The Biomarker Risk Prediction Score in Chronic Heart Failure

Research Article

J Fam Med. 2014;1(1): 2.

The Biomarker Risk Prediction Score in Chronic Heart Failure

Alexander E Berezin1*, Alexander A Kremzer2, Yulia V Martovitskaya3, Tatyana A Samura2 and Tatyana A Berezina4

1Internal Medicine Department, State Medical University, Ukraine

2Clinical Pharmacology Department, State Medical University, Ukraine

3Pathology Department, State Medical University, Ukraine

4Private Medical Center, Zaporozhye, Ukraine

*Corresponding author: Alexander E Berezin, Cardiology Unit, Internal Medicine Department, State Medical University, 26, Mayakovsky av, Zaporozhye, UA- 69035, Ukraine

Received: July 21, 2014; Accepted: July 29, 2014; Published: July 29, 2014


The study aim was to evaluate whether biomarker risk prediction score is powerful tool for risk assessment of three-year fatal and non-fatal cardiovascular events in CHF patients.

Methods: It was studied prospectively the incidence of fatal and non-fatal cardiovascular events, as well as the frequency of occurrence of death from any cause in a cohort of 388 patients with CHF during 3 years of observation. Circulating levels of NT-pro Brain Natriuretic Peptide (NT-pro-BNP), galectin-3, high-sensitivity C - reactive protein (hs-CRP), osteoprotegerin and its soluble receptor sRANKL, osteopontin, osteonectin, adiponectin, Endothelial Apoptotic Micro Particles (EMPs) and Mononuclear Progenitor Cells (MPCs) were measured at baseline.

Results: Median follow-up of patients included in the study was 2.76 years. There were 285 cardiovascular events determined, including 43 deaths and 242 readmissions. Independent predictors of clinical outcomes in patients with CHF were NT-pro-BNP, galectin-3, hs-CRP, osteoprotegerin, CD31+/annexin V+ EMPs and EMPs / CD14+CD309+ MPCs ratio. Index of cardiovascular risk was calculated by mathematical summation of all ranks of independent predictors,which occurred in the patients included in the study. The findings showed that the average value of the index of cardiovascular risk in patients with CHF was 3.17 points (95% CI = 1.65 - 5.10 points.). Kaplan-Meier analysis showed that patients with CHF and the magnitude of the risk of less than 4 units have an advantage in survival when compared with patients for whom obtained higher values of ranks cardiovascular risk score.

Conclusion: biomarker risk score for cumulative cardiovascular events, constructed by measurement of circulating NT-pro-BNP, galectin-3, hs-CRP, osteoprotegerin, CD31+/annex in V+ EMPs and EMPs / CD14+CD309+ MPCs ratio, allowing reliably predict the probability survival of patients with CHF, regardless of age, gender, state of the contractile function of the left ventricle and the number of co morbidities.

Keywords: Chronic Heart Failure; Biomarkers; Cardiovascular Outcomes; Predictive Value


BMI: Body Mass Index; BMP: Brain Natriuretic Peptide; CI: Confidence Interval; CHF: Chronic Heart Failure; EMPs: Endothelial-Derived Apoptotic Micro particles; Gal-3: Galectin-3; GFR: Glomerular Filtration Rate; LVEF: Left Ventricular Ejection Fraction; MPCs: Mononuclear Progenitor Cells; NYHA: New York Heart Association; OR: Odds Ratio; TNF: Tumor Necrosis Factor.


Chronic Heart Failure (CHF) remained leading cause of cardiovascular death worldwide [1]. As expected, significant improvements in survival have occurred for patients with CHF, with an increasing array of therapeutic options sharing quite varied properties of cost, invasiveness, and impact on life expectancy [2,3]. Contemporary risk models allow patients and physicians to achieve a better understanding of prognosis than is possible through unstructured holistic assessment [4]. Recent clinical studies have been shown that short-term and long-term prognosis among heart failure persons may be reappraised and recalculated using biological marker models demonstrated to be credible in clinical practice and useful predictable tool for physicians [5-7]. Natriuretic peptides, galectin-3 (Gal-3), high sensitive C - reactive protein (hs-CRP) were positively associated with all-cause and cardiovascular mortality and were discussed useful for estimating prognosis in persons with chronic stable heart failure [8-10]. Therefore, wide spectrum of biomarkers reflected immune status, pro inflammatory activation, endothelial function, was tested in predictive models for CHF patients [11-14]. However, no ideal biomarkers with optimal decremented potency were found that leads to prompting of use a multi marker approach in risk modeling for heart failure persons. Although several multivariate risk scores have shown significant utility in predicting patient outcomes in acute and acutely decompensate heart failure, contemporary models, such asSeattle Heart Failure Model, substantially underestimated the absolute risk of death in ambulatory CHF patients [15].

The study aim was to evaluatewhether biomarker risk prediction score is powerful tool for risk assessment of three-year fatal and nonfatal cardiovascular events in CHF patients.


Study population

The study population consisted of 388 consecutive patients with CHF who underwent angiography or PCI between April 2010 to June 2014, as well as were referred as post-myocardial infarction subjects within this period in our five centers participated in this investigation. All these patients were selected from 1427 patients according to our inclusion and exclusion criteria. The study protocol was approved by the Zaporozhe State medical University Ethnics committee review board. The study complied with the Declaration of Helsinki and voluntary informed written consent was obtained from all patients included in this study.

We analyzed cumulative survival related to CHF, and additionally all-cause mortality was examined.Prognosis was assessed by the composite endpoint all-cause death, CHF-related death or CHF hospitalization, censored at 3 years.

Methods for visualization of coronary arteries

Multispiral computed tomography angiography and/or angiographic study have been carried out to verify the ischemic nature of the disease in patients. Multispiral computed tomography angiography has been carried out for all the patients prior to their inclusion in the study. When atherosclerotic lesions of the coronary arteries were verified, patients were subjected to conventional angiographic examination provided indications for revascularization were available. CAD was considered to be diagnosed upon availability of previous angiographic examinations carried out not later than 6 months ago provided no new cardiovascular events occurred for this period, and the procedure are available for assay. The coronary artery wall structure was measured by means of contrast spiral computed tomography angiography [16] on Soma tom Volume Zoom scanner (Siemens, Erlangen, Germany) with two detector rows when holding patients breathe at the end of breathing in. After preliminary native scanning, non-ionic contrast omnipaque (Amersham Health, Ireland) was administered for the optimal image of the coronary arteries.

Echocardiography and tissue Doppler imaging

Transthoracic B-mode echocardiography and tissue Doppler imaging were performed according to a conventional procedure on ACUSON scanner (SIEMENS, Germany) using phased transducer of 5 ?Hz. Left Ventricular End-Diastolic and End-Systolic Volumes, and Ejection Fraction (LVEF) were measured by modified Simpson's plan metric method [17,18]. Peak systolic (Sm), early diastolic (Em), and late diastolic (?m) myocardial velocities were measured in the mitral annulus area, followed by calculating velocity of early diastolic left ventricular filling (E) to ?m (?/?m) ratio and to Em (?/Em) ratio. Inter- and intraobserver variability coefficients for LVEF were 3.2% and 1.1% respectively.

Glomerular filtration rate measurement

Calculation of Glomerular Filtration Rate (GFR) was calculated by CKD-EPI formula [19].

Biomarker determination

All biomarkers were determined at baseline. To measurement of biological marker concentrations, blood samples were drawn in the morning (at 7-8 a.m.) into cooled silicone test tubes. Samples were processed according to the recommendations of the manufacturer of the analytical technique used. They were centrifuged upon permanent cooling at 6,000 rpm for 3 minutes. Then, plasma was refrigerated immediately to be stored at a temperature -70?? until measurement.

Circulating NT-pro-BNP level was measured by immune electro chemo luminescent assay using sets produced by R&D Systems (USA) on Elecsys 1010 analyzer (Roche, Mannheim, Germany). Serum concentrations of Tumor Necrosis Factor alpha (TNF-alpha), solubilized Fas (sFas), sFas ligand, galectin-3, and adiponectine were determined in duplicate with commercially available enzyme-linked immunosorbent assay kits (Bender Med Systems GmbH, Vienna, Austria).

Circulatingbone-related proteins (osteoprotegerin, osteonectine, and osteopontine) were determined in duplicate by ELISA method using kits produced by IBL (Immunochemie und Immunobiologie Gmb, Gewmany).

The high-sensitivity C-Reactive Protein (hs-CRP) levels were measured by using nephelometric technique on AU640 analyzer manufactured by Diagnostic Systems Group (Japan).

Concentrations of Total Cholesterol (TC) and cholesterol of High-Density Lipoproteins (HDLP) were measured by fermentation method. Concentration of cholesterol of Low-Density Lipoproteins (LDL-C) was calculated according to the Friedewald formula (1972).

A total of 100 μl of serum samples was assayed in parallel to known standard concentrations for each biological marker. The mean intra-assay coefficients of variation were <10% of all cases.

Identifying fractions of mononuclear and endothelial progenitor cells

Mononuclear cells populations were phenotype by flowcytofluorimetry by means of monoclonal antibodies labeled with FITC fluorochromes (fluoresce in isothiocyanate) or double-labeled with FITC/PE (phycoerythrin) (BD Biosciences, USA) to CD45, CD34, CD14, Tie-2, and ?D309(VEGFR2) antigens as per HD-FACS (High-Definition Fluorescence Activated Cell Sorter) methodology, with red blood cells removed obligatory with lysing buffer according to gating strategy of International Society of Hematotherapy and Graft Engineering sequential (ISHAGE protocol of gating strategy) [20]. For each sample, 500 thousand events have been analyzed. Circulating Mononuclear Progenitor Cells (MPCs) have been identified as CD45- CD34+ cells. Proangiogenic phenotype for endothelial MPCs was determined as CD14+?D309 (VEGFR2)+Tie-2+ antigens. Obtained when laser beam is scattered in longitudinal and transversal directions in the flowcytofluorimeter, the scatter gram results were analyzed by using Boolean principles for double or triple positive events.

Endothelial-derived apoptotic microparticles determination

Endothelial-derived apoptotic micro particles were phenotyped by flow cytofluorimetry by Phycoerythrin (PE)-conjugated monoclonal antibody against CD31 (BD Biosciences, USA) followed by incubation with Fluoresce in Isothiocyanate (FITC)-conjugated annex in V (BD Biosciences, USA) per HD-FACS (High-Definition Fluorescence Activated Cell Sorter) methodology. The samples were incubated in the dark for 15 min at room temperature according to the manufacturer's instructions. The samples were then analyzed on a FC500 flow cytometer (Beckman Coulter) after 400 L annex in-V binding buffer was added. For each sample, 500 thousand events have been analyzed. EMPs gate was defined by size, using 0.8 and 1.1 mm beads (Sigma, St Louis, MO, USA). CD31+/annex in V+ micro particles were defined as EMPs positively labeled for CD31 and annex in V (CD31+/annex in V+) [21,22].

Statistical analysis

Statistical analysis of the results obtained was carried out in SPSS system for Windows, Version 22 (SPSS Inc, Chicago, IL, USA) and Graph pad Prism for Windows, Version 5 (Graph Pad Software Inc, La Jolla, CA , USA). The data were presented as Mean (?) and Standard Deviation (±SD) or 95% Confidence Interval (CI); Median (??) and Inter Quartile Range (IQR), as well as numerous (n) and frequencies (%) for categorical variables. To compare the main parameters of patients' groups (subject to the type of distribution of the parameters analyzed), two-tailed Student t-test or Mann-Whitney U-test were used. To compare categorical variables between groups, Chi2 test (?2) and Fisher F exact test were used. The circulating EMPs, MPCs, and NT-pro-BNP level in the blood failed to have a normal distribution, while distribution of the hs-CRP, bone-related proteins, adiponectine, total cholesterol and cholesterol fractions had a normal character (estimated by means of Kolmogorov-Smirnov test) and was not subjected to any mathematical transformation. The factors, which could be associated potentially with clinical outcomes, were determined by Cox regression analysis. Receive Operation Characteristic (ROC) curves were constructed for assessment of optimal balanced cut-off points that were suitable for independent predictors of clinical outcomes. Areas under curves were compared using method provided by DeLong et al (1988) [23]. Reclassification methods (C-statistics) were utilized for prediction performance analyses. The Kaplan-Meyer curves were constructed depending categories of the Biomarker risk prediction score. A calculated difference of P<0.05 was considered significant.


Study patient population

The characteristics of the patients participated in the study are depicted in Table 1. At baseline, mean age in box sexes was 58.34 years. The prevalence of II (37.9%) and III (21.4%) NYHA class was determined. At least 55.5% of the subjects enrolled in the study were hypertensive. Likewise, cardiovascular risk factors, such as dyslipidemia, type two diabetes mellitus and obesity, were reported 66.0%; 37.6%; and 44.3% respectively. Mean left ventricular ejection fraction was decreased slightly. Regarding biomarker levels, increased Gal-3, NT-pro-BNP, hs-CRP, bone-related proteins (osteoprotegerin, osteopontin, osteonectin), sRANKL and adiponectin were found. Depletion of ccirculating levels of MPCs labeled as CD14+CD309+ and CD14+CD309+Tie2+ were determined. Increased CD31+/annex in V+ EMPs were found.