were measured in 797 consecutive ambulatory heart failure patients followed up for 4.7 years. Comprehensive multivariable analyses and soluble neprilysin vs N-terminal pro-B-type natriuretic peptide head-to-head assessments of performance were performed. A primary composite endpoint included cardiovascular death or heart failure hospitalization. A secondary endpoint explored cardiovascular death alone.

RESULTS

Median soluble neprilysin and N-terminal pro-B-type natriuretic peptide concentrations were 0.64ng/mL and 1187 ng/L, respectively. Both biomarkers significantly correlated with age (P<.001) and ST2 (P<.001), but only N-terminal pro-B-type natriuretic peptide significantly correlated with estimated glomerular filtration rate (P<.001), body mass index (P<.001), left ventricular ejection fraction (P=.02) and high-sensitivity troponin T (P<.001). In multivariable Cox regression analyses, soluble neprilysin remained independently associated with the composite endpoint (hazard ratio=1.14; 95% confidence interval, 1.02-1.27; P=.03) and cardiovascular death (hazard ratio=1.15; 95% confidence interval, 1.01-1.31; P=.04), but N-terminal pro-B-type natriuretic peptide did not. The head-to-head soluble neprilysin vs N-terminal pro-B-type natriuretic peptide comparison showed good calibration and similar discrimination and reclassification for both neurohormonal biomarkers, but only soluble neprilysin improved overall goodness-of-fit.

CONCLUSIONS

When added to a multimarker strategy, soluble neprilysin remained an independent prognosticator, while N-terminal pro-B-type natriuretic peptide lost significance as a risk stratifier in ambulatory patients with heart failure. Both biomarkers performed similarly in head-to-head analyses.