Cite this article as: Iqbal N, Wentworth B,
Choudhary R, De La Parra Landa A, Kipper B, Fard A, Maisel AS. Cardiac
biomarkers: New tools for heart failure management. Cardiovasc Diagn Ther
2012;2(2):147-164. DOI: 10.3978/j.issn.2223-3652.2012.06.03
Review Article
Cardiac
biomarkers: New tools for heart failure management
Navaid Iqbal1, Bailey Wentworth1, Rajiv Choudhary1, Alejandro De La Parra
Landa1, Benjamin Kipper1, Arrash Fard1, Alan S. Maisel1,2
1Veterans Affairs San Diego Healthcare
System, San Diego, CA, USA; 2Department of
Medicine, University of California at San Diego, La Jolla, CA, USA
Corresponding to:
Navaid Iqbal, MD.
3350 La Jolla Village Dr. MC: 111A, San Diego, CA 92161, USA.
Email: navaid_iqbal@yahoo.com.
AbstractOther
Section
The last decade has seen exciting
advances in the field of biomarkers used in managing patients with heart
failure (HF). Biomarker research has broadened our knowledge base, shedding
more light on the underlying pathophysiological mechanisms occurring in
patients with both acute and chronic HF. The criterion required by an ideal
cardiovascular biomarker has been progressively changing to an era of sensitive
assays that can be used to guide treatment. Recent technological advances have
made it possible to rapidly measure even minute amounts of these proteins by
means of higher sensitivity assays. With a high prevalence of comorbidities
associated with HF, an integrated approach utilizing multiple biomarkers have
shown promise in predicting mortality, better risk stratification and reducing
re-hospitalizations, thus lowering health-care costs. This review provides a
brief insight into recent advances in the field of biomarkers currently used in
the diagnosis and prognosis of patients with acute and chronic HF.
Key words
Decompensated heart failure;
glomerular filtration rate; natriuretic peptides; cardiac myocyte
Submitted Mar 10, 2012. Accepted for publication Jun 08, 2012.
DOI: 10.3978/j.issn.2223-3652.2012.06.03
IntroductionOther
Section
Heart failure (HF) remains the
leading cause of death in the US and worldwide, causing a significant burden on
health care systems across the globe (1). According to the 2011 update on the heart disease and stroke
statistics, the prevalence of HF in people aged 20 years and older in the
United States is approximately 5.7 million (2). Clinically, HF is a complex disease process that can result from a
variety of conditions preventing the left ventricle from properly filling and
ejecting blood. Patients with acute HF commonly present to the emergency
department with symptoms and signs of fluid retention, pulmonary congestion,
peripheral edema, decreased exercise tolerance, dyspnea, and fatigue. However,
these symptoms and signs can be misleading and have poor diagnostic sensitivity
and specificity. In spite of major advances in therapy, prognosis for HF
remains poor. Biomarkers, with their objectivity and widespread availability,
have an indispensable role in improving HF management. Figure 1 represents various biomarkers reflecting distinct cardiac myocyte
pathology along with biomarkers that have demonstrated strong evidence in
detecting comorbidities such as acute kidney injury and pneumonia often seen in
patients with HF. A multi-marker approach is required to adequately assess the
risk profile of a given HF patient. As a result, significant effort has been
placed on biomarker research, leading to the emergence of several promising
novel cardiac biomarkers for HF diagnosis and risk stratification.
Figure 1 Schematic representation of the
release of various biomarkers from organs in patients with heart failure.
Increased ventricular wall stretch is the primary inciting event causing a
cascade of biomarker release which can be measured to monitor disease severity
and ongoing myocardial insult. The growing body of research has shown that in
heart failure patients, complex underlying pathophysiological processes can be
better understood by monitoring biomarker activity. BNP: B-Type Natriuretic
Peptide; NT-proBNP: Amino Terminal Natriuretic Peptide; MR-proANP: Mid-regional
A-type Natriuretic Peptide; GDF-15: Growth differentiation factor 15; NGAL:
Neutrophil gelatinase associated lipocalin; IL 6: Interleukin 6; TNF-α: Tumor
necrosis factor alpha; CRP: C-Reactive protein; RAAS:
Renin-angiotensin-aldosterone system
Markers of myocyte strainOther Section
The natriuretic peptides, which
include B-type natriuretic peptide (BNP) and the N-terminal fragment of its
prohormone (NT-proBNP), as well as atrial natriuretic peptide (ANP),
adrenomedullin and the mid-regional fragment of the prohormone (MR-proANP), are
currently the most widely used markers of myocardial strain. These prohormones
are released in hemodynamic stress and processed into biologically active
natriuretic peptides, which can counteract the stress by inducing vasodilation,
natriuresis and diuresis (3).
BNP is produced from pre-proBNP, a
134 amino acid molecule released from myocytes under stress (4). Once released, plasma BNP binds to the NP receptor A causing a
signaling cascade that initiates natriuresis, diuresis, arterial vasodilation,
inhibition of cardiac and vascular myocyte growth. BNP has a half life of 20
minutes (5) and is cleared from the circulation via endocytosis, renal filtration
or passive excretion. The utility of BNP has been demonstrated in several
studies and is perhaps the most widely used biomarker in the assessment of
acute HF (6,7).
NT-proBNP is also formed and released
as a result of cleavage of its precursor form proBNP that undergoes enzymatic
breakdown and processing by two paraprotein convertases, furin (8) and corin (9). NT-proBNP is formed in largest concentration in the left ventricle,
but is also detectable to a certain amount in the right atrial and ventricular
muscle. NT-proBNP has a half-life of 60-90 minutes and is excreted in its
original form via the kidney (10).
While ANP has been slightly less
consistent as a diagnostic marker than BNP due to its rapid clearance, the
stable mid-regional fragment of proANP (MR-proANP) has been identified as a
robust surrogate marker (11). MR-proANP degrades and clears the blood less quickly than ANP or
proANP and thus is more reliable as a marker in the clinical setting (9).
Adrenomedullin (ADM) is a
52-amino-acid peptide thought to be upregulated due to increased volume
overload and is mediated by vasoactive hormones (12,13). However, due its rapid clearance from the circulation and a short
half-life (22 min), using ADM as a routine biomarker is impractical (14). MR-proADM, the mid-regional segment of ADM’s precursor
pre-proadrenomedullin, is released in equimolar concentrations as
adrenomedullin and thus is an effective substitute, and due its inactivity and
longer half-life, MR-proADM is a better surrogate marker (13).
BNP
BNP plasma
concentrations fluctuate depending on the disease. BNP increases particularly
when there is an abnormal dilatation of the cardiac wall chamber, increased
fluid volume or reduced elimination of peptides such as in kidney failure (15).
Factors such as age, BMI, renal
function can alter NP levels resulting in “grey-zone” values, so accurate
interpretation is critical (16). The grey-zone values are approximately 100-400 pg/mL for BNP (16). In the ED wherein the majority of acute HF patients present, a
cut-off of 100 pg/mL to exclude HF is sufficient (in conjunction with other
tests) regardless of age and sex (16). Attention to other causes of elevated NP levels such as pulmonary
hypertension, right ventricular dysfunction, and valvular disorders must be
considered (16,17). Other modalities such as chest X-ray, blood tests must be utilized to
make a positive diagnosis (16-18). Close monitoring of such patients is crucial to identify associated
comorbidities and modify HF-treatment according to level of risk. In those with
high BMI (>35 kg/m2), more rapid clearance of NPs by increased clearance receptors in
adipocytes results in a lower BNP (19,20), and thus a lower cut-off value of BNP (<50 pg/mL) can be used to
exclude diagnosis of HF (16).
Most patients with acute HF will
visit the ED due to an exacerbation of their symptoms or volume overload (21). Using BNP levels in the ED can assess the risk of death or
readmission within 30 days (16). In a cohort of 464 patients presenting to the ED with symptoms of HF,
Maisel et al. found that the
90-day combined event rate with BNP <200 pg/mL was 9% compared to those
admitted with BNP >200 pg/mL, which was 29%. Prognosis of patients with BNP
levels <200 pg/mL is excellent, even though the patients were perceived to
be in a NYHA functional class III or IV (22).
In those presenting with acute
decompensated HF (ADHF), Di Somma et al. (23) found that the optimal times to assess BNP levels are at admission, 24
hours after admission and at discharge. A reduction of 25% or more 24 hours
after admission and a reduction of 46% or more of BNP levels at discharge
compared with the admission, together with the absolute value of less than 300
pg/mL yielded a strong negative prognosis for future cardiovascular events
including readmission or in-hospital mortality, independent of LVEF (23). Analysis of 48,629 patients in the ADHERE cohort showed that risk of
mortality varied 3- to 4-fold based on the patient’s initial BNP (24).
In patients with chronic HF, BNP can
predict future cardiac events and hospitalizations (25-27). Results from the Val-HeFT trial reported by Masson et al. (25) demonstrated that BNP and NT-proBNP were the strongest predictors of
mortality and hospitalization for HF. Increase in BNP levels by 50 ng/mL from
baseline carried a high risk compared to the pooled analysis by Doust et al. which demonstrated a 35% increase in risk of mortality with an
increase of 100 pg/mL from baseline (26). In another study, BNP level >189 pg/mL after 2 months in addition
to >15% change in BNP levels from baseline had worst survival despite being
stable after discharge for HF (27). Thus, it is imperative that BNP must be closely monitored after
discharge, even in stable patients with chronic HF to identify those at
increased risk and judge response to therapy.
Therapy can be guided based on “dry”
and “wet” BNP levels (21). The dry BNP level indicates the patient’s baseline euvolemic BNP
level and the wet BNP indicates the level resulting from volume overload.
Titration of HF therapy and use of diuretic can be modified judging by the
decrease in wet BNP levels during treatment. Measuring pre-discharge BNP can
help physicians in tailoring HF regimen as well as to stratify patients
according to their risk and minimize future cardiac events and lower mortality
(28).
NT-proBNP
NT-proBNP is
released along with other NPs by the cardiac myocytes in response to increased
wall stress due to HF and myocardial dysfunction. In recent years, the quantitative
assessment of NT-proBNP has shown to be a useful tool in the identification or
exclusion of HF.
In a prospective study assessing the
value of NT-proBNP in aiding diagnosis in 221 patients presenting to the ED
with acute dyspnea, there was significant correlation between NT-proBNP and the
clinical estimate of HF (P<0.0005) (29). Without knowledge of NT-proBNP, HF was diagnosed in 24.0%, lung
failure in 60.6%, a combination of heart and lung failure in 10.9% and 4.5% had
another diagnosis. Adding NT-proBNP levels to the differential resulted in
24.4% with a diagnosis of HF, 47.5% with lung failure and 23.5% with combined
heart and lung failure (29). This study concluded that the additive value of NT-proBNP helped
diagnose 18% of patients presenting with acute dyspnea.
NT-proBNP is also prognostic in
patients with suspected acute HF (30). In the Canadian multicenter IMPROVE CHF study, Moe et al. (30) demonstrated that NT-proBNP testing improved the management of
patients presenting with dyspnea in EDs of Canada and reduced their
re-hospitalization rates over 60 days (P=0.023). Adding NT-proBNP to clinical
judgment increased the ROC curve to 0.90 from 0.83 (P<0.00001).
In some studies, NT-pro-BNP has been
shown to be superior over other natriuretic peptides. BNP, NT-proBNP, and
proBNP levels at hospital admission and discharge in patients with ADHF were
compared for their predictive value of cardiac death and all cause mortality
within 90 days post discharge. NT-proBNP had superior prognostic power for all
cause mortality when compared with BNP and proBNP, suggesting that discharge
values of NT-proBNP have the greatest diagnostic and prognostic potential of
all natriuretic peptides (31).
These studies are just a few to point
to the exceptional value of NT-proBNP for the diagnosis, prognosis, and
management of patients with HF. While there are many studies suggesting that NT
proBNP and BNP are similar in their potential as a marker for heart failure,
there are some recent studies underscoring the fact that NT proBNP is a more
discerning marker in many common clinical scenarios, such as diastolic HF (32,33). This versatile cardiovascular marker will help optimize the care of a
wide range of patients with prevalent cardiovascular illnesses.
Mid-regional pro A-type natriuretic
peptide
The diagnostic utility of MR-proANP
as compared to BNP was recently demonstrated in the Biomarkers in ACute Heart
Failure (BACH) study, a 15-center international trial (34). In the diagnosis of
acute HF in those presenting to the ED with dyspnea, a MR-proANP level greater
than the predefined cutpoint of 120 pmol/L was found to be non-inferior to BNP
at the 100 pg/mL cut point. Table 1 shows the specificity and sensitivity for MR-proANP compared to BNP.
Combining MR-proANP and BNP together increased diagnostic accuracy from 73.6%
(BNP) to 76.6%. In areas where BNP and NT-proBNP could be less informative
(obesity, old age, renal dysfunction, “grey zone” values), MR-proANP adds value
when used in combination with each biomarker (34,35).
Table
1 Diagnostic Utility of
MR-proANP As Compared to BNP in the Biomarkers in Acute HF (BACH) Trial
|
||
|
MR-proANP
(>120 pmol/L)
|
MR-proANP
(>120 pmol/L)
|
Sensitivity
|
95.56%
|
96.98%
|
Specificity
|
59.85%
|
61.90%
|
Adapted
from: Maisel A, Mueller C, Nowak R, et al. Mid-region prohormone
markers for diagnosis and prognosis in acute dyspnea: results from the BACH
(Biomarkers in Acute HF) trail. J Am Coll Cardiol 2010;55:2062-76
|
In the prospective Malmö Diet and
Cancer Study, the prognostic values of MR-proANP and five other biomarkers in
the development of HF or atrial fibrillation were examined. Of 5,187
participants, 112 developed HF and 284 developed atrial fibrillation within the
14 year follow-up. MR-proANP as well as CRP and NT-proBNP were predictive of
the onset of HF, independent of risk factors or other markers (36). In a comparison of NT-proBNP and MR-proBNP in a sample of 525 chronic
HF patients of all NYHA classes, MR-proANP was found to be positively
correlated with NYHA class, and after correction for NT-proBNP, age, ejection
fraction, NYHA class, creatinine, and BMI, MR-proANP was found to be a
predictor of poor survival (37). Overall the study concluded that MR-proANP independently predicts
mortality, and adds prognostic value when combined with NT-proBNP (37).
MR-proANP has both diagnostic and
prognostic utility in the treatment of HF patients. Used correctly, MR-proANP
can aid in risk stratification, particularly in unsure cases and in concert
with BNP and other biomarkers.
Adrenomedullin
The BACH trial (34) also evaluated the prognostic utility of MR-proADM in acute HF
patients presenting to the ED with dyspnea. Results revealed that MR-proADM
performed better to BNP/NT-proBNP in predicting 90-day death or
re-hospitalization due to cardiovascular causes. Survivors were found to have
median MR-proADM level of 0.84 nmol/L compared to non-survivors-1.57 nmol/L
(P<0.0001) (34). A follow-up study (38) to the BACH trial concluded that biomarkers that proved superior to
natriuretic peptides in predicting 14-day mortality were Copeptin and
MR-proADM. Furthermore, combining MR-proADM and copeptin in predicting 14-day
mortality achieved the best AUC of 0.818 (38). Klip et al. (39) examining the prognostic AMI demonstrated that those with elevated
MR-proADM levels had a threefold increased risk of all-cause mortality.
Numerous studies conducted over the
last decade have expanded our knowledge regarding the role of adrenomedullin in
prognosticating patients with acute and chronic HF. Although the data suggests
that MR-proADM is a robust marker in predicting mortality in patients with HF,
further evidence determining its superiority to benchmark markers such as
natriuretic peptides is warranted.
Markers of myocyte remodelingOther Section
ST2
ST2, an inflammatory cytokine and
member of the interleukin (IL–1) receptor family, appears to predict mortality
and heart failure in patients with acute MI and may play a vital role in
cardiac pathophysiology (40-45). ST2 is thought to be involved in modifying immunologic processes,
specifically mediated by T-helper 2 lymphocytes (46). Interleukin-33, a hormone which may protect against LVH and
myocardial fibrosis (43) has recently been identified as the ligand for ST2 (42). The interaction between IL-33 and ST2L is necessary for the
protective effect of IL-33 making it counterintuitive that high levels of sST2
have a deleterious effect. Because sST2 lacks both the transmembrane and the
intracellular domains of its membrane-bound counterpart ST2L, excess levels of
sST2 bind and neutralize IL-33 without subsequently activating the beneficial
signaling cascade. In this way, sST2 acts as a decoy receptor, limiting the
availability of IL-33 to bind and activate the protective effects of ST2L (44,45).
The PRIDE study found that in those
presenting to the ED with dyspnea, ST2 levels were significantly higher in
those diagnosed with acute HF versus those without (47). Higher median concentrations of ST2 were seen in patients with ADHF
plus impaired left ventricular systolic function than those with non-systolic
HF. ST2 was demonstrated to be at least as predictive of death as NT-proBNP.
Even in patients with elevated values of NT-proBNP, the majority of events occurred
in subjects with elevated ST2 levels at presentation. Patients with elevated
levels of both ST2 and BNP are at a considerably high risk of death compared
with patients with none or with only one marker elevated (47,48).
As shown by Shimpo et al. (49), serum ST2 levels are important predictors of death and heart failure
in patients presenting with ST-elevation myocardial infarction (STEMI). For the
combined cohort of 810 patients in the TIMI-14 and ENTIRE-TIMI-23 trial with
acute MI, baseline levels of ST2 were significantly higher in those patients
who died or developed new congestive heart failure by 30 days. Moreover, in an
analysis by quartiles of ST2, the risk of death and the composite of death or
congestive heart failure increased in a graded stepwise fashion with higher
levels of ST2. Overall, serum ST2 may be of prognostic value in assessing risk
for heart failure and death.
Growth differentiation factor-15
GDF-15 is a member of the
transforming growth factor beta-cytokine superfamily and has been recognized as
a potential biomarker of HF (50). GDF-15 is expressed at its highest levels in the liver (51), but under conditions of stress in the heart such as inflammation,
GDF-15 is released by cardiac myocytes, with a normal circulating concentration
of <1,200 ng/L (52-54). GDF-15 exhibits protective effects in the heart by inhibiting
apoptosis, hypertrophy, and adverse remodeling in the injured heart (55). Overexpression of GDF-15 is also associated with other conditions
including certain cancers, pregnancy (56), atherosclerosis, and vascular injury (57).
In post-MI patients, GDF correlates
with NT-proBNP and together increased risk of death or HF above other clinical
factors, even allowing patients to be stratified into high, medium, and low
risk groups (58). GDF-15 appears to have a graded relationship with all-cause mortality
(54,55). Higher levels of GDF-15 on admission had higher death rates at 1
year: those in the >1,800 ng/L range had a 14% death rate compared with 5%
death (59). In the Val-HEFT study, elevated GDF-15 was associated with an increased
risk of mortality or a first morbid event in those with symptomatic heart
failure. Combined with BNP and TnT, GDF-15 allowed patients to be categorized
into subgroups with very different risks of adverse events (ischemic vs. non-ischemic) (60). Higher levels were associated with features of worse heart failure
and biomarkers of neurohormonal activation, inflammation, myocyte injury, and
renal dysfunction (60).
In patients with stages A-C of early
HF, GDF-15 was elevated compared to healthy controls, progressively increased
with worsening heart disease, and correlated with several echocardiographic
variables of structural abnormality (61). GDF-15 can be used to identify those patients who have HF with a
preserved ejection fraction (HFpEF) (62). GDF-15 may also help distinguish between patients with normal
diastolic function and patients with asymptomatic LV diastolic dysfunction (63).
Overall, GDF-15 is valuable as both a
prognostic and diagnostic marker in HF, although its lack of specificity makes
it unable to be used as a lone biomarker for HF. GDF-15 should be used in
combination with other clinical factors and indicators for more specific
information.
Galectin-3
Inflammatory and fibrotic processes
are central to cardiac remodeling and the development of HF. Galectin-3,
secreted by activated macrophages, causes cardiac fibrosis via proliferation of
cardiac fibroblasts and deposition and irreversible cross-linking of collagen I
in myocytes (64). Recent examinations of galectin-3 in the context of HF have revealed
the potential clinical value of galectin-3 as a prognostic indicator (65-67). Most commonly known for its regulation in inflammation, immunity, and
cancer, galectin-3 may be a player in cardiac pathophysiology and act as
surrogate indicator of cardiac remodeling and fibrosis apparent in HF (67).
In the PROVE IT-TIMI 22 study (65), higher galectin-3 levels in patients hospitalized for ACS showed a
positive graded relationship with the development of HF. After adjustment for
prior HF, prior MI, hypertension, and diabetes, this correlation remained
significant, though accounting for BNP slightly attenuated the relationship (65). In the COACH trial, doubling of galectin-3 was associated with twice
the risk of death or rehospitalization over a mean follow-up period of 18
months. Those with NYHA class III and IV had higher galectin-3 than NYHA II
patients (P<0.001). Galectin-3 was also found to be correlated with the
inflammatory cytokines CRP, interleukin-6 (IL-6), and vascular endothelial
growth factor (VEGF) (66). In another study, plasma galectin-3 was not very valuable in the
diagnosis of HF, but had strong prognostic value in the prediction of death and
recurrent HF within 60 days (68).
Expression of galectin-3 appears to
occur before evident HF and thus may be more useful to predict and prevent
disease. Ideally, future applications of galectin-3 may be to classify and risk
stratify the type of HF into “remodeling” (high risk) and “non-remodeling” (low
risk) to help physicians tailor their treatment plans accordingly.
Markers of myocyte injuryOther Section
High sensitivity troponin
Patients with acute HF often have
ischemic events as the predominant cause (69). When comparing high sensitive cTnI and NT-proBNP to cardiac troponins
measured using conventional assay in 258 patients with congestive HF
(EF<45%), high sensitive cTnI (>0.03 ng/mL, P=0.016) and NT-proBNP
(>627 pg/mL, P=0.0063) were single best independent prognostic predictors
where as cardiac troponins (>0.03 ng/mL) measured using conventional assays
was not. On multivariate analysis in predicting mortality, those with elevated
high sensitivity cTnI and NT-proBNP had a hazard ratio of 5.74 (P<0.0001) (70).
High sensitivity assays have
certainly improved diagnostic capabilities in patients presenting with acute
HF. In a study done by Xue et al. (71) in 144 acute HF patients demonstrated that those with troponin I
levels >23.25 ng/mL were at increased risk of mortality and HF-related
readmission (P=0.003) and elevated troponin I and BNP had the highest combined
event rate of 39% (71).
Several studies have assessed the
importance of measuring high sensitive cardiac troponins that are detected in
the serum in patient with stable-chronic HF in order to establish prognostic
potential and future cardiovascular events (72,73).
The utility of cardiac troponinT
(cTnT) in detecting sub-myocardial injury was demonstrated by Miller et al. (73) in 172 asymptomatic patients with class III and IV HF. Results
revealed that in patients with consistently elevated troponin levels (>0.01
ng/mL) even in the absence of clinical symptoms were at an increased risk of
mortality and cardiac transplantation.
The advent of high sensitive assays
has made it easier to detect previously undetectable levels of cardiac
troponins. Latini et al. (74) demonstrated elevations in high sensitive assay cardiac troponin T
(Hs-cTnT) in 90% of participants with a 35.6% associated mortality risk
(P<0.0001). Furthermore, the addition of BNP and/or Hs-cTnT improved
prognostic potential in patients with chronic HF. Expanding on the role of NPs
and cTn in risk stratification of chronic HF patients, Tsutamoto et al. (75) demonstrated that elevations in NT-proBNP (>627 pg/mL) and Hs-cTnI
(>0.03 ng/mL) carried the highest risk of mortality (P<0.0001). Pascual-Figal et al. (76) demonstrated that in 107 patients hospitalized with ADHF, sST2, high
sensitive troponin T and NT-proBNP were all independently predictive of higher
risk of death and 1-year mortality and measuring their levels individually or
in combination may provide additional prognostic information in patients with
ADHF.
Cardiac troponins measured using high
sensitive assays have proved to be superior to conventional assays. Future
studies may benefit from exploring the importance of serial monitoring of high
sensitive troponins in larger populations with emphasis on accurate
interpretation of troponin levels in order to detect all patients with
myocardial injury and heart failure.
Markers in comorbidities associated with HFOther Section
Neutrophil gelatinase-associated
lipocalin
Neutrophil gelatinase-associated
lipocalin (NGAL) is a protein of the lipocalin family that consists of
polypeptide chain of 178-amino-acids with a molecular mass of 25 kDa. It is
expressed by neutrophils and various epithelial cells (77,78). Being an acute phase protein its expression is up-regulated under
diverse conditions (79-82).
There is evidence that NGAL is one of
the earliest kidney biomarkers of nephrotoxic and ischemic injury in animal
models and is elevated in the urine and blood of humans soon after acute kidney
injury (AKI) (83). NGAL has gained attention as a structural biomarker in the urine and
plasma for an early AKI diagnosis and for the prediction of clinical outcomes
including mortality and the need for renal-replacement therapy. Serum and urine
levels of NGAL have been studied in both chronic and acute HF and have shown
much superior performance to serum creatinine in the rapid and early detection
of acute kidney injury (84-86).
Chronic HF patients have been found
to have significantly higher levels of both serum and urine NGAL when compared
with control subjects, despite having only modest reductions in estimated
glomerular filtration rates (eGFR) (84,85,87-89). Damman et al. (90) demonstrated that urinary NGAL was significantly associated with
primary outcome after adjustment for risk factors and clinical variables (P=0.042).
This relationship remained significant even in those with normal GFR. Perhaps
urine NGAL is a better marker of prognosis in chronic HF patients due to the
fact that these patients have a high risk of cardiorenal insults from not only
prerenal decreases in renal blood flow but also from nephrotoxic therapies such
as diuretics.
NGAL also seems to have a role as a
biomarker in cases of acute HF. In the (OPTIMAAL) study done by Dickstein et al. (91) in a subgroup of 236 patients with acute HF following MI, serum NGAL
levels were found to be elevated both at baseline and on followup in patients
with NYHA class III (vs. NYHA I/II). Patients with baseline
serum NGAL levels above the median showed a trend to higher incidence of the
composite endpoint of nonfatal MI, CV death, all-cause death, and stroke.
The recent GALLANT study (92) demonstrated the prognostic utility of plasma NGAL along with BNP in
186 patients with ADHF. Patients with higher NGAL levels had significantly more
HF-related adverse outcomes in 30-days than those with lower levels (134 vs. 84 ng/mL; P<0.001) and those with elevations in both NGAL and BNP were
at significant risk for HF events (P=0.006) as was also the case for those with
high NGAL but low BNP (P=0.036). These results suggest that using both markers
can serve as powerful tool in the risk stratification for those with acute HF (92).
Future research can benefit by
further exploring the role of NGAL in combination with NPs in order to reduce
diuretic overuse and timely discharge patients with acute and chronic HF.
Procalcitonin
In the ED, the diagnosis and
management of patients suspected of HF presenting with dyspnea can be an
incredible challenge if pneumonia is present. Low sensitivity and specificity
of clinical symptoms/ signs and chest X-ray imaging make it difficult to distinguish
cardiac from non-cardiac dyspnea (93).
Procalcitonin (PCT) is a serum
calcitonin precursor and has been shown to be elevated in both gram-positive
and gram-negative bacterial infections while being attenuated in viral
infections (93-96). Studies suggest that PCT levels strongly correlate with the severity
of infections and are thus able to guide antibiotic therapy in patients with
respiratory tract infections (96).
The recently conducted follow-up
study to the BACH trial (97) demonstrated the diagnostic utility of PCT in 1,641 patients
presenting with dyspnea to the ED. PCT was significantly associated with
all-cause 90-day mortality in those with acute HF (P=0.0024) and was found to
be very useful in guiding antibiotic therapy in those with pneumonia and acute
HF. When divided into groups based on PCT levels, various survival trends were
found. Those with PCT >0.21 ng/mL not treated with antibiotics had lower survival
rates (P=0.046). Moreover, those with PCT <0.05 ng/mL, had increased
mortality if receiving antibiotic therapy (P=0.049).
While these results need to be
validated in a large randomized control trial, early indications imply PCT
could be a valuable diagnostic marker in patients with undifferentiated dyspnea
presenting to the ED able to diagnose pneumonia and guide antibiotic treatment.
Inflammatory markers in heart failureOther Section
Inflammatory markers have been
identified as potential indicators of heart failure and future adverse events.
Proinflammatory cytokines may represent a class of biological mediators that
are activated in CHF, akin to but distinct from neurohormones and the
natriuretic peptide pathways. Plasma levels of these inflammatory markers are
useful in prediction of new heart failure as well as in risk stratification of
established heart failure.
IL-6
IL-6 is a pleiotropic cytokine with a
broad range of humoral and cellular immune effects (98-102). IL-6 is produced not only by immune cells and immune accessory cells
but also by cardiovascular components, such as endothelial cells, vascular
smooth-muscle cells, and ischemic myocytes (103-106). Elevated levels of IL-6 have also been found in patients suffering
from acute and chronic heart failure. Raised levels of IL-6 correlate with
severity of NYHA functional class, lowered ejection fraction, and are
associated with poor prognosis (107-110). Pudil et al. (111) explored the prognostic role of IL-6 in patients presenting with acute
decompensated heart failure (ADHF). Plasma levels of IL-6 were found to be
significantly elevated in patients with ADHF as compared to normal controls.
Significant positive correlations were also found between plasma IL-6 and
NT-proBNP levels. Both remained strong independent predictor of 1-year
mortality.
In another study (112), Maeda et al. demonstrated that
among the neurohumoral factors and cytokines measured at baseline and three
months after optimized treatment for heart failure, only sustained high levels
of BNP and IL-6 at three months are independent risk factors of mortality in
patients with CHF, despite improvements in left ventricular ejection fraction and
symptoms.
Fas (Apo 1)
Fas, also called apoptosis antigen-1
(Apo1), is a member of the TNF family, which mediates apoptosis. Fas is found
in various tissues including the thymus, liver, ovary, lung and heart (113-115). In cardiomyocytes, Fas is upregulated as a result of apoptotic cell
death due to hypoxia (115) and overstretching (116). A soluble form of Fas (sFas) lacking transmembrane domain was also
found in serum of human subjects (117) & is thought to be increased in patients with cardiovascular
diseases.
Okuyama et al. found that the circulating sFas level was higher in 61 patients with
varying degrees of CHF and actually increased in relation to severity of CHF (118). It was also demonstrated that sFas was related to soluble forms of
the similar receptor family, sTNF-R1 and sTNF-R2 and may play an important role
in determining severity of CHF. Tsutamoto et al. (119) investigated the relationship between plasma levels of cardiac
natriuretic peptides and those of sFas and TNF-α. In 96 patients with HF, they
found no significant correlation between sFas levels and those of ANP or BNP.
Plasma levels of sFas were significantly higher in patients with severe CHF
than in patients with mild CHF. Also, stepwise multivariate analysis
demonstrated that high levels of sFas and BNP and a low ejection fraction were
independent significant prognostic predictors. This study clearly demonstrated
that patients with high sFas levels had a significantly higher death rate than
those with low sFas levels and plasma sFas is a useful prognostic marker in
pathogenesis of CHF.
TNF-α
Tumor necrosis factor alpha, a
classic biomarker of inflammatory processes, has displayed clinical utility as
a marker in cases of heart failure (120). In fact, myocardial TNF-α and its receptors (type 1 and type 2) are
intricately involved in the pathogenesis of HF. Specifically, excessive
expression of TNF-α and type-1 receptor stimulation can lead to cardiac
hypertrophy, fibrosis, contractile dysfunction and apoptosis while lower TNF-α
and type-2 receptor activation is cardioprotective (121). A study of 1200 HF patients found that TNF-α levels were related
directly to NYHA stage and higher levels were associated with poorer prognosis
(122). A more recent study found that in those with recently diagnosed HF,
TNF-α level were associated with abnormal left atrial function and advanced
left systolic and diastolic dysfunction (123). Interestingly, soluble type-1 TNF-α receptor was the only independent
predictor of future HF or death after adjustment for clinical and baseline
characteristics in a study of patients with recent MI (124). While much of the research on TNF-α and HF is promising, most
clinicians would seem to demand a biomarker more specific to the HF disease
process.
CRP
Another classic marker of
inflammation, the acute phase protein C-reactive protein (CRP) has been
associated with presence of heart failure (125-128) and cardiovascular risk (129). Several studies to date have examined
what role, CRP may play in cases of HF. Cesari et al. demonstrated that elevated CRP values in elderly patients can predict
future HF onset (128). A large study by Engstrom et al. on members of the
general population found that those with a CRP ≥3 mg/L were twice as likely to
be hospitalized with HF over a mean follow-up of 13 years (130). Unfortunately, CRP lacks specificity to HF and cardiovascular
disease, perhaps even more so than TNF-α. CRP's correlation with functional
parameters such as EF has been inconsistent however as some studies have found
significant correlation whiles other haves not (131). CRP may have some clinical use in cases of HF, but it is not an ideal
biomarker for the disease.
Pentraxin-3
Pentraxin-3 (PTX3), a member of the
pentraxin family is believed to be a more specific marker of vascular
inflammation than CRP and other members of its family (132). PTX3 has also been shown to predict unfavorable clinical outcomes in
those with HF (133,134). A recent study by Matsubara et al. (135) demonstrated that PTX3, TNF-α and IL-6 but not hsCRP were elevated
significantly in those with HFPEF (HF with preserved EF) but not in those
without HF (136). Furthermore, multivariate analysis showed that only elevated
PTX3 among inflammatory markers correlated with HFPEF (P<0.01) and in those
with LV diastolic dysfunction but without HF (P<0.05). Another study
demonstrated that patients with stable CAD, PTX3 had a HR of 1.5 (P=0.21) after
adjustment for eGFR; perhaps showing some merit in this study population (132). Research so far indicates that PTX3 could be a significant marker of
vascular inflammation, diastolic dysfunction and HF. Large randomized
controlled trials are necessary to confirm and elaborate on these early
findings.
Myeloperoxidase
Myeloperoxidase (MPO) is an enzyme
derived from leukocytes and endothelial cells that catalyzes the creation of
several reactive oxidant molecules (including LDL oxidation) and contributes to
endothelial dysfunction by reducing levels of nitric oxide (136-138). It has demonstrated prognostic value in cases of ACS and chest pain (139-141) and has recently been studied successfully in cases of HF
demonstrating positive correlation with both NYHA stage and diastolic dysfunction
(142,143). In a study of 140 patients with chronic systolic HF, the combination
of MPO and BNP increased the prognostic accuracy of future events to AUC 0.70
(P=0.0004) compared to AUC 0.66 (P=0.0003) for BNP alone (144). Tang et al. came across an
interesting finding when examining a population of 3,733 healtly elderly
subjects: the relation between HF risk and elevated MPO was greater in patients
without traditional risk factors (i.e. systolic BP <136 mmHg, age <75, no
diabetes) (137). This could be a valuable utility in clinical situations as current
screening methods do not have the ability to risk stratify those lacking
traditional CV risk factors. With further research, MPO could perhaps fill this
void and help countless clinicians better manage HF risk.
Markers of neurohormonal activationOther Section
Norepinephrine;
renin-angiotensin-aldosterone system; endothelin-1/CT-proET-1
Heart failure has long been
considered to be primarily a hemodynamic disorder, in which heart pumps
insufficient blood and characterized by symptoms of congestion. In recent
years, neurohormonal activation has been found in heart failure, particularly
of the sympathetic nervous system (145,146) and the renin-angiotensin-aldosterone system (147). However, the utility of neurohormones as diagnostic or prognostic
biomarkers in heart failure is varied, particularly due to the influence of
blocking agents commonly used in heart failure, including beta-blockers, ACE
inhibitors, and aldosterone receptor blockers (ARBs) (148).
Increased levels of plasma and
urinary excretion of norepinephrine were found to be independent predictors of
mortality (145) and led to the investigation of the deleterious effects of
neurohormonal activation present in HF (146). In the Val-HeFT trial, the prognostic utility of BNP, norepinephrine,
renin activity (PRA), aldosterone, and endothelin were compared in 4,300
patients with stable heart failure of NYHA II-IV severity. Aside from BNP,
which was most strongly associated, in multivariate analysis norepinephrine was
the only marker significantly associated with poor outcome after an average
follow-up period of 23 months (149). However, Givertz and Braunwald comment that the use of norepinephrine
as a routine clinical biomarker is impractical given the need for
high-performance liquid chromatography, and thus is not a marker to be relied
on particularly at points of care (150). In the VERITAS study, CRP, BNP-32, endothelin-1, and norepinephrine
among other markers were measured at baseline, 24 and 48 h and 7 and 30 days in
patients with acute heart failure. On univariate analysis, CRP, BNP and
endothelin-1 predicted worse outcomes at 30 days; on multivariate analysis,
only CRP and BNP were found to be significantly associated with this outcome.
After consideration of other variables including age, baseline blood pressure,
serum sodium and creatinine, only age and BNP were significant (151).
In an examination of the predictive
value of plasma renin activity (PRA) among other neurohormone biomarkers,
ejection fraction, NT-proBNP, and PRA were independent predictors of cardiac
death in those with heart failure. Elevated levels of both NT-proBNP and high
PRA indicated greatest risk of cardiac death. Overall, PRA resulted to be an
independent prognostic marker in those with systolic heart failure, and added
prognostic value to NT-proBNP and ejection fraction. PRA may be most useful in
identifying those needing better therapy, particularly RAAS blockade (152).
Endothelin-1, a potent
vasoconstrictor and potentiator of sympathetic neurohormones produced in the
endothelial cells of blood vessels, is also a marker of sympathetic activation.
Plasma levels of both endothelin-1 and its precursor, big endothelin-1, are
increased in heart failure and correlated with pulmonary artery pressure,
disease severity, and mortality (153,154). A recently identified stable surrogate marker of endothelin-1,
C-terminal pro-endothelin-1 (CT-proET-1), has also been suggested as a
prognosticator. In a recent study on outcomes in 3,717 patients with stable
coronary artery disease, after adjustment for clinical cardiovascular risk
predictors and ejection fraction, elevated levels of CT-proET-1 as well as
MR-proANP and MR-proADM were independently correlated with risk of cardiac
death or heart failure (155). In another sample of 491 patients with systolic heart failure,
increasing CT-proET-1 was correlated with increased mortality at 12 months (156). However, endothelin-1 or CT-proET-1 has not yet become an established
marker of prognosis (157). Furthermore, recent investigations into endothelin-1 receptor
blockers as a potential therapy have not demonstrated significant clinical
benefits or preventive effects (154,157).
Overall, due to clinical
impracticality and widespread use of diuretics and neurohormonal blockade,
norepinephrine, angiotensin, and aldosterone are not ideal prognosticators of
disease. Renin may prove to be useful in assessing the effectiveness of
neurohormone blockade therapies. CT-proET-1 may be an emerging biomarker with
prognostic potential, though further research is necessary.
AVP/Copeptin
Arginine vasopressin, released from
the posterior pituitary and a major player in fluid homeostasis, is also noted
to be 2-3 times higher in heart failure patients (158). However, AVP as a biomarker has not been used due to short half life
and impracticality in measuring. The precursor of AVP, preprovasopressin, is
also the parent hormone to a more stable fragment, C-terminal proAVP or
copeptin (159). Copeptin is stable in serum at room temperature, is quicker to assay,
and is generally a robust surrogate marker of AVP.
Several studies recently have
indicated the possible prognostic value of copeptin in heart failure patients.
In the BACH trial, copeptin was associated with significantly worse outcomes
including increased mortality, readmissions, and emergency department visits at
90 days, particularly in those with hyponatremia. Copeptin was highly prognostic
for adverse events and added prognostic value to clinical indicators,
natriuretic peptide markers, and serum sodium (160). In another recent study done in Danish heart failure clinic on 340
patients, copeptin was found to be a significant predictor of hospitalization
or death but did not predict mortality independent from NT-proBNP (161). Copeptin has also been shown to be associated with NYHA functional
class and was the strongest predictor of mortality in patients with class II or
III heart failure. In this study, copeptin was stronger than BNP and NT-proBNP,
but they appear to be closely related (162).
Copeptin as a surrogate marker of AVP
appears to be an emerging biomarker with good prognostic potential and may add
information to natriuretic peptide biomarkers.
Matrix metalloproteinases
As mediators of collagen metabolism
and extracellular matrix (ECM) homeostasis (163), the extensive matrix metalloproteinase family has rightly come to the
attention of researchers seeking biomarkers for heart failure. Some precursors
to clinical HF such as LVH involve ventricular remodeling and the enzymes
behind this pathophysiology can offer unique insight into the disease process
and HF risks within each individual (164).
The strength of MMP’s as biomarkers
may come from their diversity. They are organized into several different
classes such as the collagenases (MMP-1, MMP-8), the gelatinases (MMP-2, MMP-9)
and the stomelysins (MMP-3, MMP-7) (162). These enzymes have been analyzed individually to varying degrees of
success. For example, MMP-2 has been suggested to be more useful than BNP in
the identification of HFPEF (165), while its fellow gelatinase MMP-9 was found to be inferior to both
BNP as a marker of remodeling (166) and to tissue inhibitor of MMP-1 (TIMP-1) as a predictor of mortality
in those with chronic HF (167).
While stand-alone marker results for
MMP’s have varied, there may be strength in numbers as far as the utilization
of a MMP biomarker panel. In a study of 144 subjects with LVH but no HF, Zile et al. found that panels of MMP's along with clinical covariates (such as BP,
age, sex, BMI) performed better than individual markers, clinical covariates
alone or NT-proBNP alone. Specifically, for detection of LVH, the panel of
MMP-7, MMP-9, tissue inhibitor of MMP-1 (TIMP-1), collagen III N-terminal
polypeptide (PIIINP) and NT-proBNP when combined with clinical covariates had
an AUC of 0.80 (164). Similar success was found in individuals with LVH that had progressed
to HFPEF (164). The authors suggest that panels such as these could better reflect
the complex pathophysiology occurring in cases of ventricular remodeling and
allow those at early stages of these changes to be identified before the
progression to overt HF or before the worsening of existing HFPEF.
Panels such as these, if validated
could become a powerful tool in identifying risk and simplifying the diagnosis
of a condition (HFPEF) that currently requires costly investigations and
subspecialist interpretations.
ConclusionsOther
Section
Table 2 shows a hypothesized strength of evidence table for different biomarkers
based on a review of previous supporting literature. Cardiac biomarkers with
their objectivity, reproducibility and accessibility are excellent adjuncts to
physical examination and imaging studies in HF diagnosis and risk
stratification. With advances in medical research, new biomarkers representing
different physiological processes continue to emerge, providing an ever clearer
risk profile for patients with HF. Biomarkers not only serve as traditional
predictors of prognosis, they can also help to identify high-risk patients who
need closer monitoring and more aggressive therapy. By continually enhancing
our understanding of underlying pathophysiology of HF, improving our ability to
identify high risk patients, and helping us to tailor therapies to an
individual’s unique risk profile, biomarkers will undoubtedly improve the
effectiveness of HF therapy and lead to better patient outcomes.
Table
2 Strength of evidence for
individual biomarkers for diagnosis and prognosis of HF
|
||
Biomarker
|
Diagnostic
Capability
|
Prognostic
Capability
|
BNP
|
+++
|
+++
|
NT-proBNP
|
+++
|
+++
|
ST2
|
-
|
++
|
GDF-15
|
-
|
+
|
Galectin
|
-
|
+
|
MR-proANP
|
++
|
++
|
NGAL
|
+++
|
+++
|
Hs-Tn
|
+++
|
+++
|
MR-proADM
|
-
|
+++
|
Procalcitonin
|
+++
|
+++
|
Adapted
from: Maisel A, Mueller C, Nowak R, et al. Mid-region prohormone
markers for diagnosis and prognosis in acute dyspnea: results from the BACH (Biomarkers
in Acute HF) trail. J Am Coll Cardiol 2010;55:2062-76
|
AcknowledgementsOther
Section
Disclosures: The authors declare no conflict of interest.
ReferencesOther
Section
1.
Haldeman GA, Croft JB, Giles WH, et al. Hospitalization of Patients with
HF: National Hospital Discharge Survey, 1985 to 1995. Am Heart J
1999;137:352-60.
2.
Roger VL, Go AS, Lloyd- Jones DM, et al. Heart Disease and stroke
statistics: 2011 update: a report from American Heart Association. Circulation
2011;123:e18-e209.
3.
Nakao K, Ogawa Y, suga S, et al. Molecular biology and biochemistry of
the natriuretic peptide system. II: Natriuretic peptide receptors. J Hypertens
1992;10:1111-4.
4.
Jorrani SA, Prabhu SD, Valdes R Jr. Strategies for developing biomarkers
of HF. Clin Chem 2004;50:265-78.
5.
Saremi A, Gopal D, Maisel AS. Brain natriuretic peptide-guided therapy
in the inpatient management of decompensated HF. Expert Rev Cardiovasc Ther
2012;10:191-203.
6.
Mueller C, Scholer A, Laule-Kilian K, et al. Use of B-type natriuretic
peptide in the evaluation and management of acute dyspnea. N Engl J Med
2004;350:647-54.
7.
Xu-Cai YO, Wu Q. Molecular forms of natriuretic peptides in HF and their
implications. Heart 2010;96:419-24.
8.
McCullough PA, Omland T, Maisel AS. B-type Natriuretic Peptides: A
Diagnostic Breakthrough for Clinicians. Rev Cardiovasc Med 2003;4:72-80.
9.
Semenov AG, Tamm NN, Seferian KR, et al. Processing of Pro-B-Type
Natriuretic Peptide Furin and Corin as Candidate Convertases. Clin Chem
2010;56:1166-76.
10. Mueller T, Gegenhuber A, Poelz W, et
al. Diagnostic accuracy of B-type natriuretic peptide and amino terminal proBNP
in the emergency diagnosis of HF. Heart 2005;91:606-12.
11. Moertl D, Berger R, Struck J, et al.
Comparison of midregional pro-atrial and B-type natriuretic peptides in chronic
HF: influencing factors, detection of left ventricular systolic dysfunction,
and prediction of death. J Am Coll Cardiol 2009;53:1783-90.
12. Daggubati S, Parks JR, Overton RM, et
al. Adrenomedullin, endothelin, neuropeptide Y, atrial, brain, and
C-natriuretic prohormone peptides compared as early HF indicators. Cardiovasc
Res 1997;36:246-55.
13. Jougasaki M, Grantham JA, Redfield
MM, et al. Regulation of cardiac adrenomedullin in HF. Peptides
2001;22:1841-50.
14. Meeran K, O’Shea D, Upton PD, et al.
Circulating adrenomedullin does not regulate systemic blood pressure but
increases plasma prolactin after intravenous infusion in humans: a
pharmacokinetic study. J Clin Endocrinol Metab 1997;82:95-100.
15. Cowie MR, Jourdain P, Maisel AS, et
al. Clinical applications of B-type natriuretic peptide (BNP) testing. Eur
Heart J 2003;24:1710-8.
16. Maisel A, Muller C, Adams K Jr, et
al. State of the art: Using natriuretic peptide levels in clinical practice.
Eur J Heart Fail 2008;10:824-39.
17. Januzzi Jr JL. The role of
natriuretic peptide testing in guiding chronic heart failure management: Review
of available data and recommendations for use. Archives of cardiovascular
disease 2012;105:40-50.
18. Leuchte HH, Holzapfel M, Baumgartner
RA, et al. Clinical significance of brain natriuretic peptide in primary
pulmonary hypertension. J Am Coll Cardiol 2004;43:764-70.
19. Daniels LB, Clopton P, Bhalla V, et
al. How obesity affects the cut-points for B-type natriuretic peptide in the
diagnosis of acute heart failure. Results from the Breathing Not Properly Study.
Am Heart J 2006;151:1006-12.
20. Horwich TB, Hamilton MA, Fonarow GC.
B-type natriuretic peptide levels in obese patients with advanced heart
failure. J Am Coll Cardiol 2006;47:85-90.
21. Maisel AS, Choudhary R. Biomarkers in
acute heart failure-state of the art. Nat Rev Cardiol 2012. [Epub ahead of
print].
22. Maisel AS, Hollander JE, Guss D, et
al. Primary results of the Rapid ED HF Outpatient Trial (REDHOT). J Am Coll
Cardiol 2007;49:1943-50.
23. Di Somma S, Magrini L, Pittoni V, et
al. In-hospital percentage BNP reduction is highly predictive for adverse
events in patients admitted for acute HF: the Italian RED Study. Crit Care
2010;14:R116.
24. Fonarow GC, Peacock WF, Phillips CO,
et al. Admission B-type Natriuretic Peptide Levels and In-Hospital Mortality in
Acute Decompensated HF. J Am Coll Cardiol 2007;49:1943-50.
25. Masson S, Latini R, Anand IS, et al.
Direct comparison of B-Type Natriuretic Peptide (BNP) and Amino-Terminal proBNP
in a Large Population of Patients with Chronic and Symptomatic Heart Failure:
The Valsartan Heart Failure (Val-HeFT) Data. Clin Chem 2006;52:1528-38.
26. Doust JA, Pietrzak E, Dobson A, et
al. How well does B-type natriuretic peptide predict death and cardiac events
in patients with heart failure: systematic review. BMJ 2005;330:625.
27. Nishiyama K, Tsutamoto T, Yamaji M,
et al. Biological Variation of Brain Natriuretic Peptide and Cardiac Events in
Stable Outpatients with Nonischemic Chronic Heart Failure. Circ J
2011;75:341-7.
28. Di Somma S, De Berardinis B,
Bongiovanni C, et al. Use of BNP and bioimpedance to drive therapy in heart
failure patients. Congest Heart Fail 2010;16:S56-61.
29. van der Burg-de Graauw N, Cobbaert
CM, Middelhoff CJ, et al. The additive value of N-terminal pro-B-type
natriuretic peptide testing at the ED in patients with acute dyspnea. Eur J
Intern Med 2009;20:301-6.
30. Moe GW, Howlett J, Januzzi JL, et al.
N-Terminal Pro-B-Type Natriuretic Peptide Testing Improves the Management of
Patients With Suspected Acute HF: Primary Results of the Canadian Prospective
Randomized Multicenter IMPROVE-CHF Study. Circulation 2007;115:3103-10.
31. Waldo SW, Beede J, Isakson S, et al.
Pro-B-Type Natriuretic Peptide Levels in Acute Decompensated Heart Failure. J
Am Coll Cardiol 2008;51:1874-82.
32. Cleland JGF, Taylor J, Freemantle N,
et al. Relationship between plasma concentrations of N-terminal pro brain
natriuretic peptide and the characteristics and outcome of patients with a
clinical diagnosis of diastolic heart failure: a report from PEP-CHF study. Eur
J Heart Fail 2012;14:487-94.
33. Betti I, Castelli G, Barchielli A, et
al. The role of N-terminal PRO- brain natriuretic peptide and echocardiography
for screening asymptomatic left ventricular dysfunction in a population at high
risk for heart failure. The PROBE-HF study. J Card Fail 2009;15:377-84.
34. Maisel A, Mueller C, Nowak R, et al.
Mid-region pro-hormone markers for diagnosis and prognosis in acute
dyspnea:results from the BACH (Biomarkers in Acute HF) trial. J Am Coll Cardiol
2010;55:2062-76.
35. Daniels LB, Clopton P, Potocki M, et
al. Influence of age, race, sex, and body mass index on interpretation of
midregional pro atrial natriuretic peptide for the diagnosis of acute
heartfailure: results from the BACH multinational study. Eur J Heart Fail
2012;14:22-31.
36. Smith JG, Newton-Cheh C, Almgren P,
et al. Assessment of conventional cardiovascular risk factors and multiple
biomarkers for the prediction of incident HF and atrial fibrillation. J Am Coll
Cardiol 2010;56:1712-9.
37. Von Haehling S, Jankowska EA,
Morgenthaler NG, et al. Comparison of midregional pro-atrial natriuretic
peptide with N-terminal pro-B-type natriuretic peptide in predicting survival
in patients with chronic HF. J Am Coll Cardiol 2007;50:1973-80.
38. Peacock WF, Nowak R, Christenson R,
et al. Short-term Mortality Risk in ED Acute HF. Acad Emerg Med 2011;18:947-58.
39. Klip IT, Voors AA, Anker SD, et al.
Prognostic value of mid-regional pro-adrenomedullin in patients with HF after
an acute myocardial infarction. Heart 2011;97:892-8.
40. Weinberg EO, Shimpo M, De Keulenaer
GW, et al. Expression and regulation of ST2, an interleukin-1 receptor family
member, in cardiomyocites and myocardial infarction. Circulation
2002;106:2961-6.
41. Iwahana H, Yanagisawa K, Ito-Kosaka
A, et al. Different promoter usage and multiple transcription initiation sites
of the interleukin-1 receptor related human ST2 gene in UT-7 and TMI2 cells.
Eur J Biochem 1999;264:397-406.
42. Coyle AJ, Lloyd C, Tian J, et al.
Crucial role of the interleukin-1 receptor family member T1/ST2 in T Helper
cell type-2 mediated lung mucosal immune responses. J Exp Med 1999;190:895-902.
43. Sanada S, Hakuno D, Higgins LJ, et
al. IL-33 and ST2 comprise a critical biomechanically induced and
cardioprotective signaling system. J Clin Invest 2007;117:1538-49.
44. Schmitz J, Owyang A, Oldham E, et al.
IL-33, an interleukin-1 like cytokine that signals via the IL-1 receptor
related protein ST2 and induces T helper type-2 associated cytokines. Immunity
2005;23:479-90.
45. Sanada S, Hakuno D, Higgins LJ, et
al. IL-33 and ST2 comprise a critical biomechanically induced and cardioprotective
signaling system. J Clin Invest 2007;117:1538-49.
46. Weinberg EO, Shimpo M, De Keulenaer
GW, et al. Expression and regulation of ST2, an interleukin-1 receptor family
member, in cardiomyocites and myocardial infarction. Circulation
2002;106:2961-6.
47. Januzzi JL, Peacock WF, Maisel AS, et
al. Measurement of the interleukin family member ST2 in patients with acute
dyspnea. J Am Coll Cardiol 2007;50:607-13.
48. Daniels LB, Maisel AS, Clopton P, et
al. Association of ST2 levels with cardiac structure and function and mortality
in outpatients. Am Heart J 2010;160:721-8.
49. Shimpo M, Morrow DA, Weinberg EO, et
al. Serum levels of the Interleukin-1 receptor family member ST2 predict
mortality and clinical outcome in acute myocardial infarction. Circulation
2004;109:2186-90.
50. Ago T, Sadoshima J. GDF-15, a
cardioprotective TGF-B superfamily protein. AHA Journals. 2011.
51. Hsiao EC, Koniaris LG,
Zimmers-Koniaris T, et al. Characterization of growth-differentiation factor
15, a transforming growth factor beta superfamily member induced following
liver injury. Mol Cell Biol 2000;20:3742-51.
52. Secchiero P, Corallini F, Gonelli A,
et al. Atniangiogenic activity of the MDM2 antagonist nutlin-3. Circ Res
2007;100:61-9.
53. Bermudez B, Lopez S, Pacheco YM, et
al. Influence of postprandial triglyceride-rich lipoproteins on lipid-mediated
gene expression in smooth muscle cells of the human coronary artery. Cardiovasc
Res 2008;79:294-303.
54. Ding Q, Mracek T, Gonzalez-Muniesa P,
et al. Identification of macrophage inhibitory cytokine-1 in adipose tissue and
its secretion as an adipokine by human adipocytes. Endocrinology
2009;150:1688-96.
55. Kempf T, von Haehling S, Peter T, et
al. Prognostic utility of growth differentiation factor-15 in patients with
chronic HF. J Amer Card 2007;50:1054-60.
56. Moore AG, Brown DA, Fairlie WD, et
al. The transforming growth factor-ss superfamily cytokine macrophage
inhibitory cytokine-1 is present in high concentrations in the serum of
pregnant women. J Clin Endocrinol Metab 2000;85:4781-8.
57. Eggers KM, Kempf T, Lind L, et al.
Relations of growth-differentiation factor-15 to biomarkers reflecting vascular
pathologies in a population-based sample of elderly subjects. Scand J Clin Lab
Invest 2012;72:45-51.
58. Khan SQ, Ng K, Dhillon O, et al.
Growth differentiation factor-15 as a prognostic marker in patients with acute
myocardial infarction. Eur Heart J 2009;30:1057-65.
59. Kempf T, Bjorklund E, Olofsson S, et
al. Growth differentiation factor-15 improves risk stratification in ST-segment
elevation myocardial infarction. Eur Heart J 2007;28:2858-65.
60. Anand IS, Kempf T, Rector TS, et al.
Serial measurement of growth differentiation factor-15 in HF. Circulation
2010;122:1387-95.
61. Wang F, Guo Y, Yu H, et al. Growth
differentiation factor 15 in different stages of HF: potential screening implications.
Biomarkers 2010;15:671-6.
62. Stahrenberg R, Edelmann F, Mende M,
et al. The novel biomarker gowth differentiation factor 15 in HF with normal
ejection fraction. Eur J Heart Fail 2010;12:1309-16.
63. Dinh W, Futh R, Lankisch M, et al.
Growth-differentiation factor-15: a novel biomarker in patients with diastolic
dysfunction? Sociedade Brasileira de Cardologia. 2011.
64. McCullough PA, Olobatoke A, Vanhecke
TE. Galectin-3: a novel blood test for the evaluation and management of
patients with HF. Rev Cardiovasc Med 2011;12:200-10.
65. Grandin EW, Jarolim P, Murphy SA, et
al. Galectin-3 and the development of HF after acute coronary syndrome: pilot
experience from PROVE IT-TIMI 22. Clin Chem 2012;58:267-73.
66. de Boer RA, Lok DJ, Jaarsma T, et al.
Predictive value of plasma galectin-3 levels in HF with reduced and preserved
ejection fraction. Ann Med 2011;43:60-8.
67. Lok DJ, Van Der Meer P, de la Porte
PW, et al. Prognostic value of galectin-3, a novel marker of fibrosis, in
patients with chronic HF: data from the DEAL-HF study. Clin Res Cardiol
2010;99:323-328.
68. Van Kimmenade RR, Januzzi JL Jr,
Ellinor PT, et al. Utility of amino-terminal pro-brain natriuretic peptide,
galectin-3, and apelin for the evaluation of patients with acute HF. J Am Coll
Cardiol 2006;48:1217-24.
69. Daubert MA, Jeremias A. The utility
of troponin measurement to detect myocardial infarction: review of the current
findings. Vasc Health Risk Manag 2010;6:691-9.
70. Tsutamoto T, Kawahara MD, Yamaji M,
et al. Prognostic role highly sensitive cardiac troponin I in patients with
systolic HF. Am Heart J 2010;159:63-7.
71. Xue Y, Clopton P, Peacock W, et al.
Serial changes in high-sensitive troponin I predict outcome in patients with
decompensated HF. Eur J Heart Fail 2011;13:37-42.
72. Masson S, Anand I, Favero C, et al. Serial
Measurement of Cardiac Troponin T Using a Highly Sensitive Assay in Patients
With Chronic HF. Circulation 2012;125:280-8.
73. Miller WL, Hartman KA, Burritt MF, et
al. Profiles of serial changes in cardiac troponin T concentrations and outcome
in ambulatory patients with chronic heart failure. J Am Coll Cardiol
2009;54:1715-21.
74. Latini R, Masson S, Anand IS, et al.
Prognostic value of very low plasma concentrations of troponin T in patients
with stable chronic heart failure. Circulation 2007;116:1242-9.
75. Tsutamoto T, Kawahara C, Nishiyama K,
et al. Prognostic role of highly sensitive cardiac troponin I in patients with
systolic heart failure. Am Heart J 2010;159:63-7.
76. Pascual-Figal DA, Manzano-Fernandez
S, Boronat M, et al. Soluble ST2, high-sensitivity troponin T-and N-terminal
pro-B-type natriuretic peptide: compementary role for risk stratification in
acutely decompensated HF. Eur J Heart Fail 2011;13:718-25.
77. Cowland JB, Borregaard N. Molecular
characterization and pattern of tissue expression of the gene for neutrophil
gelatinase-associated lipocalin from humans. Genomics 1997;45:17-23.
78. Friedl A, Stoesz SP, Buckley P, et
al. Neutrophil gelatinase-associated lipocalin in normal and neoplastic human
tissues. Cell type-specific pattern of expression. Histochem J 1999;31:433-41.
79. Soni SS, Cruz D, Bobek I, et al.
NGAL: a biomarker of acute kidney injury and other systemic conditions. Int
Urol Nephrol 2010;42:141-50.
80. Gwira JA, Wei F, Ishibe S, et al.
Expression of neutrophil gelatinase-associated lipocalin regulates epithelial
morphogenesis in vitro. J Biol Chem 2005;280:7875-82.
81. Mori K, Lee HT, Rapoport D, et al.
Endocytic delivery of lipocalin-siderophore-iron complex rescues the kidney
from ischemia-reperfusion injury. J Clin Invest 2005;115:610-21.
82. Goetz DH, Holmes MA, Borregaard N, et
al. The neutrophil lipocalin NGAL is a bacteriostatic agent that interferes
with siderophore-mediated iron acquisition. Mol Cell 2002;10:1033-43.
83. Devarajan P. NGAL in acute kidney
injury: from serendipity to utility. Am J Kidney Dis 2008;52:395-9.
84. Yndestad A, Landro L, Ueland T, et
al. Increased systemic and myocardial expression of neutrophil
gelatinase-associated lipocalin in clinical and experimental HF. Eur Heart J
2009;30:1229-36.
85. Aghel A, Shrestha K, Mullens W, et
al. Serum neutrophil gelatinase-associated lipocalin (NGAL) in predicting
worsening renal function in acute decompensated HF. J Card Fail 2010;16:49-54.
86. Alvelos M, Pimentel R, Pinho E, et
al. Neutrophil Gelatinase-Associated Lipocalin in the Diagnosirs of Type 1
Cardio-Renal Syndrome in the General Ward. Clin J Am Soc Nephrol 2011;6:476-81.
87. Damman K, van Veldhuisen DJ, Navis G,
et al. Urinary neutrophil gelatinase associated lipocalin (NGAL), a marker of
tubular damage, is increased in patients with chronic HF. Eur J Heart Fail
2008;10:997-1000.
88. Poniatowski B, Malyszko J,
Bachorzewska-Gajewska H, et al. Serum neutrophil gelatinase-associated
lipocalin as a marker of renal function in patients with chronic HF and
coronary artery disease. Kidney Blood Press Res 2009;32:77-80.
89. Bolignano D, Basile G, Parisi P, et
al. Increased plasma neutrophil gelatinase-associated lipocalin levels predict
mortality in elderly patients with chronic HF. Rejuvenation Res 2009;12:7-14.
90. Damman K, Masson S, Hillege HL, et
al. Clinical outcome of renal tubular damage in chronic HF. Eur Heart J
2011;32:2705-12.
91. Dickstein K, Kjekshus J. Effects of
losartan and captopril on mortality and morbidity in high-risk patients after
acute myocardial infarction: the OPTIMAAL randomised trial. Optimal Trial in
Myocardial Infarction with Angiotensin II Antagonist Losartan. Lancet
2002;360:752-60.
92. Maisel AS, Mueller C, Fitzgerald R,
et al. Prognostic utility of plasma neutrophil gelatinase-associated lipocalin
in patients with acute HF: the NGAL EvaLuation Along with B-type NaTriuretic
Peptide in acutely decompensated HF (GALLANT) trial. Eur J Heart Fail
2011;13:846-51.
93. Macfarlane JT, Colville A, Guion A,
et al. Prospective study of aetiology and outcome of adult
lower-respiratory-tract infections in the community. Lancet 1993;341:511-4.
94. Iversen KK, Kjaergaard J, Akkan D, et
al. The prognostic importance of lung function in patients admitted with HF.
Eur J Heart Fail 2010;12:685-91.
95. Sandek A, Springer J, Habedank D, et
al. Procalcitonin-guided antibiotic treatment in HF. Lancet 2004;363:1555;
author reply 1555-6.
96. Christ-Crain M, Jaccard-Stolz D,
Bingisser R, et al. Effect of procalcitonin-guided treatment on antibiotic use
and outcome in lower respiratory tract infections: cluster-randomised,
single-blinded intervention trial. Lancet 2004;363:600-7.
97. Maisel A, Neath SX, Landsberg J, et
al. Use of procalcitonin for the diagnosis of pneumonia in patients presenting
with a chief complaint of dyspnoea: results from the BACH (Biomarkers in Acute
HF) trial. Eur J Heart Fail 2012;14:278-86.
98. Hirano T, Yasukawa K, Harada H, et
al. Complementary DNA for a novel human interleukin (BSF-2) that induces B
lymphocytes to produce immunoglobulin. Nature 1986;324:73-6.
99. Lots M, Jirik F, Kabouridis R, et al.
BSF-2/IL-6 is costimulant for human thymocytes and T-lymphocytes. J Exp Med
1988;140:508-13.
100.
Mule JJ, McIntosh JK, Joblons DM, et al. Antitumor activity of
recombinant interleukin-6 in mice. J Exp Med 1990;171:629-35.
101.
Gauldie JC, Richards C, Harnich D, et al. Interferon s2/BSF-2 shares
identity with monocyte- derived hepatocyte stimulating factor (HSF) and
regulates the major acute phase protein response in liver cells. Proc Natl Acad
Sci USA 1987;84:7251-6.
102.
Luger TA, Krutmann J, Kirnbaner R, et al. IFN-s2/IL-6 augments the
activity of human natural killer cells. J Immunol 1989;143:1206-9.
103.
Mesri M, Altieri DC. Endothelial cell activation by leukocyte
microparticles. J Immunol 1998;161:4382-7.
104.
Loppnow H, Libby P. Proliferating or interleukin 1-activated human
vascular smooth muscle cells secrete copious interleukin 6. J Clin Invest
1990;85:731-8.
105.
Gwechenberger M, Mendoza LH, Youker KA, et al. Cardiac myocytes produce
interleukin-6 in culture and inviable border zone of reperfused infarctions.
Circulation 1999;99:546-51.
106.
Kaneko K, Kanda T, Yokoyama T, et al. Expression of interleukin-6 in the
ventricles and coronary arteries of patients with myocardial infarction. Res
Commun Mol Pathol Pharmacol 1997;97:3-12.
107.
Raymond RJ, Dehmer GJ, Theoharides TC, et al. Elevated interleukin-6
levels in patients with asymptomatic left ventricular systolic dysfunction. Am
Heart J 2001;141:435-8.
108.
Tsutamoto T, Hisanaga T, Wada A, et al. Interleukin-6 spillover in the
peripheral circulation increases with the severity of heart failure, and the
high plasma level of interleukin-6 is an important prognostic predictor in
patients with congestive heart failure. J Am Coll Cardiol 1998;31:391-8.
109.
Birks EJ, Yacoub MH. The role of nitric oxide and cytokines in heart
failure. Coron Artery Dis 1997;8:389-402.
110.
Kubota T, Miyagishima M, Alvarez RJ, et al. Expression of
proinflammatory cytokines in the failing human heart: comparison of
recent-onset and end-stage congestive heart failure. J Heart Lung Transplant
2000;19:819-24.
111.
Pudil R, Tichy M, Andrys C, et al. Plasma interleukin-6 is associated
with NT-proBNP level and predict short and long term mortality in patients with
acute heart failure. Acta Med (Hradec Kralove) 2010;53:225-8.
112.
Maeda K, Tsutamoto T, Wada A, et al. High levels of plasma brain
natriuretic peptide and interleukin-6 after optimized treatment for heart
failure are independent risk factors for morbidity and mortality in patients
with congestive heart failure. J Am Coll Cardiol 2000;36:1587-93.
113.
Itoh N, Yonehara S, Ishii A, et al. The polypeptide encoded by the cDNA
for human cell surface antigen Fas can mediate apoptosis. Cell 1991;66:233-43.
114.
Oehm A, Behrmann I, Falk W, et al. Purification and molecular cloning of
the Apo-1 cell surface antigen, a member of the tumor necrosis factor/nerve
growth receptor superfamily. J Biol Chem 1992;267:10709-15.
115.
Tanaka M, Itoh H, Adachi S, et al. Hypoxia induces apoptosis with
enhanced expression of Fas antigen messenger RNA in cultured neonatal rat
cardiomyocytes. Circ Res 1994;75:426-33.
116.
Cheng W, Li B, Kajstura J, et al. Stretch induced programmed myocyte
cell death. L clin Invest 1995; 96:2247-59.
117.
Cheng J, Zhou T, Liu C, et al. Protection from Fas mediated apoptosis by
a soluble form of the Fas molecule. Science 1994;263:1759-62.
118.
Okuyama M, Yamaguchi S, Nozaki N, et al. Serum levels of soluble form of
Fas molecule in patients with congestive heart failure. Am J Cardiol
1997;79:1698-701.
119.
Tsutamoto T, Wada A, Maeda K, et al. Relationship between plasma levels
of cardiac natriuretic peptides and soluble Fas: Plasma soluble Fas as a
prognostic predictor in patients with congestive heart failure. J Card Fail
2001;7:322-8.
120.
Levine B, Kalman J, Mayer L, et al. Elevated circulating levels of tumor
necrosis factor in severe chronic heart failure. N Engl J Med 1990;323:236-41.
121.
Kleinbongard P, Schulz R, Heusch G. TNFa in myocardial ischemia/reperfusion,
remodeling and heart failure. Heart Fail Rev 2011;16:49-69.
122.
Deswal A, Petersen NJ, Feldman AM, et al. Cytokines and cytokine
receptors in advanced heart failure: an analysis of the cytokine database from
the Vesnarinone trial (VEST). Circulation 2001;103:2055-9.
123.
Chrysohoou C, Pitsavos C, Barbetseas J, et al. Chronic systemic
inflammation accompanies impaired ventricular diastolic function, detected by
Doppler imaging, in patients with newly diagnosed systolic heart failure
(Hellenic Heart Failure Study). Heart Vessels 2009;24:22-6.
124.
Valgimigli M, Ceconi C, Malagutti P, et al. Tumor necrosis factor-alpha
receptor 1 is a major predictor of mortality and new-onset heart failure in patients
with acute myocardial infarction: the Cytokine-Activation and Long-Term
Prognosis in Myocardial Infarction (C-ALPHA) study. Circulation
2005;111:863-70.
125.
Berton G, Cordiano R, Palmieri R, et al. C-reactive protein in acute
myocardial infarction: association with heart failure. Am Heart J
2003;145:1094-101.
126.
Yin WH, Chen JW, Jen HL, et al. Independent prognostic value of elevated
high-sensitivity C-reactive protein in chronic heart failure. Am Heart J
2004;147:931-8.
127.
Chirinos JA, Zambrano JP, Chakko S, et al. Usefulness of C-reactive
protein as an independent predictor of death in patients with ischemic
cardiomyopathy. Am J Cardiol 2005;95:88-90.
128.
Cesari M, Penninx BW, Newman AB, et al. Inflammatory markers and onset
of cardiovascular events: results from the Health ABC study. Circulation
2003;108:2317-22.
129.
Boekholdt SM, Hack CE, Sandhu MS, et al. C-reactive protein levels and
coronary artery disease incidence and mortality in apparently healthy men and
women: the EPIC-Norfolk prospective population study 1993-2003. Atherosclerosis
2006;187:415-22.
130.
Engström G, Melander O, Hedblad B. Carotid intima-media thickness,
systemic inflammation, and incidence of heart failure hospitalizations.
Arterioscler Thromb Vasc Biol 2009;29:1691-5.
131.
Oikonomou E, Tousoulis D, Siasos G, et al. The role of inflammation in
heart failure: new therapeutic approaches. Hellenic J Cardiol 2011;52:30-40.
132.
Dubin R, Li Y, Ix JH, et al. Associations of pentraxin-3 with
cardiovascular events, incident heart failure, and mortality among persons with
coronary heart disease: data from the Heart and Soul Study. Am Heart J
2012;163:274-9.
133.
Suzuki S, Takeishi Y, Niizeki T, et al. Pentraxin 3, a new marker for
vascular inflammation, predicts adverse clinical outcomes in patients with
heart failure. Am Heart J 2008;155:75-81.
134.
Kotooka N, Inoue T, Aoki S, et al. Prognostic value of pentraxin 3 in
patients with chronic heart failure. Int J Cardiol 2008;130:19-22.
135.
Matsubara J, Sugiyama S, Nozaki T, et al. Pentraxin 3 is a new
inflammatory marker correlated with left ventricular diastolic dysfunction and
heart failure with normal ejection fraction. J Am Coll Cardiol 2011;57:861-9.
136.
Vita JA, Brennan ML, Gokce N. Serum myeloperoxidase levels independently
predict endothelial dysfunction in humans. Circulation 2004;110:1134-9.
137.
Tang WH, Katz R, Brennan ML. Usefulness of myeloperoxidase levels in
healthy elderly subjects to predict risk of developing heart failure. Am J
Cardiol 2009;103:1269-74.
138.
Reichlin T, Socrates T, Egli P. Use of myeloperoxidase for risk stratification
in acute heart failure. Clin Chem 2010;56:944-51.
139.
Brennan ML, Penn MS, Van Lente F, et al. Prognostic value of
myeloperoxidase in patients with chest pain. N Engl J Med 2003;349:1595-604.
140.
Cavusoglu E, Ruwende C, Eng C, et al. Usefulness of baseline plasma
myeloperoxidase levels as an independent predictor of myocardial infarction at
two years in patients presenting with acute coronary syndrome. Am J Cardiol
2007;99:1364-8.
141.
Baldus S, Heeschen C, Meinertz T, et al. Myeloperoxidase serum levels
predict risk in patients with acute coronary syndromes. Circulation
2003;108:1440-5.
142.
Tang WH, Brennan ML, Philip K, et al. Plasma myeloperoxidase levels in
patients with chronic heart failure. Am J Cardiol 2006;98:796-9.
143.
Michowitz Y, Kisil S, Guzner-Gur H, et al. Usefulness of serum
myeloperoxidase in prediction of mortality in patients with severe heart
failure. Isr Med Assoc J 2008;10:884-8.
144.
Tang WH, Tong W, Troughton RW, et al. Prognostic value and
echocardiographic determinants of plasma myeloperoxidase levels in chronic
heart failure. J Am Coll Cardiol 2007;49:2364-70.
145.
Cohn JN, Levine TB, Olivari MT, et al. Plasma norepinephrine as a guide
to prognosis in patients with chronic congestive heart failure. N Engl J Med
1984;311:819-23.
146.
Packer M. The neurohormonal hypothesis: a theory to explain the
mechanism of disease progression in heart failure. J Am Coll Cardiol
1992;20:248-54.
147.
Swedberg K, Eneroth P, Kjekshus J, et al. Hormones regulating
cardiovascular function in patients with severe congestive heart failure and
their relation to mortality. CONSENSUS Trial Study Group. Circulation
1990;82:1730-6.
148.
Francis GS. Neurohormonal control of heart failure. Cleve Clin J Med
2011;78:S75-9.
149.
Latini R, Masson S, Anand I, et al. Val-HeFT Investigators. The
comparative prognostic value of plasma neurohormones at baseline in patients
with heart failure enrolled in Val-HeFT. Eur Heart J 2004;25:292-9.
150.
Givertz MM, Braunwald E. Neurohormones in heart failure: predicting
outcomes, optimizing care. Eur Heart J 2004;25:281-2.
151.
Milo-Cotter O, Cotter-Davison B, Lombardi C, et al. Neurohormonal
activation in acute heart failure: results from VERITAS. Cardiology
2011;119:96-105.
152.
Vergaro G, Emdin M, Iervasi A, et al. Prognostic value of plasma renin
activity in heart failure. Am J Cardiol 2011;108:246-51.
153.
Hülsmann M, Stanek B, Frey B, et al. Value of cardiopulmonary exercise
testing and big endothelin plasma levels to predict short-term prognosis of
patients with chronic heart failure. J Am Coll Cardiol 1998;32:1695-700.
154.
Braunwald E. Biomarkers in heart failure. N Engl J Med 2008;358:2148-59.
155.
Sabatine MS, Morrow DA, de Lemos JA, et al. Evaluation of multiple
biomarkers of cardiovascular stress for risk prediction and guiding medical
therapy in patients with stable coronary disease. Circulation 2012;125:233-40.
156.
Jankowska EA, Filippatos GS, von Haehling S, et al. Identification of
chronic heart failure patients with a high 12-month mortality risk using
biomarkers including plasma C-terminal pro-endothelin-1. PLoS ONE
2011;6:e14506.
157.
Teerlink JR. The role of endothelin in the pathogenesis of heart
failure. Curr Cardiol Rep 2002;4:206-12.
158.
Goldsmith SR. The role of vasopressin in congestive heart failure. Cleve
Clin J Med 2006;73:S19-23.
159.
Morgenthaler NG. Copeptin: a biomarker of cardiovascular and renal
function. Congest Heart Fail 2010;16:S37-44.
160.
Maisel A, Xue Y, Shah K, et al. Increased 90-day mortality in patients
with acute heart failure with elevated copeptin: secondary results from the
Biomarkers in Acute Heart Failure (BACH) study. Circ Heart Fail 2011;4:613-20.
161.
Balling L, Kistorp C, Schou M, et al. Plasma copeptin levels and
prediction of outcome in heart failure outpatients: relation to hyponatremia
and loop diuretic doses. J Card Fail 2012;18:351-8.
162.
Neuhold S, Huelsmann M, Strunk G, et al. Comparison of copeptin, B-type
natriuretic peptide, and amino-terminal pro-B-type natriuretic peptide in
patients with chronic heart failure: prediction of death at different stages of
the disease. J Am Coll Cardiol 2008;52:266-72.
163.
Spinale FG. Myocardial matrix remodeling and the matrix
metalloproteinases: influence on cardiac form and function. Physiol Rev
2007;87:1285-342.
164.
Zile MR, Desantis SM, Baicu CF, et al. Plasma biomarkers that reflect
determinants of matrix composition identify the presence of left ventricular
hypertrophy and diastolic heart failure. Circ Heart Fail 2011;4:246-56.
165.
Martos R, Baugh J, Ledwidge M, et al. Diagnosis of heart failure with
preserved ejection fraction: improved accuracy with the use of markers of
collagen turnover. Eur J Heart Fail 2009;11:191-7.
166.
Vorovich EE, Chuai S, Li M, et al. Comparison of matrix
metalloproteinase 9 and brain natriuretic peptide as clinical biomarkers in
chronic heart failure. Am Heart J 2008;155:992-7.
167.
Frantz S, Störk S, Michels K, et al. Tissue inhibitor of
metalloproteinases levels in patients with chronic heart failure: an
independent predictor of mortality. Eur J Heart Fail 2008;10:388-95.
Refbacks
·
There are currently no refbacks.
AME Publishing Company
Pioneer Bioscience
Publishing Company
Publishing Company
Links
Copyright © 2011 - 2012 AME
Publishing Company. All rights reserved.