Cardiac Biomarkers in Advanced Heart Failure: How Can They Impact Our Pre-transplant or Pre-LVAD Decision-making

Oncostatin M: a Potential Biomarker to Predict Infection in Patients with Left Ventricular Assist Devices

Infection is a serious adverse event limiting left ventricular assist device (LVAD) therapy in advanced heart failure patients, but a reliable means to identify patients at increased risk of infection is still lacking. We hypothesized that preoperative elevated levels of plasma Oncostatin M (OSM), a cytokine marker of leukocyte activation and inflammation, would be predictive of subsequent infection. We measured plasma OSM in 41 LVAD patients one day before LVAD implantation and postoperatively over two months. Preoperative plasma OSM levels were normal in 27 patients (group A, 4.9 ± 3.2 pg/ml) but elevated in 14 patients (group B, 1649.0 ± 458.9 pg/ml) ( p = 0.003). Early postoperative levels rose in both groups and declined rapidly in group A, with group B declining slowly over two months. Significantly more infections developed in group B than group A patients over two months postimplantation ( p = 0.004). No other routine clinical assessment or laboratory testing afforded this differentiation. These findings suggest that preoperative plasma OSM levels may assist in identifying patients at increased risk of infections after LVAD implantation.

Relationship Between Preoperative NT-proBNP and Postoperative Adverse Events in Patients with Left Ventricular Assist Device

Background:

The aim of this study is to investigate the relationship of preoperative NT-proBNP values with postoperative adverse events in patient left ventricular assist device (LVAD) implantation.

Method:

Forty-six patients (35 males; mean age 49.4 ± 12.9 years) who underwent LVAD implantation between 2016 and 2018 were evaluated in this study. The analysis was made on the relationship between preoperative NT-proBNP and mortality, postoperative right ventricular failure (RVF), postoperative drainage, duration of intubation, and intensive care unit stay, was examined. The optimal NT-proBNP cut-off values for predicting mortality were determined using Receiver Operator Characteristic (ROC) curve analysis and the patients were divided into two groups according to the specified cut-off point.

Result:

Median NT-proBNP was higher in patients who died, had postoperative extracorporeal membrane oxygenation, and early RVF. The median NT-proBNP was 11,103 pg/ml in patients with IABP, and 2943 pg/ml in patients without IABP, and the difference was statistically significant ( p = 0.002). The cut-off point for NT-proBNP was found to be 1725.5 pg/ml (Sensitivity:0.929, Specificity:0.688). Accordingly, when the patients were divided into two groups and analyzed, no statistically significant difference was found between preoperative NT-proBNP below or above 1725.5 and postoperative adverse events. There was no statistically significant correlation between preoperative NT-proBNP and postoperative drainage, duration of intubation time, and duration of ICU stay ( p > 0.05).

Conclusion:

Routine monitoring of preoperative NT-proBNP and comparison with postoperative values are important in terms of patient selection, the timing of surgery, follow-up of postoperative adverse events, and improving outcomes in VAD patients.

Biomarkers of Volume Overload and Edema in Heart Failure With Reduced Ejection Fraction

From a pathogenetic point of view, heart failure (HF) is characterized by the activation of several neurohumoral pathways with a role in maintaining the cardiac output and the adequate perfusion pressure in target organs and tissues. Decreased cardiac output in HF with reduced ejection fraction causes activation of the sympathetic nervous system, the renin angiotensin aldosterone system, arginine-vasopressin system, natriuretic peptides, and endothelin, all of which cause water and salt retention in the body. As a result, patients will present clinically as the main symptoms: dyspnea and peripheral edema caused by fluid redistribution to the lungs and/or by fluid overload. By studying these pathophysiological mechanisms, biomarkers with a prognostic and therapeutic role in the management of edema were identified in patients with HF with low ejection fraction. This review aims to summarize the current data from the specialty literature of such biomarkers with a role in the pathogenesis of edema in HF with low ejection fraction. These biomarkers may be the basis for risk stratification and the development of new therapeutic means in the treatment of edema in these patients.

Biomarkers in heart failure: Relevance in the clinical practice

Early detection and risk stratification of patients with heart failure (HF) are crucial to improve outcomes. Given the complexity of the pathophysiological processes of HF and the involvement of multi-organ systems in different stages of HF, clinical prognostication of HF can be challenging. In this regard, several biomarkers have been investigated for diagnosis, screening, and risk stratification of HF patients. These biomarkers can be classified as biomarkers of myocardial stretch such as B-type natriuretic peptide, biomarkers of neurohormonal activation, biomarkers of inflammation and oxidative stress and biomarkers of cardiac hypertrophy, fibrosis and remodeling. In this paper, we summarize current evidence supporting the use of selected biomarkers in HF. We review their diagnostic, prognostic and therapeutic role in the management of HF. We also discuss potential factors limiting the use of these novel biomarkers in the clinical practice and highlight the challenges of adopting a multi-biomarker strategy.

Machine learning for multidimensional response and survival after cardiac resynchronization therapy using features from cardiac magnetic resonance

Background

Cardiac resynchronization therapy (CRT) response is complex, and better approaches are required to predict survival and need for advanced therapies.

Objective

The objective was to use machine learning to characterize multidimensional CRT response and its relationship with long-term survival.

Methods

Associations of 39 baseline features (including cardiac magnetic resonance [CMR] findings and clinical parameters such as glomerular filtration rate [GFR]) with a multidimensional CRT response vector (consisting of post-CRT left ventricular end-systolic volume index [LVESVI] fractional change, post-CRT B-type natriuretic peptide, and change in peak VO₂) were evaluated. Machine learning generated response clusters, and cross-validation assessed associations of clusters with 4-year survival.

Results

Among 200 patients (median age 67.4 years, 27.0% women) with CRT and CMR, associations with more than 1 response parameter were noted for the CMR CURE-SVD dyssynchrony parameter (associated with post-CRT brain natriuretic peptide [BNP] and LVESVI fractional change) and GFR (associated with peak VO₂ and post-CRT BNP). Machine learning defined 3 response clusters: cluster 1 (n = 123, 90.2% survival [best]), cluster 2 (n = 45, 60.0% survival [intermediate]), and cluster 3 (n = 32, 34.4% survival [worst]). Adding the 6-month response cluster to baseline features improved the area under the receiver operating characteristic curve for 4-year survival from 0.78 to 0.86 (P = .02). A web-based application was developed for cluster determination in future patients.

Conclusion

Machine learning characterizes distinct CRT response clusters influenced by CMR features, kidney function, and other factors. These clusters have a strong and additive influence on long-term survival relative to baseline features.

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.

Liver stiffness and prediction of cardiac outcomes in patients with acute decompensated heart failure

BACKGROUND

In acute decompensated heart failure (ADHF), noninvasive markers that predict morbidity and mortality are limited. Liver stiffness measurement (LSM) increases with hepatic fibrosis; however, it may be falsely elevated in patients with ADHF in the absence of liver disease. We investigated whether elevated LSM predicts cardiac outcomes in ADHF.

METHODS

In a prospective study, we examined 52 ADHF patients without liver disease between 2016 and 2017. Patients underwent liver 2D shear wave elastography (SWE) and were followed for 12 months to assess the outcomes of left ventricular assist device (LVAD), heart transplant (HT) or death.

RESULTS

The median LSM was elevated in patients who received an LVAD or HT within 30-days compared to those who did not (median [IQR]: 55.6 [22.5 - 63.4] vs 13.8 [9.5 - 40.3] kPa, p = .049). Moreover, the risk of composite outcome was highest in the 3rd tertile (> 39.8 kPa compared to 1^st and 2^nd combined, HR 2.83, 95% CI 1.20- 6.67, p = .02). Each 1-kPa increase in LSM was associated with a 1%-increase in the incidence rate of readmissions (IRR 1.01, 95% CI 1.00-1.02, p = .01).

CONCLUSIONS

LSM may serve as a novel noninvasive tool to determine LVAD, HT, or death in patients with ADHF.