Commentary

Metabolic, functional, and haemodynamic staging for CHF?

Accurate risk prediction is important for an adequate management of heart failure (HF) patients. We assessed the incremental prognostic ability of a multi-biomarker approach in advanced HF.

In 349 patients with advanced HF (median 75 years, 66% male) we investigated the incremental prognostic value of 12 novel biomarkers involved in different pathophysiological pathways including inflammation, immunological activation, oxidative stress, cell growth, remodeling, angiogenesis and apoptosis.

During a median follow-up of 4.9 years 55.9% of patients died. Using multivariable Cox regression and bootstrap variable-selection age, chronic obstructive pulmonary disease, N-terminal pro-B-type natriuretic peptide (NT-proBNP) and the following 5 novel biomarkers were retained in the best mortality prediction model: the chemokine fractalkine, the angiogenic and mitogenic hepatocyte growth factor (HGF), the growth differentiation factor 15 (GDF-15) influencing cardiac remodeling and apoptosis, and the 2 pro-apoptotic molecules soluble apoptosis-stimulating fragment (sFAS) and soluble tumor necrosis factor-related apoptosis-inducing ligand (sTRAIL). This multi-biomarker score had strong discriminatory power for 5-year mortality (area under the Receiver Operating Characteristic curve [AUC] = 0.81) and improved risk prediction beyond the prognostic power of a comprehensive conventional risk score including known clinical predictors and NT-proBNP (AUC = 0.77). Net reclassification confirmed a significant improvement of individual risk prediction (p = 0.003).

Risk prediction by a multi-biomarker score is superior to a conventional risk score including clinical parameters and NT-proBNP. Additional predictive information from different biological pathways reflects the multisystemic character of HF.

We hypothesized that obese chronic heart failure (CHF) patients, who are known to have less cardiac dysfunction, could show preserved muscle protein balance. The aim of this study was to relate muscle protein balance and cardiac function to body mass index (BMI) in order to provide further insight to the obesity paradox in CHF patients.

Thirty stable CHF patients were categorized by BMI (n = 6, normal; n = 14, overweight; n = 10, obese) and underwent post-absorptive: (i) right heart catheterization to determine cardiac hemodynamics and (ii) arterial and venous blood sampling to measure arterial and venous levels of essential amino acids (EAAs) and to calculate arterovenous differences (positive = uptake; negative = release). Muscle protein over-degradation was assessed by muscle release of the EAA phenylalanine. Plasma N-terminal pro-B-type natriuretic peptide (NT-pro-BNP) was also determined. Twenty healthy subjects, matched for age, served as controls and underwent radial artery and vein sampling only.

Obese CHF patients had normal muscle protein balance, muscle EAA release, and arterial EAA concentration. Among the non-obese patients, normally weighted ones had more pronounced muscle protein over-degradation and greater reduction of arterial EAAs (p < 0.01 for both) and EAA release (p < 0.06) than overweight ones. Arterial leucine levels correlated negatively with NT-pro-BNP (r = − 0.75; p < 0.0001) and positively with LVEF (r = + 0.68; p < 0.0001). Within EAAs, branched chain amino acids were positively associated with stroke volume index (r = + 0.51; p = 0.004).

Only obese patients with CHF have balanced muscle protein metabolism. This may contribute to explain the obesity paradox.

A vast array of parameters has been proposed to predict mortality in chronic heart failure (CHF). Their applicability into clinical practice remains challenging due to economical and availability considerations.

We studied serum uric acid, total cholesterol, and soluble tumour necrosis factor receptor 1 (sTNF-R1) in 114 CHF patients (63.0 ± 1.0 years, NYHA functional class I/II/III/IV: 11/34/54/15) recruited prospectively into a metabolic study program. All patients underwent assessment of left ventricular ejection fraction and measurement of peak oxygen consumption (pVO₂). Patients were followed for 24 months or until death. A total of 31 patients died; cumulative survival was 78% (95% confidence interval [CI] 70–86%) and 73% (65–81%) at 12 and 24 months, respectively. In single predictor Cox proportional hazard analysis, uric acid, pVO2, sTNFR-1, LVEF (all p < 0.0001) and cholesterol (p < 0.02) all predicted survival. All parameters remained significant predictors of death after multivariable adjustment (all p < 0.02). Receiver–operator characteristic (ROC) curve analyses showed that uric acid and sTNF-R1 are equally strong with regards to their prognostic performance in CHF like pVO_2, but even better than LVEF. The combination of pVO₂, LVEF, uric acid, and sTNF-R1 in ROC statistics turned out as the best model with the highest prognostic value in CHF (AUC: 0.91, sensitivity: 90.4, specificity: 74.2, p = 0.0001).

Including metabolic-immunological parameters into risk assessment might result in a better risk stratification than modeling based on clinical parameters alone, probably due to a better reflection of CHF as multisystem disease. We suggest metabolic-immunological parameters to be tested in larger populations.

Cardiac biomarkers play an important role in heart failure. The family of natriuretic peptides, especially B-type natriuretic peptide, was identified as a valued diagnostic and prognostic tool. Not unexpectedly, the natriuretic peptides fail to fulfill all the criteria of an ideal biochemical marker. The quest for a single marker or a combination is therefore still on and several established, widely available biomarkers might have been overlooked in the field of heart failure. This review puts forward some of those biomarkers, and we speculate on the possible roles of combining two or more biomarkers. In that sense, any blood parameter including hemoglobin, cholesterol, uric acid, and recently identified proteins might function as a biomarker. Additionally, several biomarkers are discussed and we try to anticipate their diagnostic and prognostic value along with the natriuretic peptides and established biomarkers. Finally, we speculate about the potential of sharing the biomarkers over a variety of chronic diseases with similar pathophysiology.

In severe chronic heart failure (CHF) elevated serum levels of uric acid (UA) predict poor survival. This study investigates whether hyperuricaemia (defined as serum UA level ≥ 6.5 mg/dL) extends its prognostic value on population with less advanced CHF.

We studied 119 consecutive patients with stable, mild–moderate CHF (88 men, age: 64 ± 11 years, NYHA class I/II/III: 9/65/45, LVEF: 32 ± 8%).

Serum UA level (mean: 6.2 ± 2.0 mg/dL, range: 2.0–16.2 mg/dL) increased in parallel to CHF severity expressed as NYHA class (4.9 ± 1.1 vs. 5.7 ± 1.5 vs. 7.2 ± 2.4 mg/dL, NYHA I vs. II vs. III; NYHA I, II vs. III, p < 0.01), inversely correlated with peak oxygen consumption (r = − 0.39, p < 0.01) and LVEF (r = − 0.31, p < 0.01), but not with renal function (expressed as creatinine clearance calculated from Cockcroft–Gault formula; r = − 0.14, p > 0.1), and predicted inflammatory status as evidenced by the correlation with C-reactive protein (r = 0.31, p = 0.003). Hyperuricaemia was detected in 48 (40%) patients. During follow-up (mean: 580 ± 209 days, > 18 months in all survivors), 27 (23%) patients died. Hyperuricaemia was related to impaired survival in univariate (HR 2.8, 95%CI: 1.3–6.1, p = 0.01) and multivariate analyses (adjusted for NYHA class and impaired renal function—the only mortality predictors in this population; p < 0.05). The 18-month survival for CHF patients with hyperuricaemia was 71% (95% CI: 58–84%) vs. 89% (95% CI: 81–96%) in those with normal UA level (p = 0.01).

In patients with mild–moderate CHF, hyperuricaemia predicts exercise intolerance and inflammatory activation and is strongly and independently related to poor prognosis. Whether elevated serum UA level may become a novel therapeutic target in CHF, deserves further studies.

Plasma volume, the intravascular portion of the extracellular fluid volume, can be measured using standard dilution techniques with radiolabeled tracer molecules. In healthy persons, plasma volume remains relatively constant as a result of tight regulation by the complex interaction between neurohormonal systems involved in sodium and water homeostasis. Although chronic heart failure (CHF) is characterized by activation of many of these neurohormonal systems, few studies have evaluated plasma volume in this condition under treatment. Untreated edematous decompensated heart failure (HF) is associated with a significant expansion of plasma volume. Patients with stable CHF, receiving conventional therapy, appear to have a contracted plasma volume, a concept that is in contrast to the widely held belief that CHF is associated with long-term hypervolemia. It is likely that significant changes in plasma volume occur during intensification of medical therapy or during transition from the edematous to the stable state. Clinical assessment of plasma volume may be of particular value during treatment in patients with decompensated HF, in whom the plasma volume is contracted despite an increase in total extracellular fluid volume. Under these circumstances, treatment with inotropes or renal vasodilators may be more appropriate than intravenous diuretics alone. Further studies evaluating plasma volume in HF may help to improve our understanding of the pathophysiologic mechanisms occurring in the development and progression of this complex condition.